Any-ttach shows that rapid end-effector swapping combined with demonstration collection and task planning enables reliable multi-tool skills in long-horizon tasks such as sandwich making.
arXiv preprint arXiv:2310.13065 , year=
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UNVERDICTED 4representative citing papers
RoboWits benchmark with 238 tasks shows pre-trained VLAs succeed on seed tasks but fail on mutated ones, highlighting brittleness in reasoning.
ChemBot adds dual-layer memory and future-state asynchronous inference to VLA models, enabling better long-horizon success in chemical lab automation on collaborative robots.
The paper defines Agent AI as interactive multimodal systems that perceive grounded data and generate embodied actions, arguing this approach can mitigate hallucinations in foundation models.
citing papers explorer
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Any-ttach: Quick End-effector Swapping Enables Manipulation Dexterity with Simplicity
Any-ttach shows that rapid end-effector swapping combined with demonstration collection and task planning enables reliable multi-tool skills in long-horizon tasks such as sandwich making.
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RoboWits: Unexpected Challenges for Robotic Creative Problem Solving
RoboWits benchmark with 238 tasks shows pre-trained VLAs succeed on seed tasks but fail on mutated ones, highlighting brittleness in reasoning.
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Long-Term Memory for VLA-based Agents in Open-World Task Execution
ChemBot adds dual-layer memory and future-state asynchronous inference to VLA models, enabling better long-horizon success in chemical lab automation on collaborative robots.
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Agent AI: Surveying the Horizons of Multimodal Interaction
The paper defines Agent AI as interactive multimodal systems that perceive grounded data and generate embodied actions, arguing this approach can mitigate hallucinations in foundation models.