Fast, High-Quality Dual-Arm Rearrangement in Synchronous, Monotone Tabletop Setups
This work addresses efficiency challenges in robotic applications like product packaging, though it is incremental as it builds on existing rearrangement methods.
The paper tackles the problem of efficiently rearranging objects on a tabletop using two robotic arms, developing an optimal model and scalable algorithm that minimizes transfer and move costs, with experiments showing fast computation of near-optimal solutions.
Rearranging objects on a planar surface arises in a variety of robotic applications, such as product packaging. Using two arms can improve efficiency but introduces new computational challenges. This paper studies the structure of dual-arm rearrangement for synchronous, monotone tabletop setups and develops an optimal mixed integer model. It then describes an efficient and scalable algorithm, which first minimizes the cost of object transfers and then of moves between objects. This is motivated by the fact that, asymptotically, object transfers dominate the cost of solutions. Moreover, a lazy strategy minimizes the number of motion planning calls and results in significant speedups. Theoretical arguments support the benefits of using two arms and indicate that synchronous execution, in which the two arms perform together either transfers or moves, introduces only a small overhead. Experiments support these points and show that the scalable method can quickly compute solutions close to the optimal for the considered setup.