MoboTSP: Solving the Task Sequencing Problem for Mobile Manipulators
This work addresses task sequencing for mobile manipulators, which is an incremental improvement in robotics optimization.
The paper tackles the mobile manipulator task sequencing problem by developing a principled method that clusters task-space targets and determines reachable base poses to minimize base movements and execution time, resulting in improved generality and computational efficiency compared to existing methods.
We introduce a new approach to tackle the mobile manipulator task sequencing problem. We leverage computational geometry, graph theory and combinatorial optimization to yield a principled method to segment the task-space targets into clusters, analytically determine reachable base pose for each cluster, and find task sequences that minimize the number of base movements and robot execution time. By clustering targets first and by doing so from first principles, our solution is more general and computationally efficient when compared to existing methods.