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Philippe Nadeau

5 accepted papers

2023

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

ICRA 2023poster

To operate safely and efficiently alongside human workers, collaborative robots (cobots) require the ability to quickly understand the dynamics of manipulated objects. However, traditional methods for estimating the full set of inertial parameters rely on motions that are necessarily fast and unsafe…

Cited by 6SourcecodeScholar
2022

Fast Object Inertial Parameter Identification for Collaborative Robots

ICRA 2022poster

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 parameters of manipulated objects will improve their flexibility and enable greater usage in manufacturing and other area…

Cited by 12SourcecodeScholar
2022

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

ICRA 2022poster

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 tactile information for many applications, tactile sensors have yet to be widely deployed in industrial robotics settings; par…

Cited by 13SourceScholar
2020

Tactile sensing based on fingertip suction flow for submerged dexterous manipulation

ICRA 2020poster

The ocean is a harsh and unstructured environment for robotic systems; high ambient pressures, saltwater corrosion and low-light conditions demand machines with robust electrical and mechanical parts that are able to sense and respond to the environment. Prior work shows that the addition of gentle…

Cited by 15SourceScholar