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We introduce a new approach to tackle the mobile manipulator task sequencingproblem. We leverage computational geometry, graph theory and combinatorialoptimization to yield a principled method to segment the task-space targetsinto clusters, analytically determine reachable base pose for each cluster, andfind task sequences that minimize the number of base movements and robotexecution time. By clustering targets first and by doing so from firstprinciples, our solution is more general and computationally efficient whencompared to existing methods.

MoboTSP: Solving the Task Sequencing Problem for Mobile Manipulators