Do we still need Uncertainty Quantification for robotics? What does uncertainty mean in the modern robotics paradigm? 💡 We are organizing a workshop “Rethinking Uncertainty for Modern Robotics Paradigms” @ IROS 2026 Submit your work by Aug 23! 👇 (rethinking-uncertainty.githu…)

A planner then computes safe trajectories, which are executed by a learned pedipulation policy. This tight coupling results in much higher success rates and lets the robot reclassify heavy 'immovable' objects. Here's a look at more technical results: (3/4)

Bayesian Inference: We use this model with Bayesian inference to intelligently combine noisy sensor readings with prior knowledge about staircase already seen. This combination lets us tackle challenges like occlusions, clutter, limited field-of-view and sensor noise. (3/4)

Making robots safer on stairs! 💪 Our new work, just accepted to RA-L, introduces a clever way for robots to perceive the whole staircase, even when parts are hidden from view! 👀 Full paper: ieeexplore.ieee.org/document… @CMU_Robotics (1/4)