arXiv AI
Jul 14
A Glimpse into Long-term Physical Coexistence with Intelligent Robots
arXiv:2607. 11377v1 Announce Type: cross Abstract: Long-term physical coexistence with intelligent robots requires more than capable robot policies.
A Glimpse into Long-term Physical Coexistence with Intelligent Robots
Long-term physical coexistence with intelligent robots requires more than capable robot policies. A persistent robotic assistant must support diverse user-facing interfaces, maintain long-horizon memory of people and preferences, coordinate across robot embodiments, and translate human intent into safe physical execution.
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arXiv AI
Jul 14
ABot-AgentOS: A General Robotic Agent OS with Lifelong Multi-modal Memory
arXiv:2607. 10350v1 Announce Type: new Abstract: Recent VLM and VLA systems have improved robotic perception and action prediction, yet long-horizon embodied agents still require a general runtime layer for reasoning, memory, tool use, verification, and cross-embodiment execution.
Hugging Face Trending Papers
Jun 25
Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy
Building persistent embodied agents in unstructured environments demands unified orchestration of heterogeneous tools spanning both cyber (APIs, IoT) and physical (manipulation, navigation) domains, coupled with autonomous recovery from physical failures that inevitably arise over extended operation. Existing systems treat these as separate problems: VLM-based planners lack a unified cyber-physical action space, agent frameworks accumulate unbounded context that degrades temporal coherence, and VLA policies execute open-loop without detecting their own failures.
arXiv AI
Jun 26
Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy
arXiv:2606. 27251v1 Announce Type: cross Abstract: Building persistent embodied agents in unstructured environments demands unified orchestration of heterogeneous tools spanning both cyber (APIs, IoT) and physical (manipulation, navigation) domains, coupled with autonomous recovery from physical failures that inevitably arise over extended operation.
arXiv AI
Jul 24
Vision-Language-Policy Model for Dynamic Robot Task Planning
arXiv:2512. 19178v2 Announce Type: replace-cross Abstract: Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotics.
arXiv AI
Aug 11
REMAC: Self-Reflective and Self-Evolving Multi-Agent Collaboration for Long-Horizon Robot Manipulation
arXiv:2503. 22122v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have demonstrated remarkable capabilities in robotic planning, particularly for long-horizon tasks that require a holistic understanding of the environment for task decomposition.
arXiv Machine Learning
Jul 7
ACE: Agentic Control for Embodied Manipulation via Zero-shot Workflow Reasoning
arXiv:2607. 04162v1 Announce Type: cross Abstract: Open-ended tabletop manipulation requires agents to not only understand natural language but also adapt to dynamic environments and execution failures.
arXiv AI
Jul 28
A Few Words Go a Long Way: Language Guided Robot Policy Synthesis
arXiv:2607. 23784v1 Announce Type: cross Abstract: While vision-language-action models have demonstrated impressive zero-shot manipulation capabilities, they remain fundamentally black box policies that are difficult to interpret, adapt, or correct when they inevitably fail.
arXiv AI
Jun 2
Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments
arXiv:2605. 30280v2 Announce Type: replace-cross Abstract: Embodied intelligence is often studied through specialized models for individual tasks such as manipulation or navigation, resulting in fragmented capabilities and limited generalization across tasks, environments, and robot embodiments.
arXiv AI
Jun 17
Extracting Semantics: LLM-Guided Automatic Population of Robot Ontology from URDF
arXiv:2606. 17073v1 Announce Type: cross Abstract: While commonsense knowledge may suffice for virtual agents, embodied robots interacting with humans require grounded and semantically rich representations of both their environment and their own physical embodiment.
arXiv AI
1d ago
MistyPilot: Enabling Social-Robot Control through Multi-Agent LLM Skill Orchestration
arXiv:2608. 15549v1 Announce Type: cross Abstract: Programming small social robots from natural-language instructions requires more than invoking isolated APIs.
arXiv Machine Learning
Jul 16
HRIBench: Benchmarking Interaction-Centric Human-Robot Collaboration
arXiv:2607. 13056v1 Announce Type: cross Abstract: Current vision-language-action (VLA) benchmarks primarily evaluate isolated manipulation skills while leaving human-robot interaction structure largely unmodeled.