Highly optimized Q-learning-based bees approach for mobile robot path planning in static and dynamic environments.
Talal BonnyMariam KashkashPublished in: J. Field Robotics (2022)
Keyphrases
- dynamic environments
- robot path planning
- highly optimized
- path planning
- path planner
- potential field
- general purpose
- mobile robot
- single agent
- special purpose
- reinforcement learning algorithms
- international space station
- autonomous agents
- reinforcement learning
- collision avoidance
- cooperative
- collision free
- multi agent
- agent systems
- changing environment
- state space
- highly dynamic environments
- multi robot
- obstacle avoidance
- motion planning
- action selection
- route planning
- multi modal
- robot soccer
- real environment
- optimal policy
- path finding
- optimal path
- dynamic programming
- degrees of freedom
- reinforcement learning agents
- rigid body
- learning algorithm