arXiv:2607.05396v1 Announce Type: cross Abstract: Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on actual scenarios. Existing view-robust Vision-Language-Action (VLA) policies tolerate such camera variations only when the camera extrinsics are explicitly provided, making them fragile and hard to use especially when view robustness is critical. We argue that the policy should not be told where the camera is, but rather figure it out by itself. To this end, we introduce Camera-Centric VLA (CamVLA
The proliferation of robotic systems in diverse, unstructured environments necessitates more adaptable perception, driving research into calibration-free solutions for enhanced robustness.
This development addresses a significant practical hurdle in real-world robot deployment, making advanced robotic systems more reliable and easier to integrate into dynamic settings without constant manual recalibration.
Robotic systems can now theoretically operate more autonomously and robustly in environments where camera positions are neither fixed nor precisely known, lessening reliance on explicit extrinsic calibration.
- · Robotics manufacturers
- · Logistics and industrial automation
- · Field robotics operators
- · High-precision calibration service providers
- · Systems heavily reliant on fixed camera infrastructure
Robots will require less setup and maintenance time, increasing their operational uptime and reducing costs.
This improved robustness could accelerate the deployment of robots in unpredictable outdoor, humanitarian, or military contexts.
Reduced technical barriers might democratize robotics further, fostering innovation in smaller enterprises and diverse applications.
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Read at arXiv cs.AI