Upload folder using huggingface_hub

.gitattributes

@@ -53,3 +53,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+scenes/blender/car_base.blend filter=lfs diff=lfs merge=lfs -text
+scenes/blender/house.blend filter=lfs diff=lfs merge=lfs -text
+scenes/blender/trees.blend filter=lfs diff=lfs merge=lfs -text
+scenes/blender/windmill.blend filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,25 @@
+---
+library_name: godot-rl
+tags:
+- deep-reinforcement-learning
+- reinforcement-learning
+- godot-rl
+- environments
+- video-games
+---
+
+A RL environment called HovercraftRacing for the Godot Game Engine.
+
+This environment was created with: https://github.com/edbeeching/godot_rl_agents 
+
+
+## Downloading the environment 
+
+After installing Godot RL Agents, download the environment with: 
+
+```
+gdrl.env_from_hub -r edbeeching/godot_rl_HovercraftRacing
+```
+
+
+

RacingExample.csproj

@@ -0,0 +1,10 @@
+<Project Sdk="Godot.NET.Sdk/4.2.1">
+  <PropertyGroup>
+    <TargetFramework>net6.0</TargetFramework>
+    <EnableDynamicLoading>true</EnableDynamicLoading>
+    <RootNamespace>GodotRLAgents</RootNamespace>
+  </PropertyGroup>
+  <ItemGroup>
+    <PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.15.1" />
+  </ItemGroup>
+</Project>

RacingExample.csproj.old

@@ -0,0 +1,10 @@
+<Project Sdk="Godot.NET.Sdk/4.2.0">
+  <PropertyGroup>
+    <TargetFramework>net6.0</TargetFramework>
+    <EnableDynamicLoading>true</EnableDynamicLoading>
+    <RootNamespace>GodotRLAgents</RootNamespace>
+  </PropertyGroup>
+  <ItemGroup>
+    <PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.15.1" />
+  </ItemGroup>
+</Project>

RacingExample.sln

@@ -0,0 +1,19 @@
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio 2012
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "RacingExample", "RacingExample.csproj", "{E2999C40-6DD8-43BC-9D9A-473B12290385}"
+EndProject
+Global
+	GlobalSection(SolutionConfigurationPlatforms) = preSolution
+	Debug|Any CPU = Debug|Any CPU
+	ExportDebug|Any CPU = ExportDebug|Any CPU
+	ExportRelease|Any CPU = ExportRelease|Any CPU
+	EndGlobalSection
+	GlobalSection(ProjectConfigurationPlatforms) = postSolution
+		{E2999C40-6DD8-43BC-9D9A-473B12290385}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{E2999C40-6DD8-43BC-9D9A-473B12290385}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{E2999C40-6DD8-43BC-9D9A-473B12290385}.ExportDebug|Any CPU.ActiveCfg = ExportDebug|Any CPU
+		{E2999C40-6DD8-43BC-9D9A-473B12290385}.ExportDebug|Any CPU.Build.0 = ExportDebug|Any CPU
+		{E2999C40-6DD8-43BC-9D9A-473B12290385}.ExportRelease|Any CPU.ActiveCfg = ExportRelease|Any CPU
+		{E2999C40-6DD8-43BC-9D9A-473B12290385}.ExportRelease|Any CPU.Build.0 = ExportRelease|Any CPU
+	EndGlobalSection
+EndGlobal

addons/godot_rl_agents/controller/ai_controller_2d.gd

@@ -0,0 +1,82 @@
+extends Node2D
+class_name AIController2D
+
+@export var reset_after := 1000
+
+var heuristic := "human"
+var done := false
+var reward := 0.0
+var n_steps := 0
+var needs_reset := false
+
+var _player: Node2D
+
+func _ready():
+	add_to_group("AGENT")
+	
+func init(player: Node2D):
+	_player = player
+	
+#-- Methods that need implementing using the "extend script" option in Godot --#
+func get_obs() -> Dictionary:
+	assert(false, "the get_obs method is not implemented when extending from ai_controller") 
+	return {"obs":[]}
+
+func get_reward() -> float:	
+	assert(false, "the get_reward method is not implemented when extending from ai_controller") 
+	return 0.0
+	
+func get_action_space() -> Dictionary:
+	assert(false, "the get get_action_space method is not implemented when extending from ai_controller") 
+	return {
+		"example_actions_continous" : {
+			"size": 2,
+			"action_type": "continuous"
+		},
+		"example_actions_discrete" : {
+			"size": 2,
+			"action_type": "discrete"
+		},
+		}
+	
+func set_action(action) -> void:	
+	assert(false, "the get set_action method is not implemented when extending from ai_controller") 	
+# -----------------------------------------------------------------------------#
+	
+func _physics_process(delta):
+	n_steps += 1
+	if n_steps > reset_after:
+		needs_reset = true
+		
+func get_obs_space():
+	# may need overriding if the obs space is complex
+	var obs = get_obs()
+	return {
+		"obs": {
+			"size": [len(obs["obs"])],
+			"space": "box"
+		},
+	}
+
+func reset():
+	n_steps = 0
+	needs_reset = false
+
+func reset_if_done():
+	if done:
+		reset()
+		
+func set_heuristic(h):
+	# sets the heuristic from "human" or "model" nothing to change here
+	heuristic = h
+
+func get_done():
+	return done
+	
+func set_done_false():
+	done = false
+
+func zero_reward():
+	reward = 0.0
+	
+

addons/godot_rl_agents/controller/ai_controller_3d.gd

@@ -0,0 +1,80 @@
+extends Node3D
+class_name AIController3D
+
+@export var reset_after := 1000
+
+var heuristic := "human"
+var done := false
+var reward := 0.0
+var n_steps := 0
+var needs_reset := false
+
+var _player: Node3D
+
+func _ready():
+	add_to_group("AGENT")
+	
+func init(player: Node3D):
+	_player = player
+	
+#-- Methods that need implementing using the "extend script" option in Godot --#
+func get_obs() -> Dictionary:
+	assert(false, "the get_obs method is not implemented when extending from ai_controller") 
+	return {"obs":[]}
+
+func get_reward() -> float:	
+	assert(false, "the get_reward method is not implemented when extending from ai_controller") 
+	return 0.0
+	
+func get_action_space() -> Dictionary:
+	assert(false, "the get get_action_space method is not implemented when extending from ai_controller") 
+	return {
+		"example_actions_continous" : {
+			"size": 2,
+			"action_type": "continuous"
+		},
+		"example_actions_discrete" : {
+			"size": 2,
+			"action_type": "discrete"
+		},
+		}
+	
+func set_action(action) -> void:	
+	assert(false, "the get set_action method is not implemented when extending from ai_controller") 	
+# -----------------------------------------------------------------------------#
+	
+func _physics_process(delta):
+	n_steps += 1
+	if n_steps > reset_after:
+		needs_reset = true
+		
+func get_obs_space():
+	# may need overriding if the obs space is complex
+	var obs = get_obs()
+	return {
+		"obs": {
+			"size": [len(obs["obs"])],
+			"space": "box"
+		},
+	}
+
+func reset():
+	n_steps = 0
+	needs_reset = false
+
+func reset_if_done():
+	if done:
+		reset()
+		
+func set_heuristic(h):
+	# sets the heuristic from "human" or "model" nothing to change here
+	heuristic = h
+
+func get_done():
+	return done
+	
+func set_done_false():
+	done = false
+
+func zero_reward():
+	reward = 0.0

addons/godot_rl_agents/godot_rl_agents.gd

@@ -0,0 +1,16 @@
+@tool
+extends EditorPlugin
+
+
+func _enter_tree():
+	# Initialization of the plugin goes here.
+	# Add the new type with a name, a parent type, a script and an icon.
+	add_custom_type("Sync", "Node", preload("sync.gd"), preload("icon.png"))
+	#add_custom_type("RaycastSensor2D2", "Node", preload("raycast_sensor_2d.gd"), preload("icon.png"))
+
+
+func _exit_tree():
+	# Clean-up of the plugin goes here.
+	# Always remember to remove it from the engine when deactivated.
+	remove_custom_type("Sync")
+	#remove_custom_type("RaycastSensor2D2")

addons/godot_rl_agents/icon.png.import

@@ -0,0 +1,34 @@
+[remap]
+
+importer="texture"
+type="CompressedTexture2D"
+uid="uid://dlg5s1ygj8c34"
+path="res://.godot/imported/icon.png-45a871b53434e556222f5901d598ab34.ctex"
+metadata={
+"vram_texture": false
+}
+
+[deps]
+
+source_file="res://addons/godot_rl_agents/icon.png"
+dest_files=["res://.godot/imported/icon.png-45a871b53434e556222f5901d598ab34.ctex"]
+
+[params]
+
+compress/mode=0
+compress/high_quality=false
+compress/lossy_quality=0.7
+compress/hdr_compression=1
+compress/normal_map=0
+compress/channel_pack=0
+mipmaps/generate=false
+mipmaps/limit=-1
+roughness/mode=0
+roughness/src_normal=""
+process/fix_alpha_border=true
+process/premult_alpha=false
+process/normal_map_invert_y=false
+process/hdr_as_srgb=false
+process/hdr_clamp_exposure=false
+process/size_limit=0
+detect_3d/compress_to=1

