ICRA 2026 awards Best Robot Learning Paper to research showing camera conditioning enables view-invariant robotic policy learning
The work reinforces the necessity of 3D geometric understanding.
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Just in time: the Best Paper Award in Robot Learning #ICRA2026 uses 3D camera pose to improve policy learning.
Pretty straightforward: robots live in a 3D world.
Image credit: @CSProfKGD
Have to disagree that robotics should not care about 3D.
Robots operate in a 3D world. Hand-eye calibration, 3D perception, grasp planning, motion planning, and contact-rich manipulation all rely on 3D geometry.
3D remains fundamental to robotics.
Just in time: the Best Paper Award in Robot Learning #ICRA2026 uses 3D camera pose to improve policy learning.
Pretty straightforward: robots live in a 3D world.
Image credit: @CSProfKGD
Have to disagree that robotics should not care about 3D.
Robots operate in a 3D world. Hand-eye calibration, 3D perception, grasp planning, motion planning, and contact-rich manipulation all rely on 3D geometry.
3D remains fundamental to robotics.
There may be some debate about HOW to do it but its clear robots need a good understanding of 3d
Just in time: the Best Paper Award in Robot Learning #ICRA2026 uses 3D camera pose to improve policy learning.
Pretty straightforward: robots live in a 3D world.
Image credit: @CSProfKGD