From the 1 of 8 linked papers with an AI index.
8 papers
TACTIC: Tactile and Vision Conditioned Contact-Centric Control for Whole-Arm Manipulation
Rishabh Madan, Angchen Xie, Samantha Saak +7
The paper introduces TACTIC, a receding‑horizon controller that combines RGB‑D vision and distributed tactile sensing with a contact‑centric predictive model to plan and execute wh…
Impact of Different Failures on a Robot's Perceived Reliability
Andrew Violette, Zhanxin Wu, Haruki Nishimura +5
Robots fail, potentially leading to a loss in the robot's perceived reliability (PR), a measure correlated with trustworthiness. In this study we examine how various kinds of failu…
A Systematic Study of Data Modalities and Strategies for Co-training Large Behavior Models for Robot Manipulation
Fanqi Lin, Kushal Arora, Jean Mercat +9
Large behavior models have shown strong dexterous manipulation capabilities by extending imitation learning to large-scale training on multi-task robot data, yet their generalizati…
Robot-Powered Data Flywheels: Deploying Robots in the Wild for Continual Data Collection and Foundation Model Adaptation
Jennifer Grannen, Michelle Pan, Kenneth Llontop +4
Foundation models (FM) have unlocked powerful zero-shot capabilities in vision and language, yet their reliance on internet pretraining data leaves them brittle in unstructured, re…
A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation
TRI LBM Team, Jose Barreiros, Andrew Beaulieu +79
Robot manipulation has seen tremendous progress in recent years, with imitation learning policies enabling successful performance of dexterous and hard-to-model tasks. Concurrently…
Re4MPC: Reactive Nonlinear MPC for Multi-model Motion Planning via Deep Reinforcement Learning
NeÅet Ãnver Akmandor, Sarvesh Prajapati, Mark Zolotas +1
Traditional motion planning methods for robots with many degrees-of-freedom, such as mobile manipulators, are often computationally prohibitive for real-world settings. In this pap…