addons/godot_rl_agents/onnx/csharp/ONNXInference.cs

@@ -0,0 +1,103 @@
+using Godot;
+using Microsoft.ML.OnnxRuntime;
+using Microsoft.ML.OnnxRuntime.Tensors;
+using System.Collections.Generic;
+using System.Linq;
+
+namespace GodotONNX
+{
+	/// <include file='docs/ONNXInference.xml' path='docs/members[@name="ONNXInference"]/ONNXInference/*'/>
+	public partial class ONNXInference : GodotObject
+	{
+
+		private InferenceSession session;
+		/// <summary>
+		/// Path to the ONNX model. Use Initialize to change it. 
+		/// </summary>
+		private string modelPath;
+		private int batchSize;
+
+		private SessionOptions SessionOpt;
+
+		//init function
+		/// <include file='docs/ONNXInference.xml' path='docs/members[@name="ONNXInference"]/Initialize/*'/>
+		public void Initialize(string Path, int BatchSize)
+		{
+			modelPath = Path;
+			batchSize = BatchSize;
+            SessionOpt = SessionConfigurator.MakeConfiguredSessionOptions();
+            session = LoadModel(modelPath);
+
+		}
+		/// <include file='docs/ONNXInference.xml' path='docs/members[@name="ONNXInference"]/Run/*'/>
+		public Godot.Collections.Dictionary<string, Godot.Collections.Array<float>> RunInference(Godot.Collections.Array<float> obs, int state_ins)
+		{
+			//Current model: Any (Godot Rl Agents)
+			//Expects a tensor of shape [batch_size, input_size] type float named obs and a tensor of shape [batch_size] type float named state_ins
+
+			//Fill the input tensors
+			// create span from inputSize
+			var span = new float[obs.Count]; //There's probably a better way to do this
+			for (int i = 0; i < obs.Count; i++)
+			{
+				span[i] = obs[i];
+			}
+
+			IReadOnlyCollection<NamedOnnxValue> inputs = new List<NamedOnnxValue>
+			{
+			NamedOnnxValue.CreateFromTensor("obs", new DenseTensor<float>(span, new int[] { batchSize, obs.Count })),
+			NamedOnnxValue.CreateFromTensor("state_ins", new DenseTensor<float>(new float[] { state_ins }, new int[] { batchSize }))
+			};
+			IReadOnlyCollection<string> outputNames = new List<string> { "output", "state_outs" }; //ONNX is sensible to these names, as well as the input names
+
+			IDisposableReadOnlyCollection<DisposableNamedOnnxValue> results; 
+			//We do not use "using" here so we get a better exception explaination later
+			try
+			{
+				results = session.Run(inputs, outputNames);
+			}
+			catch (OnnxRuntimeException e)
+			{
+				//This error usually means that the model is not compatible with the input, beacause of the input shape (size)
+				GD.Print("Error at inference: ", e);
+				return null;
+			}
+			//Can't convert IEnumerable<float> to Variant, so we have to convert it to an array or something
+			Godot.Collections.Dictionary<string, Godot.Collections.Array<float>> output = new Godot.Collections.Dictionary<string, Godot.Collections.Array<float>>();
+			DisposableNamedOnnxValue output1 = results.First();
+			DisposableNamedOnnxValue output2 = results.Last();
+			Godot.Collections.Array<float> output1Array = new Godot.Collections.Array<float>();
+			Godot.Collections.Array<float> output2Array = new Godot.Collections.Array<float>();
+
+			foreach (float f in output1.AsEnumerable<float>())
+			{
+				output1Array.Add(f);
+			}
+
+			foreach (float f in output2.AsEnumerable<float>())
+			{
+				output2Array.Add(f);
+			}
+
+			output.Add(output1.Name, output1Array);
+			output.Add(output2.Name, output2Array);
+
+			//Output is a dictionary of arrays, ex: { "output" : [0.1, 0.2, 0.3, 0.4, ...], "state_outs" : [0.5, ...]}
+			results.Dispose();
+			return output;
+		}
+		/// <include file='docs/ONNXInference.xml' path='docs/members[@name="ONNXInference"]/Load/*'/>
+		public InferenceSession LoadModel(string Path)
+		{
+			using Godot.FileAccess file = FileAccess.Open(Path, Godot.FileAccess.ModeFlags.Read);
+			byte[] model = file.GetBuffer((int)file.GetLength());
+			//file.Close(); file.Dispose(); //Close the file, then dispose the reference.
+			return new InferenceSession(model, SessionOpt); //Load the model
+		}
+		public void FreeDisposables()
+		{
+			session.Dispose();
+			SessionOpt.Dispose();
+		}
+	}
+}

addons/godot_rl_agents/onnx/csharp/SessionConfigurator.cs

@@ -0,0 +1,131 @@
+using Godot;
+using Microsoft.ML.OnnxRuntime;
+
+namespace GodotONNX
+{
+	/// <include file='docs/SessionConfigurator.xml' path='docs/members[@name="SessionConfigurator"]/SessionConfigurator/*'/>
+
+	public static class SessionConfigurator
+	{
+		public enum ComputeName
+		{
+			CUDA,
+			ROCm,
+			DirectML,
+			CoreML,
+			CPU
+		}
+
+        /// <include file='docs/SessionConfigurator.xml' path='docs/members[@name="SessionConfigurator"]/GetSessionOptions/*'/>
+        public static SessionOptions MakeConfiguredSessionOptions()
+        {
+            SessionOptions sessionOptions = new();
+            SetOptions(sessionOptions);
+            return sessionOptions;
+        }
+
+        private static void SetOptions(SessionOptions sessionOptions)
+        {
+            sessionOptions.LogSeverityLevel = OrtLoggingLevel.ORT_LOGGING_LEVEL_WARNING;
+            ApplySystemSpecificOptions(sessionOptions);
+        }
+
+        /// <include file='docs/SessionConfigurator.xml' path='docs/members[@name="SessionConfigurator"]/SystemCheck/*'/>
+        static public void ApplySystemSpecificOptions(SessionOptions sessionOptions)
+        {
+            //Most code for this function is verbose only, the only reason it exists is to track
+            //implementation progress of the different compute APIs.
+
+            //December 2022: CUDA is not working. 
+
+            string OSName = OS.GetName(); //Get OS Name
+
+            //ComputeName ComputeAPI = ComputeCheck(); //Get Compute API
+            //                                         //TODO: Get CPU architecture
+
+            //Linux can use OpenVINO (C#) on x64 and ROCm on x86 (GDNative/C++)
+            //Windows can use OpenVINO (C#) on x64
+            //TODO: try TensorRT instead of CUDA
+            //TODO: Use OpenVINO for Intel Graphics
+
+            // Temporarily using CPU on all platforms to avoid errors detected with DML
+            ComputeName ComputeAPI = ComputeName.CPU;
+
+            //match OS and Compute API
+            GD.Print($"OS: {OSName} Compute API: {ComputeAPI}");
+
+            // CPU is set by default without appending necessary
+            // sessionOptions.AppendExecutionProvider_CPU(0);
+
+            /*
+            switch (OSName)
+            {
+                case "Windows": //Can use CUDA, DirectML
+                    if (ComputeAPI is ComputeName.CUDA)
+                    {
+                        //CUDA 
+                        //sessionOptions.AppendExecutionProvider_CUDA(0);
+                        //sessionOptions.AppendExecutionProvider_DML(0);
+                    }
+                    else if (ComputeAPI is ComputeName.DirectML)
+                    {
+                        //DirectML
+                        //sessionOptions.AppendExecutionProvider_DML(0);
+                    }
+                    break;
+                case "X11": //Can use CUDA, ROCm
+                    if (ComputeAPI is ComputeName.CUDA)
+                    {
+                        //CUDA
+                        //sessionOptions.AppendExecutionProvider_CUDA(0);
+                    }
+                    if (ComputeAPI is ComputeName.ROCm)
+                    {
+                        //ROCm, only works on x86 
+                        //Research indicates that this has to be compiled as a GDNative plugin
+                        //GD.Print("ROCm not supported yet, using CPU.");
+                        //sessionOptions.AppendExecutionProvider_CPU(0);
+                    }
+                    break;
+                case "macOS": //Can use CoreML
+                    if (ComputeAPI is ComputeName.CoreML)
+                    { //CoreML
+                      //TODO: Needs testing
+                        //sessionOptions.AppendExecutionProvider_CoreML(0);
+                        //CoreML on ARM64, out of the box, on x64 needs .tar file from GitHub
+                    }
+                    break;
+                default:
+                    GD.Print("OS not Supported.");
+                    break;
+            }
+            */
+        }
+
+
+        /// <include file='docs/SessionConfigurator.xml' path='docs/members[@name="SessionConfigurator"]/ComputeCheck/*'/>
+        public static ComputeName ComputeCheck()
+		{
+			string adapterName = Godot.RenderingServer.GetVideoAdapterName();
+			//string adapterVendor = Godot.RenderingServer.GetVideoAdapterVendor();
+			adapterName = adapterName.ToUpper(new System.Globalization.CultureInfo(""));
+			//TODO: GPU vendors for MacOS, what do they even use these days?
+		  
+			if (adapterName.Contains("INTEL"))
+			{
+				return ComputeName.DirectML;
+			}
+			if (adapterName.Contains("AMD") || adapterName.Contains("RADEON"))
+			{
+				return ComputeName.DirectML;
+			}
+			if (adapterName.Contains("NVIDIA"))
+			{
+				return ComputeName.CUDA;
+			}
+
+			GD.Print("Graphics Card not recognized."); //Should use CPU
+			return ComputeName.CPU;
+		}
+	}
+}

