activity
20212025
most citedFast Object Inertial Parameter Identification for Collaborative Robots

20 citations · 25 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2025

Generating Stable Placements via Physics-guided Diffusion Models

Philippe Nadeau, Miguel Rogel, Ivan Bilić +2

Stably placing an object in a multi-object scene is a fundamental challenge in robotic manipulation, as placements must be penetration-free, establish precise surface contact, and…

cs.RO2024

Robustness Assessment of Assemblies in Frictional Contact

Philippe Nadeau, Jonathan Kelly

This work establishes a solution to the problem of assessing the capacity of multi-object assemblies to withstand external forces without becoming unstable. Our physically-grounded…

cs.RO2024★ 1 cited

Stable Object Placement Planning From Contact Point Robustness

Philippe Nadeau, Jonathan Kelly

We introduce a planner designed to guide robot manipulators in stably placing objects within intricate scenes. Our proposed method reverses the traditional approach to object place…

cs.RO2024

Automated Continuous Force-Torque Sensor Bias Estimation

Philippe Nadeau, Miguel Rogel Garcia, Emmett Wise +1

Six axis force-torque sensors are commonly attached to the wrist of serial robots to measure the external forces and torques acting on the robot's end-effector. These measurements…

cs.RO2023★ 4 cited

The Sum of Its Parts: Visual Part Segmentation for Inertial Parameter Identification of Manipulated Objects

Philippe Nadeau, Matthew Giamou, Jonathan Kelly

To operate safely and efficiently alongside human workers, collaborative robots (cobots) require the ability to quickly understand the dynamics of manipulated objects. However, tra…

cs.RO2022★ 20 cited

Fast Object Inertial Parameter Identification for Collaborative Robots

Philippe Nadeau, Matthew Giamou, Jonathan Kelly

Collaborative robots (cobots) are machines designed to work safely alongside people in human-centric environments. Providing cobots with the ability to quickly infer the inertial p…

cs.RO2022

Learning to Detect Slip with Barometric Tactile Sensors and a Temporal Convolutional Neural Network

Abhinav Grover, Philippe Nadeau, Christopher Grebe +1

The ability to perceive object slip via tactile feedback enables humans to accomplish complex manipulation tasks including maintaining a stable grasp. Despite the utility of tactil…

cs.RO2021

Under Pressure: Learning to Detect Slip with Barometric Tactile Sensors

Abhinav Grover, Christopher Grebe, Philippe Nadeau +1

Despite the utility of tactile information, tactile sensors have yet to be widely deployed in industrial robotics settings. Part of the challenge lies in identifying slip and other…