Sharing Cognition: Human Gesture and Natural Language Grounding Based Planning and Navigation for Indoor Robots
Gourav Kumar, Soumyadip Maity, Ruddra dev Roychoudhury, Brojeshwar, Bhowmick

TL;DR
This paper presents a novel system that combines human gesture recognition with language grounding to enable indoor robots to navigate and interact naturally with humans, enhancing cooperation and cognition sharing.
Contribution
It introduces the first pipeline integrating human gestures with language grounding for autonomous indoor navigation in robots.
Findings
Effective gesture-based communication improves navigation accuracy.
The system outperforms traditional vision-only approaches in complex environments.
Real-world experiments demonstrate practical applicability and robustness.
Abstract
Cooperation among humans makes it easy to execute tasks and navigate seamlessly even in unknown scenarios. With our individual knowledge and collective cognition skills, we can reason about and perform well in unforeseen situations and environments. To achieve a similar potential for a robot navigating among humans and interacting with them, it is crucial for it to acquire the ability for easy, efficient and natural ways of communication and cognition sharing with humans. In this work, we aim to exploit human gestures which is known to be the most prominent modality of communication after the speech. We demonstrate how the incorporation of gestures for communicating spatial understanding can be achieved in a very simple yet effective way using a robot having the vision and listening capability. This shows a big advantage over using only Vision and Language-based Navigation, Language…
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Taxonomy
TopicsMultimodal Machine Learning Applications · Speech and dialogue systems · Robotics and Automated Systems
