Automotive assembly cells are cluttered environments, including robots, workpieces, and fixtures. Due to high volumes and several product variants assembled in the same cell, robot placement is crucial to increase flexibility and throughput. In this paper, we propose a novel method to optimize the base position of an industrial robot with the objective to reach all predefined tasks and minimize cycle time: robot inverse kinematics and collision avoidance are integrated together with a derivative-free optimization algorithm. This approach is successfully used to find feasible solutions on industrial test cases, showing up to 20% cycle time improvement.
