8 papers
Moving On, Even When You're Broken: Fail-Active Trajectory Generation via Diffusion Policies Conditioned on Embodiment and Task
Gilberto G. Briscoe-Martinez, Yaashia Gautam, Rahul Shetty +3
Robot failure is detrimental and disruptive, often requiring human intervention to recover. Our vision is 'fail-active' operation, allowing robots to safely complete their tasks ev…
Dynamics-Compliant Trajectory Diffusion for Super-Nominal Payload Manipulation
Anuj Pasricha, Joewie Koh, Jay Vakil +1
Nominal payload ratings for articulated robots are typically derived from worst-case configurations, resulting in uniform payload constraints across the entire workspace. This cons…
Exploring How Non-Prehensile Manipulation Expands Capability in Robots Experiencing Multi-Joint Failure
Gilberto Briscoe-Martinez, Anuj Pasricha, Ava Abderezaei +4
This work explores non-prehensile manipulation (NPM) and whole-body interaction as strategies for enabling robotic manipulators to conduct manipulation tasks despite experiencing l…
Towards Super-Nominal Payload Handling: Inverse Dynamics Analysis for Multi-Skill Robotic Manipulation
Anuj Pasricha, Alessandro Roncone
Motion planning for articulated robots has traditionally been governed by algorithms that operate within manufacturer-defined payload limits. Our empirical analysis of the Franka E…
Clutter-Aware Spill-Free Liquid Transport via Learned Dynamics
Ava Abderezaei, Anuj Pasricha, Alex Klausenstock +1
In this work, we present a novel algorithm to perform spill-free handling of open-top liquid-filled containers that operates in cluttered environments. By allowing liquid-filled co…
The Virtues of Laziness: Multi-Query Kinodynamic Motion Planning with Lazy Methods
Anuj Pasricha, Alessandro Roncone
In this work, we introduce LazyBoE, a multi-query method for kinodynamic motion planning with forward propagation. This algorithm allows for the simultaneous exploration of a robot…
PokeRRT: A Kinodynamic Planning Approach for Poking Manipulation
Anuj Pasricha, Yi-Shiuan Tung, Bradley Hayes +1
This work introduces PokeRRT, a novel motion planning algorithm that demonstrates poking as an effective non-prehensile manipulation skill to enable fast manipulation of objects an…
PokeRRT: Poking as a Skill and Failure Recovery Tactic for Planar Non-Prehensile Manipulation
Anuj Pasricha, Yi-Shiuan Tung, Bradley Hayes +1
In this work, we introduce PokeRRT, a novel motion planning algorithm that demonstrates poking as an effective non-prehensile manipulation skill to enable fast manipulation of obje…