Planning for Large-Scale Multi-Robot Systems

Speaker:  Sven Koenig – Los Angeles, CA, United States
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Abstract

Multi-robot systems are now being used in industry. For example, hundreds of robots navigate autonomously in Amazon fulfillment centers to move inventory pods all the way from their storage locations to the inventory stations that need the products they store (and vice versa). Autonomous aircraft towing vehicles will soon tow aircraft all the way from the runways to their gates (and vice versa), thereby reducing pollution, energy consumption, congestion, and human workload. Path planning for these robots is difficult, yet one must find high-quality collision-free paths for them in real-time. Shorter paths result in higher throughput or lower operating costs (since fewer robots are required). I will discuss different versions of such multi-robot path-planning problems, algorithms for solving them, and their applications. I will also discuss a planning architecture that combines ideas from artificial intelligence and robotics. It makes use of a simple temporal network to post-process the output of a multi-robot path-planning algorithm in polynomial time to create a plan-execution schedule for robots that provides a guaranteed safety distance between them and exploits slack to absorb imperfect plan executions and avoid time-intensive re-planning in many cases. This talk is suitable for audiences with some computer science background. A background in artificial intelligence or robotics is not necessary.

About this Lecture

Number of Slides:  60
Duration:  50 minutes
Languages Available:  English
Last Updated: 

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