Mobile manipulator base placement optimization using an ellipsoidal reachability model

The mobile manipulator's base positioning is strategic to optimize the execution of different tasks within a specific workspace. Base placements provided by the human intuition yield suboptimal results, and existing methods are usually based on computationally expensive maps built to represent the distribution of the manipulator's dexterity or the base positions effective for reaching a specific target, but not both simultaneously. This paper proposes a novel optimization-based method for mobile manipulator's base placement, focused on a compact mathematical model of the manipulator reachability space. By representing it through two concentric ellipsoid equations, such a model enables efficient evaluation of end effector reachability while guiding the base placement. This model is exploited in the optimization problem to autonomously reposition the mobile base, ensuring pose reachability with high dexterity and minimizing collision risk. The approach is validated experimentally using a mobile manipulator in a real-world laboratory and assigning target poses with varying difficulty levels. The results demonstrate the effectiveness of the obtained base poses and the adaptability of the method to different scenarios.