addons/godot_rl_agents/onnx/csharp/docs/ONNXInference.xml

@@ -0,0 +1,31 @@
+<docs>
+	<members name="ONNXInference">
+		<ONNXInference>
+			<summary>
+       		The main <c>ONNXInference</c> Class that handles the inference process.
+        	</summary>
+		</ONNXInference>
+   		<Initialize>
+        	<summary>
+			Starts the inference process. 
+			</summary>
+			<param name="Path">Path to the ONNX model, expects a path inside resources.</param>
+			<param name="BatchSize">How many observations will the model recieve.</param>
+		</Initialize>
+		<Run>
+			<summary>
+			Runs the given input through the model and returns the output.
+			</summary>
+			<param name="obs">Dictionary containing all observations.</param>
+			<param name="state_ins">How many different agents are creating these observations.</param>
+			<returns>A Dictionary of arrays, containing instructions based on the observations.</returns>
+		</Run>
+		<Load>
+			<summary>
+			Loads the given model into the inference process, using the best Execution provider available.
+			</summary>
+			<param name="Path">Path to the ONNX model, expects a path inside resources.</param>
+			<returns>InferenceSession ready to run.</returns>
+		</Load>
+	</members>
+</docs>

addons/godot_rl_agents/onnx/csharp/docs/SessionConfigurator.xml

@@ -0,0 +1,29 @@
+<docs>
+	<members name="SessionConfigurator">
+		<SessionConfigurator>
+			<summary>
+       		The main <c>SessionConfigurator</c> Class that handles the execution options and providers for the inference process.
+        	</summary>
+		</SessionConfigurator>
+  		<GetSessionOptions>
+    	    <summary>
+    	    Creates a SessionOptions with all available execution providers.
+    	    </summary>
+			<returns>SessionOptions with all available execution providers.</returns>
+    	</GetSessionOptions>
+    	<SystemCheck>
+        	<summary>
+        	Appends any execution provider available in the current system.  
+        	</summary>
+			<remarks>
+				This function is mainly verbose for tracking implementation progress of different compute APIs. 
+			</remarks>
+    	</SystemCheck>
+    	<ComputeCheck>
+        	<summary>
+        		Checks for available GPUs.
+        	</summary>
+			<returns>An integer identifier for each compute platform.</returns>
+    	</ComputeCheck>
+	</members>
+</docs>

addons/godot_rl_agents/onnx/wrapper/ONNX_wrapper.gd

@@ -0,0 +1,24 @@
+extends Resource
+class_name ONNXModel
+var inferencer_script = load("res://addons/godot_rl_agents/onnx/csharp/ONNXInference.cs")
+
+var inferencer = null
+
+# Must provide the path to the model and the batch size
+func _init(model_path, batch_size):
+	inferencer = inferencer_script.new()
+	inferencer.Initialize(model_path, batch_size)
+
+# This function is the one that will be called from the game, 
+# requires the observation as an array and the state_ins as an int
+# returns an Array containing the action the model takes. 
+func run_inference(obs : Array, state_ins : int) -> Dictionary:
+	if inferencer == null:
+		printerr("Inferencer not initialized")
+		return {}
+	return inferencer.RunInference(obs, state_ins)
+
+func _notification(what):
+	if what == NOTIFICATION_PREDELETE:
+		inferencer.FreeDisposables()
+		inferencer.free()

addons/godot_rl_agents/plugin.cfg

@@ -0,0 +1,7 @@
+[plugin]
+
+name="GodotRLAgents"
+description="Custom nodes for the godot rl agents toolkit	"
+author="Edward Beeching"
+version="0.1"
+script="godot_rl_agents.gd"

addons/godot_rl_agents/sensors/sensors_2d/ExampleRaycastSensor2D.tscn

@@ -0,0 +1,48 @@
+[gd_scene load_steps=5 format=3 uid="uid://ddeq7mn1ealyc"]
+
+[ext_resource type="Script" path="res://addons/godot_rl_agents/sensors/sensors_2d/RaycastSensor2D.gd" id="1"]
+
+[sub_resource type="GDScript" id="2"]
+script/source = "extends Node2D
+
+
+
+func _physics_process(delta: float) -> void:
+    print(\"step start\")
+    
+"
+
+[sub_resource type="GDScript" id="1"]
+script/source = "extends RayCast2D
+
+var steps = 1
+
+func _physics_process(delta: float) -> void:
+    print(\"processing raycast\")
+    steps += 1
+    if steps % 2:
+        force_raycast_update()
+
+    print(is_colliding())
+"
+
+[sub_resource type="CircleShape2D" id="3"]
+
+[node name="ExampleRaycastSensor2D" type="Node2D"]
+script = SubResource("2")
+
+[node name="ExampleAgent" type="Node2D" parent="."]
+position = Vector2(573, 314)
+rotation = 0.286234
+
+[node name="RaycastSensor2D" type="Node2D" parent="ExampleAgent"]
+script = ExtResource("1")
+
+[node name="TestRayCast2D" type="RayCast2D" parent="."]
+script = SubResource("1")
+
+[node name="StaticBody2D" type="StaticBody2D" parent="."]
+position = Vector2(1, 52)
+
+[node name="CollisionShape2D" type="CollisionShape2D" parent="StaticBody2D"]
+shape = SubResource("3")

