arXiv:2605.22082v1 Announce Type: cross Abstract: We present CoRMA(Contrastive Robotic Motor Adaptation), a context-based meta-adaptation framework that modifies RMA for force-dominant assembly. CoRMA replaces raw simulator-parameter adaptation with a compact 6D simulator-only semantic contact context describing contact onset, lateral engagement, guided transition, contact direction, and jamming. A deployable causal Transformer adapter infers this context online from force, proprioceptive, and action histories using semantic regression and a force-regime contrastive objective. At deployment, o
The proliferation of advanced robotics, especially in domains requiring fine motor skills and adaptability, necessitates more robust and adaptable control systems like CoRMA.
This development improves robotic adaptability to real-world complexities, accelerating the deployment and capability of robots in unstructured and contact-rich environments.
Robots can now more effectively interpret and adapt to physical contact during complex tasks, reducing failure rates and increasing autonomy.
- · Robotics manufacturers
- · Automation sector
- · Logistics and assembly industries
- · AI/ML researchers
- · Manual labor in precision assembly
- · Legacy robotic control systems
Improved performance and broader application of robots in manufacturing and service industries requiring physical interaction.
Reduced operational costs and increased efficiency in supply chains due to highly adaptable robotic systems.
Accelerated development of general-purpose robots capable of performing diverse and complex physical tasks in human environments.
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