Graph-Sparse Distributed Predictive Control for Multi-Robot Motion Planning via Edge-Consensus ADMM
Graph-Sparse Distributed Predictive Control for Multi-Robot Motion Planning vianEdge-Consensus ADMM
This paper presents a distributed model predictive control (MPC) architecture for collision-avoiding motion planning of planar robots with double-integrator dynamics.
Source: arXiv Robotics — research abstracts · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
- Environment
- SimulationOpen source S4
Reported numbers
Robot count
32 robots
View original evidence
distributed candidate does not satisfy the direct-execution conditions. Evaluated in C++ simulations involving 8, 16, and 32 robots, the proposed architecture achieves collision-free execution and substantially improves computational scalability while maintaining task-level performance comparable to a centralized complete-graph baseline.
Open source S4
- paper: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
distributed candidate does not satisfy the direct-execution conditions. Evaluated in C++ simulations involving 8, 16, and 32 robots, the proposed architecture achieves collision-free execution and substantially improves computational scalability while maintaining task-level performance comparable to a centralized complete-graph baseline.
Open source S4
Source：arXiv Robotics — research abstracts · arxiv.org