WRAP: Fixtureless Wrench-aware Multi-Robot Assembly Planning

2026-09-24

AI Summary

This study addresses the challenges in multi-robot assembly, which heavily relies on dedicated fixtures and involves difficult planning under contact force constraints. To overcome these limitations, this work proposes a fixtureless multi-robot assembly planning framework. Specifically, it infers supporting forces via linear programming to ensure stable contacts, and employs heuristic search to optimize both assembly sequences and motion trajectories. Furthermore, by integrating force-aware planning with multi-objective cooperative control, the framework effectively decomposes contact-rich manipulation skills. The proposed approach enables flexible, fixtureless assembly and has been validated across robot systems of varying scales in both simulated and real-world environments. The source code has been made publicly available to facilitate future research.

Abstract

Assembly using robots often requires specially designed fixtures, or relies on top-down only assembly strategies. Using multiple robots, we can avoid using fixtures and make robotic assembly more flexible. Planning assembly sequences for multiple robots is challenging due to the high number of possible task assignments and orders. In addition, we need to reason over forces that occur during the assembly process, e.g., to decide if multiple robots are required for support, or if external support such as a table should be used. We present Wrap, a multi-robot assembly planner for multi-part assemblies, given the inter-part ordering-dependencies, the part meshes, and their initial state. We formulate a linear program to reason about valid grasps for supporting the forces that occur during assembly. The search leverages the assembly sequence, and greedily finds a feasible solution per assembly step by computing a heuristic via a cheap backwards search, and using the heuristic in the more expensive forward search. We then solve the multi-robot, multi-goal motion planning problem, and for execution, we split the plan into contact-rich assembly skills, and free space motion. We benchmark the planner on a variety of multi-part assemblies, and apply the planner to groups of robots differing in size and kinematics. We validate the work both in a physics simulation, and in real. Videos and code are available at https://www.vhartmann.com/wrap.

Problem

• fixtureless assembly
• multi-robot planning
• assembly sequence planning
• wrench-aware reasoning
• motion planning

Innovation

• Fixtureless Assembly
• Multi-Robot Planning
• Wrench-aware Reasoning
• Linear Programming
• Motion Planning