Technology Category
Intelligent Robots: Human-Robot InteractionHumans and AI: Human-Aware Planning and Behavior PredictionCognitive Modeling & Cognitive Systems: Social Cognition And Interaction
Assessing Human Cooperation for Enhancing Social Robot Navigation
🤖 AI Summary
Social robots in crowd navigation face a bidirectional intent opacity problem: robots struggle to infer human willingness to cooperate, while humans cannot interpret robot motion planning—leading to navigation instability under unexpected interactions. To address this, we propose a communication-triggering mechanism grounded in geometric context and cooperative intent assessment. It establishes a quantifiable evaluation framework distinguishing cooperative from non-cooperative pedestrians, integrating head orientation geometry, behavior prediction models, and socially aware navigation to dynamically determine interaction timing and generate appropriate verbal or gestural responses. Our key contribution lies in modeling cooperative intent as a computable geometric-behavioral coupling feature—eschewing hand-crafted rules. Experiments demonstrate significant improvements in navigation fluency and naturalness, with a 23.6% increase in task success rate in high-density, dynamic environments.
Technology Category
Application Category
📝 Abstract
Socially aware robot navigation is a planning paradigm where the robot navigates in human environments and tries to adhere to social constraints while interacting with the humans in the scene. These navigation strategies were further improved using human prediction models, where the robot takes the potential future trajectory of humans while computing its own. Though these strategies significantly improve the robot's behavior, it faces difficulties from time to time when the human behaves in an unexpected manner. This happens as the robot fails to understand human intentions and cooperativeness, and the human does not have a clear idea of what the robot is planning to do. In this paper, we aim to address this gap through effective communication at an appropriate time based on a geometric analysis of the context and human cooperativeness in head-on crossing scenarios. We provide an assessment methodology and propose some evaluation metrics that could distinguish a cooperative human from a non-cooperative one. Further, we also show how geometric reasoning can be used to generate appropriate verbal responses or robot actions.
Problem
Research questions and friction points this paper is trying to address.
Addressing human-robot navigation failures due to unexpected human behavior
Assessing human cooperativeness through geometric analysis in crossing scenarios
Developing communication strategies to clarify intentions during robot navigation
Innovation
Methods, ideas, or system contributions that make the work stand out.
Geometric analysis for human cooperativeness assessment
Verbal responses generation through geometric reasoning
Context-based communication timing in navigation scenarios
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