Collision avoidance techniques tend to derive the robot away of the obstacles in minimal total travel distance. Most ofthe collision avoidance algorithms have trouble get stuck in a local minimum. A new technique is to avoid local minimum in convexoptimization-based path planning. Obstacle avoidance problem is considered as a convex optimization problem under system state andcontrol constraints. The idea is by considering the obstacles as a convex set of points which represents the obstacle that encloses inminimum volume ellipsoid, also the addition of the necessary offset distance and the modified motion path is presented. In the analysis,the results demonstrated the effectiveness of the suggested motion planning by using the convex optimization technique.
ROBOTIC MOTION PLANNING USING CONVEX OPTIMIZATION METHODS