addons/godot_rl_agents/sensors/sensors_2d/GridSensor2D.gd

@@ -0,0 +1,216 @@
+@tool
+extends ISensor2D
+class_name GridSensor2D
+
+@export var debug_view := false:
+	get: return debug_view
+	set(value):
+		debug_view = value
+		_update()
+		
+@export_flags_2d_physics var detection_mask := 0:
+	get: return detection_mask
+	set(value):
+		detection_mask = value
+		_update()
+
+@export var collide_with_areas := false:
+	get: return collide_with_areas
+	set(value):
+		collide_with_areas = value
+		_update()
+
+@export var collide_with_bodies := true:
+	get: return collide_with_bodies
+	set(value):
+		collide_with_bodies = value
+		_update()
+
+@export_range(1, 200, 0.1) var cell_width := 20.0:
+	get: return cell_width
+	set(value):
+		cell_width = value
+		_update()
+
+@export_range(1, 200, 0.1) var cell_height := 20.0:
+	get: return cell_height
+	set(value):
+		cell_height = value
+		_update()	
+
+@export_range(1, 21, 2, "or_greater") var grid_size_x := 3:
+	get: return grid_size_x
+	set(value):
+		grid_size_x = value
+		_update()
+
+@export_range(1, 21, 2, "or_greater") var grid_size_y := 3:
+	get: return grid_size_y
+	set(value):
+		grid_size_y = value
+		_update()
+
+var _obs_buffer: PackedFloat64Array
+var _rectangle_shape: RectangleShape2D
+var _collision_mapping: Dictionary
+var _n_layers_per_cell: int
+
+var _highlighted_cell_color: Color
+var _standard_cell_color: Color
+
+func get_observation():
+	return _obs_buffer
+	
+func _update():
+	if Engine.is_editor_hint():
+		if is_node_ready():
+			_spawn_nodes()	
+
+func _ready() -> void:
+	_set_colors()
+	
+	if Engine.is_editor_hint():	
+		if get_child_count() == 0:
+			_spawn_nodes()
+	else:
+		_spawn_nodes()
+		
+	
+func _set_colors() -> void:
+	_standard_cell_color = Color(100.0/255.0, 100.0/255.0, 100.0/255.0, 100.0/255.0)
+	_highlighted_cell_color = Color(255.0/255.0, 100.0/255.0, 100.0/255.0, 100.0/255.0)
+
+func _get_collision_mapping() -> Dictionary:
+	# defines which layer is mapped to which cell obs index
+	var total_bits = 0
+	var collision_mapping = {} 
+	for i in 32:
+		var bit_mask = 2**i
+		if (detection_mask & bit_mask) > 0:
+			collision_mapping[i] = total_bits
+			total_bits += 1
+		
+	return collision_mapping
+
+func _spawn_nodes():
+	for cell in get_children():
+		cell.name = "_%s" % cell.name # Otherwise naming below will fail
+		cell.queue_free()
+	
+	_collision_mapping = _get_collision_mapping()
+	#prints("collision_mapping", _collision_mapping, len(_collision_mapping))
+	# allocate memory for the observations
+	_n_layers_per_cell = len(_collision_mapping)
+	_obs_buffer = PackedFloat64Array()
+	_obs_buffer.resize(grid_size_x*grid_size_y*_n_layers_per_cell)
+	_obs_buffer.fill(0)
+	#prints(len(_obs_buffer), _obs_buffer )
+	
+	_rectangle_shape = RectangleShape2D.new()
+	_rectangle_shape.set_size(Vector2(cell_width, cell_height))
+	
+	var shift := Vector2(
+		-(grid_size_x/2)*cell_width,
+		-(grid_size_y/2)*cell_height,
+	)
+	
+	for i in grid_size_x:
+		for j in grid_size_y:
+			var cell_position =  Vector2(i*cell_width, j*cell_height) + shift
+			_create_cell(i, j, cell_position)
+		
+
+func _create_cell(i:int, j:int, position: Vector2):
+	var cell : = Area2D.new()
+	cell.position = position
+	cell.name = "GridCell %s %s" %[i, j]
+	cell.modulate = _standard_cell_color
+	
+	if collide_with_areas:
+		cell.area_entered.connect(_on_cell_area_entered.bind(i, j))
+		cell.area_exited.connect(_on_cell_area_exited.bind(i, j))
+		
+	if collide_with_bodies:
+		cell.body_entered.connect(_on_cell_body_entered.bind(i, j))
+		cell.body_exited.connect(_on_cell_body_exited.bind(i, j))
+	
+	cell.collision_layer = 0
+	cell.collision_mask = detection_mask
+	cell.monitorable = true
+	add_child(cell)
+	cell.set_owner(get_tree().edited_scene_root)
+
+	var col_shape : = CollisionShape2D.new()
+	col_shape.shape = _rectangle_shape
+	col_shape.name = "CollisionShape2D"
+	cell.add_child(col_shape)
+	col_shape.set_owner(get_tree().edited_scene_root)
+	
+	if debug_view:
+		var quad = MeshInstance2D.new()
+		quad.name = "MeshInstance2D"
+		var quad_mesh = QuadMesh.new()
+		
+		quad_mesh.set_size(Vector2(cell_width, cell_height))
+		
+		quad.mesh = quad_mesh
+		cell.add_child(quad)
+		quad.set_owner(get_tree().edited_scene_root)
+
+func _update_obs(cell_i:int, cell_j:int, collision_layer:int, entered: bool):
+	for key in _collision_mapping:
+		var bit_mask = 2**key
+		if (collision_layer & bit_mask) > 0:
+			var collison_map_index = _collision_mapping[key]
+			
+			var obs_index = (
+							(cell_i * grid_size_x * _n_layers_per_cell) + 
+							(cell_j * _n_layers_per_cell) + 
+							collison_map_index
+							)
+			#prints(obs_index, cell_i, cell_j)
+			if entered:
+				_obs_buffer[obs_index] += 1
+			else:
+				_obs_buffer[obs_index] -= 1
+
+func _toggle_cell(cell_i:int, cell_j:int):
+	var cell = get_node_or_null("GridCell %s %s" %[cell_i, cell_j])
+	
+	if cell == null:
+		print("cell not found, returning")
+		
+	var n_hits = 0
+	var start_index = (cell_i * grid_size_x * _n_layers_per_cell) + (cell_j * _n_layers_per_cell)
+	for i in _n_layers_per_cell:
+		n_hits += _obs_buffer[start_index+i]
+		
+	if n_hits > 0:
+		cell.modulate = _highlighted_cell_color
+	else:
+		cell.modulate = _standard_cell_color
+		
+func _on_cell_area_entered(area:Area2D, cell_i:int, cell_j:int):
+	#prints("_on_cell_area_entered", cell_i, cell_j)
+	_update_obs(cell_i, cell_j, area.collision_layer, true)
+	if debug_view:
+		_toggle_cell(cell_i, cell_j)
+	#print(_obs_buffer)
+
+func _on_cell_area_exited(area:Area2D, cell_i:int, cell_j:int):
+	#prints("_on_cell_area_exited", cell_i, cell_j)
+	_update_obs(cell_i, cell_j, area.collision_layer, false)
+	if debug_view:
+		_toggle_cell(cell_i, cell_j)
+
+func _on_cell_body_entered(body: Node2D, cell_i:int, cell_j:int):
+	#prints("_on_cell_body_entered", cell_i, cell_j)
+	_update_obs(cell_i, cell_j, body.collision_layer, true)
+	if debug_view:
+		_toggle_cell(cell_i, cell_j)
+
+func _on_cell_body_exited(body: Node2D, cell_i:int, cell_j:int):
+	#prints("_on_cell_body_exited", cell_i, cell_j)
+	_update_obs(cell_i, cell_j, body.collision_layer, false)
+	if debug_view:
+		_toggle_cell(cell_i, cell_j)

addons/godot_rl_agents/sensors/sensors_2d/ISensor2D.gd

@@ -0,0 +1,20 @@
+extends Node2D
+class_name ISensor2D
+
+var _obs : Array = []
+var _active := false
+
+func get_observation():
+	pass
+	
+func activate():
+	_active = true
+	
+func deactivate():
+	_active = false
+
+func _update_observation():
+	pass
+	
+func reset():
+	pass

addons/godot_rl_agents/sensors/sensors_2d/RaycastSensor2D.gd

@@ -0,0 +1,118 @@
+@tool
+extends ISensor2D
+class_name RaycastSensor2D
+
+@export_flags_2d_physics var collision_mask := 1:
+	get: return collision_mask
+	set(value):
+		collision_mask = value
+		_update()
+
+@export var collide_with_areas := false:
+	get: return collide_with_areas
+	set(value):
+		collide_with_areas = value
+		_update()
+
+@export var collide_with_bodies := true:
+	get: return collide_with_bodies
+	set(value):
+		collide_with_bodies = value
+		_update()
+
+@export var n_rays := 16.0:
+	get: return n_rays
+	set(value):
+		n_rays = value
+		_update()
+	
+@export_range(5,200,5.0) var ray_length := 200:
+	get: return ray_length
+	set(value):
+		ray_length = value
+		_update()
+@export_range(5,360,5.0) var cone_width := 360.0:
+	get: return cone_width
+	set(value):
+		cone_width = value
+		_update()
+	
+@export var debug_draw := true :
+	get: return debug_draw 
+	set(value):
+		debug_draw = value
+		_update()  
+
+
+var _angles = []
+var rays := []
+
+func _update():
+	if Engine.is_editor_hint():
+		if debug_draw:
+			_spawn_nodes()
+		else:
+			for ray in get_children():
+				if ray is RayCast2D:
+					remove_child(ray)
+
+func _ready() -> void:
+	_spawn_nodes()
+
+func _spawn_nodes():
+	for ray in rays:
+		ray.queue_free()
+	rays = []
+		
+	_angles = []
+	var step = cone_width / (n_rays)
+	var start = step/2 - cone_width/2
+	
+	for i in n_rays:
+		var angle = start + i * step
+		var ray = RayCast2D.new()
+		ray.set_target_position(Vector2(
+			ray_length*cos(deg_to_rad(angle)),
+			ray_length*sin(deg_to_rad(angle))
+		))
+		ray.set_name("node_"+str(i))
+		ray.enabled  = true
+		ray.collide_with_areas = collide_with_areas
+		ray.collide_with_bodies = collide_with_bodies
+		ray.collision_mask = collision_mask
+		add_child(ray)
+		rays.append(ray)
+		
+		
+		_angles.append(start + i * step)
+	
+
+func _physics_process(delta: float) -> void:
+	if self._active:
+		self._obs = calculate_raycasts()
+		
+func get_observation() -> Array:
+	if len(self._obs) == 0:
+		print("obs was null, forcing raycast update")
+		return self.calculate_raycasts()
+	return self._obs
+	
+
+func calculate_raycasts() -> Array:
+	var result = []
+	for ray in rays:
+		ray.force_raycast_update()
+		var distance = _get_raycast_distance(ray)
+		result.append(distance)
+	return result
+
+func _get_raycast_distance(ray : RayCast2D) -> float : 
+	if !ray.is_colliding():
+		return 0.0
+		
+	var distance = (global_position - ray.get_collision_point()).length()
+	distance = clamp(distance, 0.0, ray_length)
+	return (ray_length - distance) / ray_length
+	
+	
+	

