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Advancements in WSU Robotics: Enhancing Efficiency with Innovative Strategies

Washington State University is making strides in robotics by exploring how to optimize robots for a variety of tasks. This project focuses on re-using sub-MDPs (Markov Decision Processes) to save time and improve the efficacy of robotic actions. Researchers investigate important questions such as knowing when to reuse strategies, handling excess options, and employing both spatial and temporal abstractions. They also delve into sensor types, motion modeling, localization, and map-building, aiming to enhance SLAM (Simultaneous Localization and Mapping) through reinforcement learning methods.

marny-mccoy
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Advancements in WSU Robotics: Enhancing Efficiency with Innovative Strategies

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  1. http://www.klewtv.com/news/local/WSU-robots-253558541.html?tab=video&c=yhttp://www.klewtv.com/news/local/WSU-robots-253558541.html?tab=video&c=y Final Project Proposals Exercise 4

  2. Sub-MDPs re-usable in new tasks • Can save time • Know when to re-use? • What if you have too many? • SMDP • Options: policy termination, init. set • Can use very similarly to “normal” actions • Can learn to optimize • Can learn • Temporal vs. spatial abstractions • Irrelevant state variables

  3. Types of Sensors • Grid vs. Feature Map • What are Maps for? • Motion model • Localization • Map building • Optimization (of SLAM) via RL

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