Time-Optimal TCP and Robot Base Placement for Pick-and-Place Tasks in Highly Constrained Environments

This work proposes a highly parallelized optimization scheme to simultaneously optimize the robot base and tool center point (TCP) placement within a robotic work cell for a sequence of pick-and-place tasks. The placement is optimized for minimum cycle time by considering the scenario holistically, including point-to-point trajectory planning while respecting the kinodynamic constraints of the robot, collision avoidance in highly constrained environments, redundancy in grasp configurations and inverse kinematic solutions, and the cyclic constraint of the process. The proposed algorithm is applied to optimize the robot base and TCP placements in a spatially constrained packaging scenario, demonstrating a cycle time reduction of 41% compared to state-of-the-art approaches. The results are validated experimentally using a KUKA LBR iiwa with 7 degrees of freedom, where the TCP placement is realized using topology optimization and 3D printing.