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Object- and Task-Aware Active Perception Framework for Mobile Manipulators in Semi-Static Environments

An arXiv paper proposes an object- and task-aware active perception framework that lets a high-degree-of-freedom mobile manipulator use its hand camera to actively inspect uncertain or safety-critical regions during navigation. The framework uses a probabilistic next-best-view (NBV) formulation and is integrated with hierarchical task model predictive control (HTMPC), exploiting kinematic redundancy to adjust viewpoints while preserving the higher priority of base-trajectory tracking. Real-world tests showed that, compared with passive or non-task-aware baselines, the system improved map consistency and reduced task-related map entropy and navigation risk.

Part of the event: Proposes an active-perception safe navigation framework for mobile manipulators

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