Abstract
Physical active vision allows robots to change their viewpoint when task-relevant observations become unreliable, yet existing manipulation benchmarks provide limited support for studying how policies recover from occlusion during execution. We introduce BAVO-Bench (Bimanual Active Vision under Occlusion), a bimanual active-vision benchmark that systematically controls external visibility through Clean, Stage Occlusion, and Random-time Occlusion conditions, enabling evaluation of both manipulation performance and active visual recovery. Building on this setting, we present A-FAR (Active Future-Aware Recovery), an active-vision policy for joint viewpoint and manipulation control. A-FAR represents moving-camera observations in a unified robot-centric 3D frame and distills relational structure together with its future evolution from a pretrained 4D model, providing the policy with future-aware geometric guidance without requiring future observations at deployment. Experiments across multiple manipulation tasks show that A-FAR improves robustness to both structured and temporally shifted occlusions while maintaining strong performance under clean observations.
Keywords
Publication details
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Cite this article
APA 7
Luo, K., Huang, Y., Zhong, Q., Song, X., Liu, Y., & Lin, L. (2026). Recovering the View: Benchmarking Physical Active Vision for Occlusion Recovery in Robotic Manipulation. https://omanscience.com/en/articles/recovering-the-view-benchmarking-physical-active-vision-for-occlusion-recovery-in-robotic-manipulation
MLA 9
Luo, Kaijun, et al. "Recovering the View: Benchmarking Physical Active Vision for Occlusion Recovery in Robotic Manipulation." https://omanscience.com/en/articles/recovering-the-view-benchmarking-physical-active-vision-for-occlusion-recovery-in-robotic-manipulation.
Chicago (author–date)
Luo, Kaijun, Yudi Huang, Qijun Zhong, Xinshuai Song, Yang Liu, and Liang Lin. 2026. "Recovering the View: Benchmarking Physical Active Vision for Occlusion Recovery in Robotic Manipulation." https://omanscience.com/en/articles/recovering-the-view-benchmarking-physical-active-vision-for-occlusion-recovery-in-robotic-manipulation.
Harvard
Luo, K., Huang, Y., Zhong, Q., Song, X., Liu, Y. and Lin, L. (2026) 'Recovering the View: Benchmarking Physical Active Vision for Occlusion Recovery in Robotic Manipulation', Available at: https://omanscience.com/en/articles/recovering-the-view-benchmarking-physical-active-vision-for-occlusion-recovery-in-robotic-manipulation.
Vancouver
Luo K, Huang Y, Zhong Q, Song X, Liu Y, Lin L. Recovering the View: Benchmarking Physical Active Vision for Occlusion Recovery in Robotic Manipulation. https://omanscience.com/en/articles/recovering-the-view-benchmarking-physical-active-vision-for-occlusion-recovery-in-robotic-manipulation
IEEE
K. Luo, Y. Huang, Q. Zhong, X. Song, Y. Liu, and L. Lin, "Recovering the View: Benchmarking Physical Active Vision for Occlusion Recovery in Robotic Manipulation," https://omanscience.com/en/articles/recovering-the-view-benchmarking-physical-active-vision-for-occlusion-recovery-in-robotic-manipulation.