activity
20172022
most citedHypothesis-based Belief Planning for Dexterous Grasping

13 citations · 48 across the 13 of their papers we have counts for

collaborators
Showing cs.ROShow all

22 papers · 1 filter

cs.RO20221 cited

A Hierarchical Variable Autonomy Mixed-Initiative Framework for Human-Robot Teaming in Mobile Robotics

Dimitris Panagopoulos, Giannis Petousakis, Aniketh Ramesh +4

This paper presents a Mixed-Initiative (MI) framework for addressing the problem of control authority transfer between a remote human operator and an AI agent when cooperatively co…

cs.RO2022

Grasp Transfer for Deformable Objects by Functional Map Correspondence

Cristiana de Farias, Brahim Tamadazte, Rustam Stolkin +1

Handling object deformations for robotic grasping is still a major problem to solve. In this paper, we propose an efficient learning-free solution for this problem where generated…

cs.RO2021

Fessonia: a Method for Real-Time Estimation of Human Operator Workload Using Behavioural Entropy

Paraskevas Chatzithanos, Grigoris Nikolaou, Rustam Stolkin +1

This paper addresses the problem of the human operator cognitive workload estimation while controlling a robot. Being capable of assessing, in real-time, the operator's workload co…

cs.RO2021

A Bayesian-Based Approach to Human Operator Intent Recognition in Remote Mobile Robot Navigation

Dimitris Panagopoulos, Giannis Petousakis, Rustam Stolkin +2

This paper addresses the problem of human operator intent recognition during teleoperated robot navigation. In this context, recognition of the operator's intended navigational goa…

cs.RO20219 cited

Human operator cognitive availability aware Mixed-Initiative control

Giannis Petousakis, Manolis Chiou, Grigoris Nikolaou +1

This paper presents a Cognitive Availability Aware Mixed-Initiative Controller for remotely operated mobile robots. The controller enables dynamic switching between different level…

cs.RO2021

SpectGRASP: Robotic Grasping by Spectral Correlation

Maxime Adjigble, Cristiana de Farias, Rustam Stolkin +1

This paper presents a spectral correlation-based method (SpectGRASP) for robotic grasping of arbitrarily shaped, unknown objects. Given a point cloud of an object, SpectGRASP extra…