TY - CHAP

T1 - Feasible Joint Angle Continuous Function of Robotics Arm in Obstacles Environment Using Particle Swarm Optimization

AU - Machmudah, Affiani

AU - Parman, Setyamartana

PY - 2013

Y1 - 2013

N2 - This paper addresses a point-to-point robotic arm path planning in complex obstacle environments. To guarantee a smoothness of a motion during a manipulation, a continuous function of a sixth degree polynomial is utilized as a joint angle path. The feasible sixth degree joint angle path will be searched utilizing a Particle Swarm Optimization (PSO). There is no information regarding the region of this feasible joint angle so that the PSO should search it first. At the first computation where the population is generated randomly, all particles commonly collide with obstacles. The searching computation will be continued till at certain iteration for which the feasible particle is met. Then, the PSO should evolve this particle to find the best one with the highest fitness value. It is very hard computation since it involves a requirement to escape from zero fitness. The most difficult computation in this case is in finding at least one particle that lies in the feasible zone. In this paper, the PSO has shown its good performance in finding the feasible motion of the sixth degree polynomial joint angle path by utilizing just the information of a forward kinematics. To simulate the proposed path planning, 3-Degree of Freedom (DOF) planar robot will be utilized.

AB - This paper addresses a point-to-point robotic arm path planning in complex obstacle environments. To guarantee a smoothness of a motion during a manipulation, a continuous function of a sixth degree polynomial is utilized as a joint angle path. The feasible sixth degree joint angle path will be searched utilizing a Particle Swarm Optimization (PSO). There is no information regarding the region of this feasible joint angle so that the PSO should search it first. At the first computation where the population is generated randomly, all particles commonly collide with obstacles. The searching computation will be continued till at certain iteration for which the feasible particle is met. Then, the PSO should evolve this particle to find the best one with the highest fitness value. It is very hard computation since it involves a requirement to escape from zero fitness. The most difficult computation in this case is in finding at least one particle that lies in the feasible zone. In this paper, the PSO has shown its good performance in finding the feasible motion of the sixth degree polynomial joint angle path by utilizing just the information of a forward kinematics. To simulate the proposed path planning, 3-Degree of Freedom (DOF) planar robot will be utilized.

UR - http://www.scopus.com/inward/record.url?scp=84885446092&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-30504-7_41

DO - 10.1007/978-3-642-30504-7_41

M3 - Chapter

AN - SCOPUS:84885446092

SN - 9783642305030

T3 - Intelligent Systems Reference Library

SP - 1047

EP - 1071

BT - Handbook of Optimization

A2 - Zelinka, Ivan

A2 - Snasel, Vaclav

A2 - Abraham, Ajith

ER -