addons/godot_rl_agents/sensors/sensors_2d/RaycastSensor2D.tscn

@@ -0,0 +1,7 @@
+[gd_scene load_steps=2 format=3 uid="uid://drvfihk5esgmv"]
+
+[ext_resource type="Script" path="res://addons/godot_rl_agents/sensors/sensors_2d/RaycastSensor2D.gd" id="1"]
+
+[node name="RaycastSensor2D" type="Node2D"]
+script = ExtResource("1")
+n_rays = 17.0

addons/godot_rl_agents/sensors/sensors_3d/ExampleRaycastSensor3D.tscn

@@ -0,0 +1,6 @@
+[gd_scene format=3 uid="uid://biu787qh4woik"]
+
+[node name="ExampleRaycastSensor3D" type="Node3D"]
+
+[node name="Camera3D" type="Camera3D" parent="."]
+transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 0.804183, 0, 2.70146)

addons/godot_rl_agents/sensors/sensors_3d/GridSensor3D.gd

@@ -0,0 +1,233 @@
+@tool
+extends ISensor3D
+class_name GridSensor3D
+
+@export var debug_view := false:
+	get: return debug_view
+	set(value):
+		debug_view = value
+		_update()
+		
+@export_flags_3d_physics var detection_mask := 0:
+	get: return detection_mask
+	set(value):
+		detection_mask = value
+		_update()
+
+@export var collide_with_areas := false:
+	get: return collide_with_areas
+	set(value):
+		collide_with_areas = value
+		_update()
+
+@export var collide_with_bodies := false:
+	# NOTE! The sensor will not detect StaticBody3D, add an area to static bodies to detect them
+	get: return collide_with_bodies
+	set(value):
+		collide_with_bodies = value
+		_update()
+
+@export_range(0.1, 2, 0.1) var cell_width := 1.0:
+	get: return cell_width
+	set(value):
+		cell_width = value
+		_update()
+
+@export_range(0.1, 2, 0.1) var cell_height := 1.0:
+	get: return cell_height
+	set(value):
+		cell_height = value
+		_update()	
+
+@export_range(1, 21, 2, "or_greater") var grid_size_x := 3:
+	get: return grid_size_x
+	set(value):
+		grid_size_x = value
+		_update()
+
+@export_range(1, 21, 2, "or_greater") var grid_size_z := 3:
+	get: return grid_size_z
+	set(value):
+		grid_size_z = value
+		_update()
+
+var _obs_buffer: PackedFloat64Array
+var _box_shape: BoxShape3D
+var _collision_mapping: Dictionary
+var _n_layers_per_cell: int
+
+var _highlighted_box_material: StandardMaterial3D
+var _standard_box_material: StandardMaterial3D
+
+func get_observation():
+	return _obs_buffer
+
+func reset():
+	_obs_buffer.fill(0)
+
+func _update():
+	if Engine.is_editor_hint():
+		if is_node_ready():
+			_spawn_nodes()	
+
+func _ready() -> void:
+	_make_materials()
+	
+	if Engine.is_editor_hint():	
+		if get_child_count() == 0:
+			_spawn_nodes()
+	else:
+		_spawn_nodes()
+	
+func _make_materials() -> void:
+	if _highlighted_box_material != null and _standard_box_material != null:
+		return
+		
+	_standard_box_material = StandardMaterial3D.new()
+	_standard_box_material.set_transparency(1) # ALPHA
+	_standard_box_material.albedo_color = Color(100.0/255.0, 100.0/255.0, 100.0/255.0, 100.0/255.0)
+	
+	_highlighted_box_material = StandardMaterial3D.new()
+	_highlighted_box_material.set_transparency(1) # ALPHA
+	_highlighted_box_material.albedo_color = Color(255.0/255.0, 100.0/255.0, 100.0/255.0, 100.0/255.0)
+
+func _get_collision_mapping() -> Dictionary:
+	# defines which layer is mapped to which cell obs index
+	var total_bits = 0
+	var collision_mapping = {} 
+	for i in 32:
+		var bit_mask = 2**i
+		if (detection_mask & bit_mask) > 0:
+			collision_mapping[i] = total_bits
+			total_bits += 1
+		
+	return collision_mapping
+
+func _spawn_nodes():
+	for cell in get_children():
+		cell.name = "_%s" % cell.name # Otherwise naming below will fail
+		cell.queue_free()
+	
+	_collision_mapping = _get_collision_mapping()
+	#prints("collision_mapping", _collision_mapping, len(_collision_mapping))
+	# allocate memory for the observations
+	_n_layers_per_cell = len(_collision_mapping)
+	_obs_buffer = PackedFloat64Array()
+	_obs_buffer.resize(grid_size_x*grid_size_z*_n_layers_per_cell)
+	_obs_buffer.fill(0)
+	#prints(len(_obs_buffer), _obs_buffer )
+	
+	_box_shape = BoxShape3D.new()
+	_box_shape.set_size(Vector3(cell_width, cell_height, cell_width))
+	
+	var shift := Vector3(
+		-(grid_size_x/2)*cell_width,
+		0,
+		-(grid_size_z/2)*cell_width,
+	)
+	
+	for i in grid_size_x:
+		for j in grid_size_z:
+			var cell_position =  Vector3(i*cell_width, 0.0, j*cell_width) + shift
+			_create_cell(i, j, cell_position)
+		
+
+func _create_cell(i:int, j:int, position: Vector3):
+	var cell : = Area3D.new()
+	cell.position = position
+	cell.name = "GridCell %s %s" %[i, j]
+	
+	if collide_with_areas:
+		cell.area_entered.connect(_on_cell_area_entered.bind(i, j))
+		cell.area_exited.connect(_on_cell_area_exited.bind(i, j))
+		
+	if collide_with_bodies:
+		cell.body_entered.connect(_on_cell_body_entered.bind(i, j))
+		cell.body_exited.connect(_on_cell_body_exited.bind(i, j))
+		
+#		cell.body_shape_entered.connect(_on_cell_body_shape_entered.bind(i, j))
+#		cell.body_shape_exited.connect(_on_cell_body_shape_exited.bind(i, j))
+	
+	cell.collision_layer = 0
+	cell.collision_mask = detection_mask
+	cell.monitorable = true
+	cell.input_ray_pickable = false
+	add_child(cell)
+	cell.set_owner(get_tree().edited_scene_root)
+
+	var col_shape : = CollisionShape3D.new()
+	col_shape.shape = _box_shape
+	col_shape.name = "CollisionShape3D"
+	cell.add_child(col_shape)
+	col_shape.set_owner(get_tree().edited_scene_root)
+	
+	if debug_view:
+		var box = MeshInstance3D.new()
+		box.name = "MeshInstance3D"
+		var box_mesh = BoxMesh.new()
+		
+		box_mesh.set_size(Vector3(cell_width, cell_height, cell_width))
+		box_mesh.material = _standard_box_material
+		
+		box.mesh = box_mesh
+		cell.add_child(box)
+		box.set_owner(get_tree().edited_scene_root)
+
+func _update_obs(cell_i:int, cell_j:int, collision_layer:int, entered: bool):
+	for key in _collision_mapping:
+		var bit_mask = 2**key
+		if (collision_layer & bit_mask) > 0:
+			var collison_map_index = _collision_mapping[key]
+			
+			var obs_index = (
+							(cell_i * grid_size_x * _n_layers_per_cell) + 
+							(cell_j * _n_layers_per_cell) + 
+							collison_map_index
+							)
+			#prints(obs_index, cell_i, cell_j)
+			if entered:
+				_obs_buffer[obs_index] += 1
+			else:
+				_obs_buffer[obs_index] -= 1
+
+func _toggle_cell(cell_i:int, cell_j:int):
+	var cell = get_node_or_null("GridCell %s %s" %[cell_i, cell_j])
+	
+	if cell == null:
+		print("cell not found, returning")
+		
+	var n_hits = 0
+	var start_index = (cell_i * grid_size_x * _n_layers_per_cell) + (cell_j * _n_layers_per_cell)
+	for i in _n_layers_per_cell:
+		n_hits += _obs_buffer[start_index+i]
+		
+	var cell_mesh = cell.get_node_or_null("MeshInstance3D")
+	if n_hits > 0:
+		cell_mesh.mesh.material = _highlighted_box_material
+	else:
+		cell_mesh.mesh.material = _standard_box_material
+		
+func _on_cell_area_entered(area:Area3D, cell_i:int, cell_j:int):
+	#prints("_on_cell_area_entered", cell_i, cell_j)
+	_update_obs(cell_i, cell_j, area.collision_layer, true)
+	if debug_view:
+		_toggle_cell(cell_i, cell_j)
+	#print(_obs_buffer)
+
+func _on_cell_area_exited(area:Area3D, cell_i:int, cell_j:int):
+	#prints("_on_cell_area_exited", cell_i, cell_j)
+	_update_obs(cell_i, cell_j, area.collision_layer, false)
+	if debug_view:
+		_toggle_cell(cell_i, cell_j)
+
+func _on_cell_body_entered(body: Node3D, cell_i:int, cell_j:int):
+	#prints("_on_cell_body_entered", cell_i, cell_j)
+	_update_obs(cell_i, cell_j, body.collision_layer, true)
+	if debug_view:
+		_toggle_cell(cell_i, cell_j)
+
+func _on_cell_body_exited(body: Node3D, cell_i:int, cell_j:int):
+	#prints("_on_cell_body_exited", cell_i, cell_j)
+	_update_obs(cell_i, cell_j, body.collision_layer, false)
+	if debug_view:
+		_toggle_cell(cell_i, cell_j)

