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Carnegie Mellon Develops LAMP to Enhance Robot Coordination in Cluttered Spaces

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ri.cmu.edu
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Researchers at Carnegie Mellon University are advancing a system called Long-Horizon Adaptive Manipulation Planning (LAMP) to improve how teams of robots collaborate in cluttered environments. This innovative approach addresses the challenges of multirobot manipulation, particularly in settings like warehouses where obstacles can hinder movement.

LAMP enables robots to plan their movements collectively, ensuring they can navigate around obstacles while efficiently transporting objects. This system integrates learned models with search-based planning, allowing robots to adapt their strategies in real-time based on environmental changes, which is crucial for maintaining stability and control during operations.

The team successfully demonstrated LAMP's capabilities by having multiple robots transport objects to form the letters “IROS” in a crowded space. This research highlights the potential for enhanced robotic coordination in complex environments, with the system set to be presented at the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems in Pittsburgh this fall.

Original report

LAMP Helps Robots Find a Way Through

ri.cmu.edu · Mallory Lindahl
Read at ri.cmu.edu

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