Safe multi-agent motion planning via filtered reinforcement learning.
Abraham P. VinodSleiman SafaouiAnkush ChakrabartyRien QuirynenNobuyuki YoshikawaStefano Di CairanoPublished in: ICRA (2022)
Keyphrases
- motion planning
- reinforcement learning
- multi agent
- degrees of freedom
- path planning
- mobile robot
- trajectory planning
- robot arm
- humanoid robot
- autonomous mobile robot
- state space
- robotic tasks
- multi agent environments
- multi robot
- reinforcement learning algorithms
- model free
- robotic arm
- obstacle avoidance
- mechanical systems
- single agent
- learning agents
- learning algorithm
- belief space
- configuration space
- markov decision processes
- multi agent systems
- partially observable
- multiple agents
- inverse kinematics
- reinforcement learning agents
- machine learning
- optimal control
- optimal policy
- dynamic programming
- potential field
- manipulation tasks
- viewpoint
- high dimensional
- kinematic model
- climbing robot