POLAR organizes prior interactions into a multimodal knowledge graph with semantic and episodic memory to improve personalized embodied task execution across multiple MLLM backbones.
Robi butler: Remote multimodal interactions with household robot assistant
4 Pith papers cite this work. Polarity classification is still indexing.
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A hierarchical VLA architecture lets robots follow complex instructions and situated feedback by separating high-level reasoning from low-level control.
A visibility-aware mobile grasping system with iterative whole-body planning and behavior-tree subgoal generation achieves 68.8% success in unknown static and 58% in dynamic environments, outperforming a baseline by 22.8% and 18%.
The paper proposes a bidirectional continuum between LLMs and control systems, covering LLM-assisted controller design, control-based LLM steering, and state-space modeling of LLMs.
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Visibility-Aware Mobile Grasping in Dynamic Environments
A visibility-aware mobile grasping system with iterative whole-body planning and behavior-tree subgoal generation achieves 68.8% success in unknown static and 58% in dynamic environments, outperforming a baseline by 22.8% and 18%.