Crowd navigation in a multi-room environment: a model predictive control framework for mobile robots
Mobile robots operating in human-populated environments must navigate complex, multi-room spaces while ensuring safety, i.e., generating collision-free motion. In this study, we present a sensor-based model predictive control (MPC) scheme designed for safe crowd navigation in such non-convex environments. The proposed framework decomposes the free space into a set of overlapping convex regions to construct a topological graph, enabling a high-level planner to compute optimal sequences of travers
Record details
Published: 27 July 2026
Source: Frontiers in Robotics and AI
Category: Research
Topics: Agents & autonomy · Environment
Retrieved: 27 July 2026
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How to cite this record
ethics.ai (27 July 2026), “Crowd navigation in a multi-room environment: a model predictive control framework for mobile robots,” evidence record 13642, https://ethics.ai/record/13642 (originally published by Frontiers in Robotics and AI).
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