Path Tracking for Car-like Robots Based on Neural Networks with NMPC as Learning Samples

Path Planning with Uncertainty for Car-Like Robots

| this paper presents the rst path planner taking into account both non-holonomic and uncertainty constraints. The case of a car-like robot subject to cumulative and unbounded connguration uncertainty related to bounded control and sensing errors is considered. Assuming the existence of landmarks allowing the robot to relocalize itself in particular places, we present an algorithm that computes...

A Geometric Path Planner for Car-like Robots

This technical brief presents a refined slabbing method, originally used for free-flying robots, for finding efficient paths for nonholonomic robots. Our method takes kinematic constraints and reversal maneuvers into account. We create orientation levels for each orientation configuration of the robot. The slopes of slabbing lines in each orientation level match the orientation of a robot in th...

Path Planning and Robust Tracking for A Car-Like Robot

In this paper the problem of path planning and path following for a car-like robot is considered. Some new algorithms are proposed, which, by experiments, have been proven to be quite robust.

Path-Tracking Control of Non-holonomic Car-Like Robot with Reinforcement Learning

Path-Tracking Control of a Non-Holonomic Car-Like Robot with Reinforcement Learning

The problem investigated in this paper is that of driving a car-like robot along a race track and the use of reinforcement learning to find a good control function. The reinforcement learner uses a case-based function approximator to extend the reinforcement learning paradigm to handle continuous states. The learned controller performs similar to the best control functions in both simulation an...