Rl-rrt: kinodynamic motion planning via learning reachability estimators from rl policies

HIGHLIGHTS

• who: RL-RRT Kinodynamic Motion Planning and colleagues from the (UNIVERSITY) have published the Article: RL-RRT: Kinodynamic Motion Planning via Learning Reachability Estimators From RL Policies, in the Journal: (JOURNAL)
• what: Through the combination of sampling-based a Rapidly Exploring Randomized Tree (RRT) and an efficient planner through machine learning the authors propose an efficient solution to long-range for First the authors use deep reinforcement learning to learn an obstacle-avoiding policy that maps a robot's sensor observations to actions which is used as a local planner during and as a controller . . .
  

   

  

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