Differentiable Constrained Imitation Learning for Robot Motion Planning and Control. (arXiv:2210.11796v1 [cs.RO])

Motion planning and control are crucial components of robotics applications.
Here, spatio-temporal hard constraints like system dynamics and safety
boundaries (e.g., obstacles in automated driving) restrict the robot's motions.
Direct methods from optimal control solve a constrained optimization problem.
However, in many applications finding a proper cost function is inherently
difficult because of the weighting of partially conflicting objectives. On the
other hand, Imitation Learning (IL) methods such as Behavior Cloning (BC)
provide a intuitive framework for learning decision-making from …

arxiv imitation learning motion planning planning robot