# Autonomous Loading System for Load-Haul-Dump (LHD) Machines Used in Underground Mining
## 3 Proposed Autonomous Loading System  
### Methodology Overview  
The hardware used in this work included a full-scale LHD machine (a GHH LF11H with 11-ton traming capacity and hydraulic powertrain) retrofitted with two 2D laser scanners (SICK LMS511), encoders in all joints (IFM RN7012), pressure sensors along the bucket's tilt and the boom's lift hydraulic lines (manufacturer specific, 600 bar), and an onboard industrial computer (Advantech ARK-2151-59 AIE) (see Figure 1). All components are of industrial grade, suitable for the rigorous environment of underground mining, and readily available as off-the-shelf components used widely in a broad range of commercial applications. In order to better integrate the system with commercial autonomous navigation solutions for LHDs, which only use 2D scanners, 3D laser scanners were not used in the current version of the proposed system. The software implementation was performed using ROS as the central middleware [28], CABSL library [29] for state-machine codification, and ROS actions to interface with the main processing function in each state. The system was initially developed and tested in a simulated environment using Gazebo [30].  
An autonomous loading routine can be thought of as a sequence of several steps that perform specific actions, as presented in the diagram of Figure 2. There, rock pile identification is the process of finding the draw point's location and status (whether it is suited for loading or not). Positioning refers to orienting the LHD machine to ensure that a forward thrust will end in a collision with the rock pile. Charging is the step that considers lowering the bucket and accelerating towards the pile. Excavation is the machine control that performs the digging action. Pull back comprises the backward motion of the vehicle and bucket shake. Finally, Payload weighing estimates the amount of ore loaded. Most of the mentioned steps could fail due to the highly variable environment in underground mining. It is possible that the onboard sensors fail to find the rock pile accurately or that the machine positioning cannot avoid colliding with a tunnel wall. The collision between the machine and the rock pile might not be detected, and the LHD's bucket could become stuck during excavation. In any of these cases, human assistance would be required to overcome the problematic situation. In fact, human interaction with automated mobile machines for mining operations is needed in the state-of-the-art systems, at the very least to supervise a fleet of machines. Since large-scale operations have a fleet of vehicles, it is common for one or more operators to supervise and assist multiple semi-autonomous machinery, as each machine does not require constant attention. For these reasons, in our view, it is imperative that this human interaction is considered at the design stage of the autonomous loading system and, thus, included in the formulation of the agent's behavior. Figure 6 shows the proposed state machine for the autonomous loading process with the human in the loop. There are two assistance states: positioning assistance allows the operator to take control of the machine to position it in front of the rock pile, while loading assistance provides the operator with full control of the LHD to perform the remaining parts of the loading maneuver up until payload weighing, which is needed to record the performance of the task. The positioning assistance is called either when the rock pile identification cannot characterize the rock or when positioning is not able to place the LHD to start the charging procedure, while loading assistance is called when the charging, the excavation, or the pull back procedures cannot be successfully completed.