DockAnywhere lifts single demonstrations to diverse docking points via structure-preserving augmentation and point-cloud spatial editing to improve viewpoint generalization in visuomotor policies for mobile manipulation.
A holistic approach to reactive mobile manipulation
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.RO 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
FastGrasp uses two-stage RL with CVAE for diverse grasp candidates from point clouds and tactile sensing for impact adjustments to achieve robust fast whole-body grasping in sim and real-world settings.
A coordinated path optimization model and isolated control scheme for tracked rescue robots improves end-effector stability and task success rates over prior methods.
citing papers explorer
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DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation
DockAnywhere lifts single demonstrations to diverse docking points via structure-preserving augmentation and point-cloud spatial editing to improve viewpoint generalization in visuomotor policies for mobile manipulation.
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FastGrasp: Learning-based Whole-body Control method for Fast Dexterous Grasping with Mobile Manipulators
FastGrasp uses two-stage RL with CVAE for diverse grasp candidates from point clouds and tactile sensing for impact adjustments to achieve robust fast whole-body grasping in sim and real-world settings.
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EMMa: End-Effector Stability-Oriented Mobile Manipulation for Tracked Rescue Robots
A coordinated path optimization model and isolated control scheme for tracked rescue robots improves end-effector stability and task success rates over prior methods.