Language-guided Robust Navigation for Mobile Robots in Dynamically-changing Environments

• URL: http://arxiv.org/abs/2409.19459v1
• Date: Sat, 28 Sep 2024 21:30:23 GMT
• Title: Language-guided Robust Navigation for Mobile Robots in Dynamically-changing Environments
• Authors: Cody Simons, Zhichao Liu, Brandon Marcus, Amit K. Roy-Chowdhury, Konstantinos Karydis,
• Abstract summary: We develop an embodied AI system for human-in-the-loop navigation with a wheeled mobile robot. We propose a method of monitoring the robot's current plan to detect changes in the environment that impact the intended trajectory of the robot. This work can support applications like precision agriculture and construction, where persistent monitoring of the environment provides a human with information about the environment state.
• Score: 26.209402619114353
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we develop an embodied AI system for human-in-the-loop navigation with a wheeled mobile robot. We propose a direct yet effective method of monitoring the robot's current plan to detect changes in the environment that impact the intended trajectory of the robot significantly and then query a human for feedback. We also develop a means to parse human feedback expressed in natural language into local navigation waypoints and integrate it into a global planning system, by leveraging a map of semantic features and an aligned obstacle map. Extensive testing in simulation and physical hardware experiments with a resource-constrained wheeled robot tasked to navigate in a real-world environment validate the efficacy and robustness of our method. This work can support applications like precision agriculture and construction, where persistent monitoring of the environment provides a human with information about the environment state.

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