Path Planning Method Using Dyna-Q Algorithm under Complex Urban Environment
- Resource Type
- Conference
- Authors
- Huang, Jingyi; Tan, Qingke; Ma, Jiming; Han, Liang
- Source
- 2022 China Automation Congress (CAC) Automation Congress (CAC), 2022 China. :6776-6781 Nov, 2022
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Atmospheric modeling
Heuristic algorithms
Urban areas
Reinforcement learning
Autonomous aerial vehicles
Path planning
Task analysis
Dyna-Q
path planning
UGV
simulation platform
- Language
- ISSN
- 2688-0938
Path planning and obstacle avoidance problems are now the focus of robotics research. This paper uses the Dyna-Q reinforcement learning algorithm to implement an obstacle avoidance and a path planning algorithm for unmanned ground vehicle(UGV) under urban environment. Using the reinforcement learning algorithm, we calculate the waypoints of the unmanned vehicle and achieve obstacle avoidance tasks and path planning using a vector field. Finally, we use a PID controller on unmanned aerial vehicle (UAV) to realize the air-ground collaboration task. The algorithms and the agents’ modeling in this paper are implemented in the lab’s simulation platform.