Alapfogalmak
CoPa leverages common sense knowledge in foundation models for robotic manipulation, enabling fine-grained physical understanding and seamless integration with high-level planning methods.
Kivonat
The content introduces CoPa, a framework for robotic manipulation using spatial constraints and foundation models. It discusses the importance of common sense knowledge in low-level control, the challenges faced by existing methods, and the proposed solution. CoPa decomposes manipulation into task-oriented grasping and task-aware motion planning phases. The framework is evaluated through real-world experiments, showcasing its success in completing everyday tasks. Additionally, an ablation study highlights the significance of foundation models, coarse-to-fine grounding, and constraint generation. Integration with high-level planning methods is demonstrated for complex tasks.
Initial Observation:
- Introduction to CoPa framework for robotic manipulation.
- Importance of common sense knowledge in low-level control.
Task-Oriented Grasping:
- Utilizes vision-language models for object grasping.
- Process involves grasp pose proposals and filtering based on task relevance.
Task-Aware Motion Planning:
- Identifies spatial constraints for post-grasp poses.
- Utilizes VLMs to generate constraints and a solver for pose calculation.
Experiments:
- Real-world setup with Panda robot and cameras.
- Evaluation of CoPa's success rate in various manipulation tasks.
Ablation Study:
- Importance of foundation models, coarse-to-fine grounding, and constraint generation.
- Impact on performance when these components are removed.
Integration with High-Level Planning:
- Combination with VILA for long-horizon tasks like making pour-over coffee.
Statisztikák
"Boasting a fine-grained physical understanding of scenes"
"63% success rate across ten different tasks"
"VoxPoser baseline significantly surpassed"
Idézetek
"Endow robots with fine-grained physical understanding"
"Utilizes VLMs to provide spatial geometry constraints"
"Seamlessly integrated with existing robotic planning algorithms"