LiDAR Based Traversable Regions Identification Method for Off-Road UGV Driving

Shan, Yunxiao; Fu, Yao; Chen, Xiangchun; Lin, Hongquan; Zhang, Ziquan; Lin, Jun; Huang, Kai

doi:10.1109/tiv.2023.3342801

IEEE Trans. Intell. Veh.

2024

DOI: 10.1109/tiv.2023.3342801

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LiDAR Based Traversable Regions Identification Method for Off-Road UGV Driving

Yunxiao Shan,

Yao Fu,

Xiangchun Chen

et al.

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An Autonomous Cooperative Navigation Approach for Multiple Unmanned Ground Vehicles in a Variable Communication Environment

Lin,

Huang

2024

Electronics

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Robots assist emergency responders by collecting critical information remotely. Deploying multiple cooperative unmanned ground vehicles (UGVs) for a response can reduce the response time, improve situational awareness, and minimize costs. Reliable communication is critical for multiple UGVs for environmental response because multiple robots need to share information for cooperative navigation and data collection. In this work, we investigate a control policy for optimal communication among multiple UGVs and base stations (BSs). A multi-agent deep deterministic policy gradient (MADDPG) algorithm is proposed to update the control policy for the maximum signal-to-interference ratio. The UGVs communicate with both the fixed BSs and a mobile BS. The proposed control policy can navigate the UGVs and mobile BS to optimize communication and signal strength. Finally, a genetic algorithm (GA) is proposed to optimize the hyperparameters of the MADDPG-based training. Simulation results demonstrate the computational efficiency and robustness of the GA-based MADDPG algorithm for the control of multiple UGVs.

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An Autonomous Cooperative Navigation Approach for Multiple Unmanned Ground Vehicles in a Variable Communication Environment

Lin,

Huang

2024

Electronics

View full text Add to dashboard Cite

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LiDAR Based Traversable Regions Identification Method for Off-Road UGV Driving

Cited by 1 publication

References 38 publications

An Autonomous Cooperative Navigation Approach for Multiple Unmanned Ground Vehicles in a Variable Communication Environment

An Autonomous Cooperative Navigation Approach for Multiple Unmanned Ground Vehicles in a Variable Communication Environment

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