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Èric Pairet

10 accepted papers

2023

Model-Based Underwater 6D Pose Estimation From RGB

RA-L 2023

Object pose estimation underwater allows an autonomous system to perform tracking and intervention tasks. Nonetheless, underwater target pose estimation is remarkably challenging due to, among many factors, limited visibility, light scattering, cluttered environments, and constantly varying water co

Cited by 11SourceScholar
2022

Side-Pull Maneuver: A Novel Control Strategy for Dragging a Cable-Tethered Load of Unknown Weight Using a UAV

RA-L 2022

This work presents an approach for dealing with suspended-cable load transportation using unmanned aerial vehicles (UAVs), specifically when the cargo overcomes the lifting capacity. Herein, this approach is referred to as the Side-Pull Maneuver (SPM). This maneuver is an alternative and viable stra

Cited by 26SourceScholar
2021

Affordance-Aware Handovers With Human Arm Mobility Constraints

RA-L 2021

Reasoning about object handover configurations allows an assistive agent to estimate the appropriateness of handover for a receiver with different arm mobility capacities. While there are existing approaches for estimating the effectiveness of handovers, their findings are limited to users without a

Cited by 27SourceScholar
2021

Building Affordance Relations for Robotic Agents - A Review

IJCAI 2021poster

Affordances describe the possibilities for an agent to perform actions with an object. While the significance of the affordance concept has been previously studied from varied perspectives, such as psychology and cognitive science, these approaches are not always sufficient to enable direct transfer…

Cited by 21SourcePDFScholar
2021

Path Planning for Manipulation Using Experience-Driven Random Trees

RA-L 2021

Robotic systems may frequently come across similar manipulation planning problems that result in similar motion plans. Instead of planning each problem from scratch, it is preferable to leverage previously computed motion plans, i.e., experiences, to ease the planning. Different approaches have been

Cited by 28SourceScholar
2020

Self-Assessment of Grasp Affordance Transfer

IROS 2020poster

Reasoning about object grasp affordances allows an autonomous agent to estimate the most suitable grasp to execute a task. While current approaches for estimating grasp affordances are effective, their prediction is driven by hypotheses on visual features rather than an indicator of a proposal's sui…

Cited by 21SourceScholar
2019

Learning Generalizable Coupling Terms for Obstacle Avoidance via Low-Dimensional Geometric Descriptors

RA-L 2019

Unforeseen events are frequent in the real-world environments where robots are expected to assist, raising the need for fast replanning of the on-going policy to guarantee operational safety. Inspired by human behavioral studies of obstacle avoidance and route selection, this letter presents a hiera

Cited by 33SourceScholar
2019

Learning Grasp Affordance Reasoning Through Semantic Relations

RA-L 2019

Reasoning about object affordances allows an autonomous agent to perform generalised manipulation tasks among object instances. While current approaches to grasp affordance estimation are effective, they are limited to a single hypothesis. We present an approach for detection and extraction of multi

Cited by 75SourceScholar
2018

Uncertainty-based Online Mapping and Motion Planning for Marine Robotics Guidance

IROS 2018poster

In real-world robotics, motion planning remains to be an open challenge. Not only robotic systems are required to move through unexplored environments, but also their manoeuvrability is constrained by their dynamics and often suffer from uncertainty. One approach to overcome this problem is to incre…

Cited by 24SourceScholar