Motion Planning For A Planar 4R Robot Based On C-space And APF

Redundant manipulators are widely used to replace manpower in such fields as oceanic engineering, fire protection, construction and so on. Especially in some special fields like deep-ocean exploration, waste and pollution disposal, road and bridge detection which it is difficult for man to work in, these mechanical arms are designed not only with facile structures but also necessarily with some characteristics named AI (artificial intelligence) so that they could detect and avoid obstacles and safely fulfill the preconcerted working task by itself, well serving people to meet the need of reliving the burden and exploring the world.Path planning of redundant manipulators is one of important topics in robotics. The research has been studied extensively thus far with two essential sorts. One is global planning approach, and the other is local planning approach. Global planning approach primarily includes geometric method and topological method based on configuration space while the local one chiefly involves artificial potential field method based on Cartesian space. Global planning approach considers all the condition, but it need big computation, large store space and much time. The Artificial potential field is a common local path planning method for the mobile robot. It has the advantages of rapid respondence, small computation and real- time property. The robot may stop moving and can't reach the goal for the problem of local minima.For collision-free motion planning of a planar 4R robot, this paper proposes an approach, which combines global planning approach and local planning approach. Firstly, the four-bar mechanism was looked as composing of two open-chain two-bar mechanisms. Two-bank-bar arrives a middle point by C-space approach, at the same time, two-front-bar approaches goal point without collision by APF approach. Finally, two-front-bar arrives goal point by C-space approach. The approach is not an absolute global approach. It gets the strongpoint of global planning approach and local planning approach. The approach considers all the conditions, and it can resolve the problem of local minima in APF and improve the robustness of APF.