The invention discloses an
industrial robot grabbing
obstacle avoidance path
planning method based on an RRT-TAGB
algorithm, and belongs to the field of mechanical
assembly. Firstly, a self-adaptive target bias sampling strategy is provided for the problem that a traditional RRT
algorithm is large in search randomness, the target sampling probability is determined through the volume relation between an obstacle and a grabbing
work space, a
random tree is made to be expanded to a target point more quickly, and the guidance quality of the
algorithm in the search process is improved; secondly, in order to effectively solve the problem that path planning fails due to the fact that
local optimum is prone to occurring in the dense obstacle environment, an artificial
potential field method is used for conducting local path planning, and the positions of nodes are adjusted again to obtain an optimized path; then, aiming at the problem that invalid nodes on the path are too many, a greedy strategy is adopted to remove redundant nodes of the path, and the length of the path is reduced; and finally, aiming at the problem of poor path quality, performing
smoothing operation on the path by using a cubic B-spline curve, and removing unnecessary corners so as to improve the quality of the path. According to the RRT-TAGB algorithm adopted by the invention, the guidance quality of
random tree growth is improved, redundant nodes on a path are greatly reduced, the search time is shortened, the final path is smoother, the overall
obstacle avoidance path quality is higher, and the
adaptive capacity of grabbing and
obstacle avoidance of the
industrial robot in a complex environment is ensured.