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LLM-State: Open World State Representation for Long-horizon Task Planning with Large Language Model
We propose an open state representation that provides continuous expansion and updating of object attributes from the LLM's inherent capabilities for context understanding and historical action reasoning.
Autonomous Navigation for Quadrupedal Robots with Optimized Jumping through Constrained Obstacles
The resulted jumping mode is utilized in an autonomous navigation pipeline that leverages a search-based global planner and a local planner to enable the robot to reach the goal location by walking.
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