Simulated annealing based algorithm for smooth robot path planning with different kinematic constraints

Abstract

In this paper, we present a simulated annealing (SA) based algorithm for robot path planning. The kernel of our SA engine is based on Voronoi diagram and composite Bezier curve to obtain the shortest smooth path under given kinematic constraints. In our algorithm, a Voronoi diagram is constructed according to the global environment. The piecewise linear path in the Voronoi diagram which keeps away from the obstacles is obtained by performing Dijkstra's shortest path algorithm. The control points on the reference path are used to create the control variables for our SA engine. Our SA engine then updates the control variables to obtain the shortest composite Bezier curve path while satisfying given kinematic constraints. Experimental results on two maps containing sharp turns demonstrate the effectiveness of the proposed SA-based smooth path planning algorithm.

Collision-free curvature-bounded smooth path planning using composite Bezier curve based on Voronoi diagram

“…Our next topic will focus on the control point refinement to obtain even shorter path length satisfying different kinematic constraints. In [8], we adopt simulated annealing algorithm for this issue and obtain good results.…”

Fenceless obstacle avoidance method for efficient and safe human–robot collaboration in a shared work space

“…Deals with highly nonlinear models, chaotic and noisy data, and many constraints and can generate smooth path. 43 Very slow when cost function is expensive, cannot tell whether it has found an optimal solution. 44 Neural networks Suitable for artificial intelligence, can be trained to solve nonlinear static and dynamic without knowledge of environment structure.…”

Metaheuristic global path planning algorithm for mobile robots

“…The SA method has found its vast utilization in many practical applications. Ho and Liu (2010) presented a research study that created the path of the robot by using a Voronoi diagram. This information was then fed to the Dijkstra algorithm to obtain an obstacle-free route and then this data were used to compute the best path by implementing the SA algorithm, thus satisfying kinematic constraints.…”