Semi-constrained Path Planning for Industrial Robot with External Axis

To solve the problem that the working space of the industrial robot is limited by the arm length, and the flexibility is limited by the number of joints, the robot system with external axes is necessary. This paper proposes a novel sampling-based path planning method to control the industrial robot and external axes simultaneously. An external axis space is proposed for sampling external axis value to solve task-constrained path planning problems in practical industrial applications. The configuration space of a robot system with external axes is decoupled to extract task space independent of external axis space, based on the semi-constrained characteristic of typical Cartesian curve tracking tasks. The task space is defined by the position and orientation parameter of the robot's end-effector. As a result, a sampling space, which meets the task-constraint, can he found. Analytical Inverse Kinematics (IK) algorithm is used to map the samples back to the task-constrained configuration space without iterative modifications. Simulation studies on practical path planning tasks under constraints prove the effectiveness of the proposed method.