This article is cited in 1 paper

Part 6. Intelligent control, robots and biomechatronics systems

Path planning of an autonomous robot in a maze with obstacles

E. I. Zalilov, A. S. Dolgiy, A. V. Shokurov

Mechanics and Mathematics Faculty of Lomonosov Moscow State University

Abstract: We solve the problem of autonomous robot path planning by applying and comparing classical approach and approach using machine learning algorithms. The task was set to "move from point A to point B" on various experimental maps representing a maze with obstacles. We studied the behavior of a two-wheeled robot with different methods of building routes and different sets of sensors. It is assumed that the machine learning approach is easier to develop and requires fewer sensors, so this significantly reduces the cost of such a robot.

Keywords: path planning, robotics, motion primitives, reinforcement learning.