A multi-agent path planning algorithm based on hierarchical reinforcement learning and artificial potential field.
Yanbin ZhengBo LiDeyu AnNa LiPublished in: ICNC (2015)
Keyphrases
- potential field
- path planning
- path planning algorithm
- hierarchical reinforcement learning
- multi agent
- reinforcement learning
- state abstraction
- mobile robot
- path finding
- dynamic environments
- multi robot
- collision avoidance
- obstacle avoidance
- multiple robots
- model free
- optimal path
- multi agent systems
- motion planning
- state space
- indoor environments
- collision free
- reward function
- autonomous navigation
- markov decision processes
- learning algorithm
- intelligent agents
- unknown environments
- markov decision process
- simulated annealing
- multiple agents