addons/godot_rl_agents/sensors/sensors_3d/ISensor3D.gd

@@ -0,0 +1,20 @@
+extends Node3D
+class_name ISensor3D
+
+var _obs : Array = []
+var _active := false
+
+func get_observation():
+	pass
+	
+func activate():
+	_active = true
+	
+func deactivate():
+	_active = false
+
+func _update_observation():
+	pass
+	
+func reset():
+	pass

addons/godot_rl_agents/sensors/sensors_3d/RGBCameraSensor3D.gd

@@ -0,0 +1,14 @@
+extends Node3D
+class_name RGBCameraSensor3D
+var camera_pixels = null
+
+@onready var camera_texture := $Control/TextureRect/CameraTexture as Sprite2D
+
+func get_camera_pixel_encoding():
+	return camera_texture.get_texture().get_image().get_data().hex_encode()
+
+func get_camera_shape()-> Array:
+	if $SubViewport.transparent_bg:
+		return [$SubViewport.size[0], $SubViewport.size[1], 4]
+	else:
+		return [$SubViewport.size[0], $SubViewport.size[1], 3]

addons/godot_rl_agents/sensors/sensors_3d/RGBCameraSensor3D.tscn

@@ -0,0 +1,41 @@
+[gd_scene load_steps=3 format=3 uid="uid://baaywi3arsl2m"]
+
+[ext_resource type="Script" path="res://addons/godot_rl_agents/sensors/sensors_3d/RGBCameraSensor3D.gd" id="1"]
+
+[sub_resource type="ViewportTexture" id="1"]
+viewport_path = NodePath("SubViewport")
+
+[node name="RGBCameraSensor3D" type="Node3D"]
+script = ExtResource("1")
+
+[node name="RemoteTransform3D" type="RemoteTransform3D" parent="."]
+remote_path = NodePath("../SubViewport/Camera3D")
+
+[node name="SubViewport" type="SubViewport" parent="."]
+size = Vector2i(32, 32)
+render_target_update_mode = 3
+
+[node name="Camera3D" type="Camera3D" parent="SubViewport"]
+near = 0.5
+
+[node name="Control" type="Control" parent="."]
+layout_mode = 3
+anchors_preset = 15
+anchor_right = 1.0
+anchor_bottom = 1.0
+grow_horizontal = 2
+grow_vertical = 2
+
+[node name="TextureRect" type="ColorRect" parent="Control"]
+layout_mode = 0
+offset_left = 1096.0
+offset_top = 534.0
+offset_right = 1114.0
+offset_bottom = 552.0
+scale = Vector2(10, 10)
+color = Color(0.00784314, 0.00784314, 0.00784314, 1)
+
+[node name="CameraTexture" type="Sprite2D" parent="Control/TextureRect"]
+texture = SubResource("1")
+offset = Vector2(9, 9)
+flip_v = true

addons/godot_rl_agents/sensors/sensors_3d/RaycastSensor3D.gd

@@ -0,0 +1,166 @@
+@tool
+extends ISensor3D
+class_name RayCastSensor3D
+@export_flags_3d_physics var collision_mask = 1:
+	get: return collision_mask
+	set(value):
+		collision_mask = value
+		_update()
+@export_flags_3d_physics var boolean_class_mask = 1:
+	get: return boolean_class_mask
+	set(value):
+		boolean_class_mask = value
+		_update()
+
+@export var n_rays_width := 6.0:
+	get: return n_rays_width
+	set(value):
+		n_rays_width = value
+		_update()
+	
+@export var n_rays_height := 6.0:
+	get: return n_rays_height
+	set(value):
+		n_rays_height = value
+		_update()
+
+@export var ray_length := 10.0:
+	get: return ray_length
+	set(value):
+		ray_length = value
+		_update()
+		
+@export var cone_width := 60.0:
+	get: return cone_width
+	set(value):
+		cone_width = value
+		_update()
+		
+@export var cone_height := 60.0:
+	get: return cone_height
+	set(value):
+		cone_height = value
+		_update()
+
+@export var collide_with_areas := false:
+	get: return collide_with_areas
+	set(value):
+		collide_with_areas = value
+		_update()
+		
+@export var collide_with_bodies := true:
+	get: return collide_with_bodies
+	set(value):
+		collide_with_bodies = value
+		_update()
+
+@export var class_sensor := false
+		
+var rays := []
+var geo = null
+
+func _update():
+	if Engine.is_editor_hint():
+		if is_node_ready():
+			_spawn_nodes()	
+
+func _ready() -> void:
+	if Engine.is_editor_hint():	
+		if get_child_count() == 0:
+			_spawn_nodes()
+	else:
+		_spawn_nodes()
+
+func _spawn_nodes():
+	print("spawning nodes")
+	for ray in get_children():
+		ray.queue_free()
+	if geo:
+		geo.clear()
+	#$Lines.remove_points()
+	rays = []
+	
+	var horizontal_step = cone_width / (n_rays_width)
+	var vertical_step = cone_height / (n_rays_height)
+	
+	var horizontal_start = horizontal_step/2 - cone_width/2
+	var vertical_start = vertical_step/2 - cone_height/2   
+
+	var points = []
+	
+	for i in n_rays_width:
+		for j in n_rays_height:
+			var angle_w = horizontal_start + i * horizontal_step
+			var angle_h = vertical_start + j * vertical_step
+			#angle_h = 0.0
+			var ray = RayCast3D.new()
+			var cast_to = to_spherical_coords(ray_length, angle_w, angle_h)
+			ray.set_target_position(cast_to)
+
+			points.append(cast_to)
+			
+			ray.set_name("node_"+str(i)+" "+str(j))
+			ray.enabled  = true
+			ray.collide_with_bodies = collide_with_bodies
+			ray.collide_with_areas = collide_with_areas
+			ray.collision_mask = collision_mask
+			add_child(ray)
+			ray.set_owner(get_tree().edited_scene_root)
+			rays.append(ray)
+			ray.force_raycast_update()
+			
+#    if Engine.editor_hint:
+#        _create_debug_lines(points)
+		
+func _create_debug_lines(points):
+	if not geo: 
+		geo = ImmediateMesh.new()
+		add_child(geo)
+		
+	geo.clear()
+	geo.begin(Mesh.PRIMITIVE_LINES)
+	for point in points:
+		geo.set_color(Color.AQUA)
+		geo.add_vertex(Vector3.ZERO)
+		geo.add_vertex(point)
+	geo.end()
+
+func display():
+	if geo:
+		geo.display()
+	
+func to_spherical_coords(r, inc, azimuth) -> Vector3:
+	return Vector3(
+		r*sin(deg_to_rad(inc))*cos(deg_to_rad(azimuth)),
+		r*sin(deg_to_rad(azimuth)),
+		r*cos(deg_to_rad(inc))*cos(deg_to_rad(azimuth))       
+	)
+	
+func get_observation() -> Array:
+	return self.calculate_raycasts()
+
+func calculate_raycasts() -> Array:
+	var result = []
+	for ray in rays:
+		ray.set_enabled(true)
+		ray.force_raycast_update()
+		var distance = _get_raycast_distance(ray)
+
+		result.append(distance)
+		if class_sensor:
+			var hit_class = 0 
+			if ray.get_collider():
+				var hit_collision_layer = ray.get_collider().collision_layer
+				hit_collision_layer = hit_collision_layer & collision_mask
+				hit_class = (hit_collision_layer & boolean_class_mask) > 0
+			result.append(hit_class)
+		ray.set_enabled(false)
+	return result
+
+func _get_raycast_distance(ray : RayCast3D) -> float : 
+	if !ray.is_colliding():
+		return 0.0
+		
+	var distance = (global_transform.origin - ray.get_collision_point()).length()
+	distance = clamp(distance, 0.0, ray_length)
+	return (ray_length - distance) / ray_length

