# Controlling Industrial Robotic Arms Using Gyroscopic and Gesture Inputs from a Smartwatch
## 3 Methodology and Infrastructure
The plot illustrates time (seconds) on the X-axis and angular velocity (rad/s) on the Y-axis across all three rotational axes: X (blue), Y (green), and Z (orange). Peaks in the Z-axis indicate clockwise wrist rotations. This figure serves as a reference for baseline gesture detection. Advantages of Research and Reproducibility  
Access to both raw and processed sensor data improves transparency in the human-machine interaction process. It improves uniformity in experimental setups and facilitates comparative evaluations among different signal processing techniques. Furthermore, it promotes ongoing advancements in wearable robotics, human-machine interface design, and intuitive robot programming. Figure 2 illustrates the time progression of gyroscope sensor values from the smartwatch and their analysis within the context of robotic control. 1. Immediate Surveillance  
The graph on the left depicts fluctuations in angular velocity over time across all three axes. The primary variation on the Y-axis indicates rotational motion, which might be associated with a robotic arm rotation command. 2. Immediate Feedback  
The bar chart on the right encapsulates the latest gyroscope measurements. This visual feedback is essential for calibration and aids in identifying the prevailing direction of movement at a given moment. 3. Functional Utility  
It facilitates the operator's evaluation of the gesture's strength and clarity for system recognition. It assists developers in identifying sensor anomalies or delays in data processing. 4. Scientific Contribution  
This type of visualization supports research on sensor fusion optimization by providing insight into the stability and reliability of gyroscope data during gesture-based robotic control. The code presented above, Algorithm 1, initializes the smartwatch-based robot control system. It configures control modes, gesture state tracking, and sensor filtering parameters and initializes the robotic arm using the xArm Python SDK 1.15.0 API. It sets thresholds for motion filtering, response smoothing, and communication intervals, providing the core runtime environment for real-time gesture processing and robot movement. Figure 2: Real-time gyroscope visualization from the smartwatch interface. (**a**) Continuous angular velocity (rad/s) over time for each axis—X (red), Y (green), and Z (blue). (**b**) Current gyroscope readings with color-coded bar display. This interface provides immediate sensor feedback to assist gesture calibration and system responsiveness. ```
1. class RoboticArmWatch(Watch)
2. \"\"\"
3. Control a robotic arm using a smartwatch via TouchSDK. 4. This class processes sensor data from the watch to extract
5. position information and control the robotic arm. 6. \"\"\"
7. def _init_(self, name_filter=None, robot_ip=\"192.168.1.160\"):
8. \"\"\"Initialize the robotic arm controller.\"\"\"
9. super().__init_(name_filter)
10. # Control state
11. self.active = False
12. self.mode = ControlMode.POSITION
13. self.last_tap_time = 0
14. self.double_tap_threshold = 0.5 # seconds
15. self.threading = False
16. # Position tracking
17. self.current_position = {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}
18. self.target_position = {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}
19. self.reference_orientation = None
20. self.reference_acceleration = None
21. self.last_update_time = time.time()
22. # Motion processing parameters
23. self.position_scale = 100.0 # Scale factor for position mode
24. self.orientation_scale = 2.0 # Scale factor for orientation mode
25. self.movement_threshold = 0.1 # Increased minimum movement to register (was 0.05)
26. self.smoothing_alpha = 0.3 # Low-pass filter coefficient (0-1)--slightly more responsive
27. # Robot control parameters
28. self.update_interval = 0.2 # Send position updates at most every 200 ms
29. self.last_send_time = 0
30. self.position_change_threshold = 5.0 # Minimum position change to send update (mm)
31. self.speed_factor = 50 # Speed factor for robot movement (mm/s)
32. self.max_speed = 200 # Maximum speed (mm/s)
33.