addons/godot_rl_agents/sensors/sensors_3d/RaycastSensor3D.tscn

@@ -0,0 +1,27 @@
+[gd_scene load_steps=2 format=3 uid="uid://b803cbh1fmy66"]
+
+[ext_resource type="Script" path="res://addons/godot_rl_agents/sensors/sensors_3d/RaycastSensor3D.gd" id="1"]
+
+[node name="RaycastSensor3D" type="Node3D"]
+script = ExtResource("1")
+n_rays_width = 4.0
+n_rays_height = 2.0
+ray_length = 11.0
+
+[node name="node_1 0" type="RayCast3D" parent="."]
+target_position = Vector3(-1.38686, -2.84701, 10.5343)
+
+[node name="node_1 1" type="RayCast3D" parent="."]
+target_position = Vector3(-1.38686, 2.84701, 10.5343)
+
+[node name="node_2 0" type="RayCast3D" parent="."]
+target_position = Vector3(1.38686, -2.84701, 10.5343)
+
+[node name="node_2 1" type="RayCast3D" parent="."]
+target_position = Vector3(1.38686, 2.84701, 10.5343)
+
+[node name="node_3 0" type="RayCast3D" parent="."]
+target_position = Vector3(4.06608, -2.84701, 9.81639)
+
+[node name="node_3 1" type="RayCast3D" parent="."]
+target_position = Vector3(4.06608, 2.84701, 9.81639)

addons/godot_rl_agents/sync.gd

@@ -0,0 +1,342 @@
+extends Node
+
+# --fixed-fps 2000 --disable-render-loop
+
+enum ControlModes {HUMAN, TRAINING, ONNX_INFERENCE}
+@export var control_mode: ControlModes = ControlModes.TRAINING
+@export_range(1, 10, 1, "or_greater") var action_repeat := 8
+@export_range(1, 10, 1, "or_greater") var speed_up = 1
+@export var onnx_model_path := ""
+
+@onready var start_time = Time.get_ticks_msec()
+
+const MAJOR_VERSION := "0"
+const MINOR_VERSION := "3" 
+const DEFAULT_PORT := "11008"
+const DEFAULT_SEED := "1"
+var stream : StreamPeerTCP = null
+var connected = false
+var message_center
+var should_connect = true
+var agents
+var need_to_send_obs = false
+var args = null
+var initialized = false
+var just_reset = false
+var onnx_model = null
+var n_action_steps = 0
+
+var _action_space : Dictionary
+var _obs_space : Dictionary
+
+# Called when the node enters the scene tree for the first time.
+func _ready():
+	await get_tree().root.ready
+	get_tree().set_pause(true) 
+	_initialize()
+	await get_tree().create_timer(1.0).timeout
+	get_tree().set_pause(false) 
+	
+func _initialize():
+	_get_agents()
+	_obs_space = agents[0].get_obs_space()
+	_action_space = agents[0].get_action_space()
+	args = _get_args()
+	Engine.physics_ticks_per_second = _get_speedup() * 60 # Replace with function body.
+	Engine.time_scale = _get_speedup() * 1.0
+	prints("physics ticks", Engine.physics_ticks_per_second, Engine.time_scale, _get_speedup(), speed_up)
+	
+	_set_heuristic("human")
+	match control_mode:
+		ControlModes.TRAINING:
+			connected = connect_to_server()
+			if connected:
+				_set_heuristic("model")
+				_handshake()
+				_send_env_info()  
+			else:
+				push_warning("Couldn't connect to Python server, using human controls instead. ",
+				"Did you start the training server using e.g. `gdrl` from the console?")
+		ControlModes.ONNX_INFERENCE:
+				assert(FileAccess.file_exists(onnx_model_path), "Onnx Model Path set on Sync node does not exist: %s" % onnx_model_path)
+				onnx_model = ONNXModel.new(onnx_model_path, 1)
+				_set_heuristic("model")	
+	
+	_set_seed()
+	_set_action_repeat()
+	initialized = true  
+
+func _physics_process(_delta): 
+	# two modes, human control, agent control
+	# pause tree, send obs, get actions, set actions, unpause tree
+	if n_action_steps % action_repeat != 0:
+		n_action_steps += 1
+		return
+
+	n_action_steps += 1
+	
+	if connected:
+		get_tree().set_pause(true) 
+		
+		if just_reset:
+			just_reset = false
+			var obs = _get_obs_from_agents()
+		
+			var reply = {
+				"type": "reset",
+				"obs": obs
+			}
+			_send_dict_as_json_message(reply)
+			# this should go straight to getting the action and setting it checked the agent, no need to perform one phyics tick
+			get_tree().set_pause(false) 
+			return
+		
+		if need_to_send_obs:
+			need_to_send_obs = false
+			var reward = _get_reward_from_agents()
+			var done = _get_done_from_agents()
+			#_reset_agents_if_done() # this ensures the new observation is from the next env instance : NEEDS REFACTOR
+			
+			var obs = _get_obs_from_agents()
+			
+			var reply = {
+				"type": "step",
+				"obs": obs,
+				"reward": reward,
+				"done": done
+			}
+			_send_dict_as_json_message(reply)
+		
+		var handled = handle_message()
+	
+	elif onnx_model != null:
+		var obs : Array = _get_obs_from_agents()
+	
+		var actions = []
+		for o in obs:
+			var action = onnx_model.run_inference(o["obs"], 1.0)
+			action["output"] = clamp_array(action["output"], -1.0, 1.0)
+			var action_dict = _extract_action_dict(action["output"])
+			actions.append(action_dict)
+		
+		_set_agent_actions(actions) 
+		need_to_send_obs = true
+		get_tree().set_pause(false) 
+		_reset_agents_if_done()	
+		
+	else:
+		_reset_agents_if_done()	
+
+func _extract_action_dict(action_array: Array):
+	var index = 0
+	var result = {}
+	for key in _action_space.keys():
+		var size = _action_space[key]["size"]
+		if _action_space[key]["action_type"] == "discrete":
+			result[key] = round(action_array[index])
+		else:
+			result[key] = action_array.slice(index,index+size)
+		index += size
+		
+	return result
+
+func _get_agents():
+	agents = get_tree().get_nodes_in_group("AGENT")
+
+func _set_heuristic(heuristic):
+	for agent in agents:
+		agent.set_heuristic(heuristic)
+
+func _handshake():
+	print("performing handshake")
+	
+	var json_dict = _get_dict_json_message()
+	assert(json_dict["type"] == "handshake")
+	var major_version = json_dict["major_version"]
+	var minor_version = json_dict["minor_version"]
+	if major_version != MAJOR_VERSION:
+		print("WARNING: major verison mismatch ", major_version, " ", MAJOR_VERSION)  
+	if minor_version != MINOR_VERSION:
+		print("WARNING: minor verison mismatch ", minor_version, " ", MINOR_VERSION)
+		
+	print("handshake complete")
+
+func _get_dict_json_message():
+	# returns a dictionary from of the most recent message
+	# this is not waiting
+	while stream.get_available_bytes() == 0:
+		stream.poll()
+		if stream.get_status() != 2:
+			print("server disconnected status, closing")
+			get_tree().quit()
+			return null
+
+		OS.delay_usec(10)
+		
+	var message = stream.get_string()
+	var json_data = JSON.parse_string(message)
+	
+	return json_data
+
+func _send_dict_as_json_message(dict):
+	stream.put_string(JSON.stringify(dict, "", false))
+
+func _send_env_info():
+	var json_dict = _get_dict_json_message()
+	assert(json_dict["type"] == "env_info")
+
+		
+	var message = {
+		"type" : "env_info",
+		"observation_space": _obs_space,
+		"action_space":_action_space,
+		"n_agents": len(agents)
+		}
+	_send_dict_as_json_message(message)
+
+func connect_to_server():
+	print("Waiting for one second to allow server to start")
+	OS.delay_msec(1000)
+	print("trying to connect to server")
+	stream = StreamPeerTCP.new()
+	
+	# "localhost" was not working on windows VM, had to use the IP
+	var ip = "127.0.0.1"
+	var port = _get_port()
+	var connect = stream.connect_to_host(ip, port)
+	stream.set_no_delay(true) # TODO check if this improves performance or not
+	stream.poll()
+	# Fetch the status until it is either connected (2) or failed to connect (3)
+	while stream.get_status() < 2:
+		stream.poll()
+	return stream.get_status() == 2
+
+func _get_args():
+	print("getting command line arguments")
+	var arguments = {}
+	for argument in OS.get_cmdline_args():
+		print(argument)
+		if argument.find("=") > -1:
+			var key_value = argument.split("=")
+			arguments[key_value[0].lstrip("--")] = key_value[1]
+		else:
+			# Options without an argument will be present in the dictionary,
+			# with the value set to an empty string.
+			arguments[argument.lstrip("--")] = ""
+
+	return arguments   
+
+func _get_speedup():
+	print(args)
+	return args.get("speedup", str(speed_up)).to_int()
+
+func _get_port():    
+	return args.get("port", DEFAULT_PORT).to_int()
+
+func _set_seed():
+	var _seed = args.get("env_seed", DEFAULT_SEED).to_int()
+	seed(_seed)
+
+func _set_action_repeat():
+	action_repeat = args.get("action_repeat", str(action_repeat)).to_int()
+	
+func disconnect_from_server():
+	stream.disconnect_from_host()
+
+
+
+func handle_message() -> bool:
+	# get json message: reset, step, close
+	var message = _get_dict_json_message()
+	if message["type"] == "close":
+		print("received close message, closing game")
+		get_tree().quit()
+		get_tree().set_pause(false) 
+		return true
+		
+	if message["type"] == "reset":
+		print("resetting all agents")
+		_reset_all_agents()
+		just_reset = true
+		get_tree().set_pause(false) 
+		#print("resetting forcing draw")
+#        RenderingServer.force_draw()
+#        var obs = _get_obs_from_agents()
+#        print("obs ", obs)
+#        var reply = {
+#            "type": "reset",
+#            "obs": obs
+#        }
+#        _send_dict_as_json_message(reply)   
+		return true
+		
+	if message["type"] == "call":
+		var method = message["method"]
+		var returns = _call_method_on_agents(method)
+		var reply = {
+			"type": "call",
+			"returns": returns
+		}
+		print("calling method from Python")
+		_send_dict_as_json_message(reply)   
+		return handle_message()
+	
+	if message["type"] == "action":
+		var action = message["action"]
+		_set_agent_actions(action) 
+		need_to_send_obs = true
+		get_tree().set_pause(false) 
+		return true
+		
+	print("message was not handled")
+	return false
+
+func _call_method_on_agents(method):
+	var returns = []
+	for agent in agents:
+		returns.append(agent.call(method))
+		
+	return returns
+
+
+func _reset_agents_if_done():
+	for agent in agents:
+		if agent.get_done(): 
+			agent.set_done_false()
+
+func _reset_all_agents():
+	for agent in agents:
+		agent.needs_reset = true
+		#agent.reset()   
+
+func _get_obs_from_agents():
+	var obs = []
+	for agent in agents:
+		obs.append(agent.get_obs())
+
+	return obs
+	
+func _get_reward_from_agents():
+	var rewards = [] 
+	for agent in agents:
+		rewards.append(agent.get_reward())
+		agent.zero_reward()
+	return rewards    
+	
+func _get_done_from_agents():
+	var dones = [] 
+	for agent in agents:
+		var done = agent.get_done()
+		if done: agent.set_done_false()
+		dones.append(done)
+	return dones    
+	
+func _set_agent_actions(actions):
+	for i in range(len(actions)):
+		agents[i].set_action(actions[i])
+	
+func clamp_array(arr : Array, min:float, max:float):
+	var output : Array = []
+	for a in arr:
+		output.append(clamp(a, min, max))
+	return output

asset-license.md

@@ -0,0 +1,5 @@
+Hovercraft Racing Environment made by Ivan-267 using Godot, Godot RL Agents, and Blender. 
+
+The following license is only for the assets (.blend files) in the folder "scenes/blender":
+Author: https://github.com/Ivan-267
+License: https://creativecommons.org/licenses/by/4.0/

icon.svg.import

@@ -0,0 +1,37 @@
+[remap]
+
+importer="texture"
+type="CompressedTexture2D"
+uid="uid://b8abixqka5atk"
+path="res://.godot/imported/icon.svg-218a8f2b3041327d8a5756f3a245f83b.ctex"
+metadata={
+"vram_texture": false
+}
+
+[deps]
+
+source_file="res://icon.svg"
+dest_files=["res://.godot/imported/icon.svg-218a8f2b3041327d8a5756f3a245f83b.ctex"]
+
+[params]
+
+compress/mode=0
+compress/high_quality=false
+compress/lossy_quality=0.7
+compress/hdr_compression=1
+compress/normal_map=0
+compress/channel_pack=0
+mipmaps/generate=false
+mipmaps/limit=-1
+roughness/mode=0
+roughness/src_normal=""
+process/fix_alpha_border=true
+process/premult_alpha=false
+process/normal_map_invert_y=false
+process/hdr_as_srgb=false
+process/hdr_clamp_exposure=false
+process/size_limit=0
+detect_3d/compress_to=1
+svg/scale=1.0
+editor/scale_with_editor_scale=false
+editor/convert_colors_with_editor_theme=false

model.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0363b72528e3814052e3d156d490660cfbb5ccac7eae94506345daadcd899fea
+size 31693

project.godot

@@ -0,0 +1,51 @@
+; Engine configuration file.
+; It's best edited using the editor UI and not directly,
+; since the parameters that go here are not all obvious.
+;
+; Format:
+;   [section] ; section goes between []
+;   param=value ; assign values to parameters
+
+config_version=5
+
+[application]
+
+config/name="HovercraftRacingExample"
+run/main_scene="res://scenes/main_scene/main_scene.tscn"
+config/features=PackedStringArray("4.2", "C#", "GL Compatibility")
+config/icon="res://icon.svg"
+
+[dotnet]
+
+project/assembly_name="RacingExample"
+
+[editor_plugins]
+
+enabled=PackedStringArray("res://addons/godot_rl_agents/plugin.cfg")
+
+[input]
+
+move_forward={
+"deadzone": 0.5,
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readme.md

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+## Hovercraft Racing Environment
+
+https://github.com/edbeeching/godot_rl_agents_examples/assets/61947090/09cfa8ef-4d1a-46d3-a38a-0b7cdf1e1000
+
+A 1v1 hovercraft racing environment with:
+
+- `Human VS AI` (use `WASD` keys to control the car), or `AI vs AI` mode,
+- Adjustable number of laps (can be set to 0 for infinite race),
+- Basic powerups (push forward or push backward).
+
+### Observations:
+- Velocity of the car in local reference,
+- 3 sampled `next track points` in the car's local reference,
+- Wall detecting raycast sensor observations,
+- Other car detecting raycast sensor observations,
+- Position of the other car in the current car's local reference,
+- Position of the nearest powerup in the car's local reference,
+- Category of the powerup, as there are only two powerups it can be either `[0, 1]` or `[1, 0]`.
+
+### Action space:
+```gdscript
+func get_action_space() -> Dictionary:
+	return {
+		"acceleration": {"size": 1, "action_type": "continuous"},
+		"steering": {"size": 1, "action_type": "continuous"},
+	}
+```
+
+### Rewards:
+- Step reward based on the car's track offset difference from the previous step (advancing on the track gives a positive reward, moving backward gives a negative reward),
+- Negative step reward for moving backward,
+- Negative reward for colliding with a wall or the other car,
+- Optional reward for driving over a powerup (can be adjusted in Godot Editor in the scene of the powerup), currently set to 0 for both powerups.
+
+### Game over / episode end conditions:
+![image](https://github.com/edbeeching/godot_rl_agents_examples/assets/61947090/d9fdf617-0c4a-479e-8feb-cab9880345e6)
+
+The episode ends for each car after each lap in infinite race mode if `total laps` is set to 0, without restarting the cars,
+or if larger than 0, after the set amount of total laps has been completed by any car, in that case the winner is announced (except in training mode), and the cars are automatically restarted for the next race.
+
+`Seconds Until Race Begins` is only applicable to inference (`AI vs AI` or `Player vs AI` modes).
+
+### Running inference with the pretrained onnx model:
+![image](https://github.com/edbeeching/godot_rl_agents_examples/assets/61947090/2f9dfd2b-9835-42e0-9bf5-5f45e896967b)
+
+After opening the project in Godot, open the main_scene (should open by default), select a game mode, and click on `Play`.
+
+### Training:
+
+- Set the game mode to `Training` before starting starting training. You can use for instance the [sb3 example](https://github.com/edbeeching/godot_rl_agents/blob/main/examples/stable_baselines3_example.py) to train.
+
+- In the `game_scene`'s `Cars` node, there's a property `Number of Car Groups To Spawn` which allows multiple car groups to spawn and collect experiences during training (during inference, only 1 car group is spawned). Since this is a `1v1` example, each car group is set so a car can only collide with the other car from its own group and the walls. This is done by the car manager script by setting each car to its own physics layer and adjusting the masks (also for the raycast sensor that detects the other car). Settings this value too high may make the environment not work correctly, as there is a limit in the number of physics layers available.
+
+![image](https://github.com/edbeeching/godot_rl_agents_examples/assets/61947090/94752856-8729-4cde-8151-3aaf65bab155)
+
+
+

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