10 citations · 25 across the 22 of their papers we have counts for
21 papers · 1 filter
GUIDER: Evaluating Goal-Free Human Intent Inference for Teleoperated Manipulation on Real-Robot Data
Nicholas Kenny, Cesar Alan Contreras, Basile Ouedraogo +3
This paper presents an evaluation of a goal-free probabilistic framework for human intent inference during robotic manipulation. We deploy the Global User Intent Dual-phase Estimat…
End-to-end example-based sim-to-real RL policy transfer based on neural stylisation with application to robotic cutting
Jamie Hathaway, Alireza Rastegarpanah, Rustam Stolkin
Whereas reinforcement learning has been applied with success to a range of robotic control problems in complex, uncertain environments, reliance on extensive data - typically sourc…
Intent-Driven LLM Ensemble Planning for Flexible Multi-Robot Disassembly: Demonstration on EV Batteries
Cansu Erdogan, Cesar Alan Contreras, Alireza Rastegarpanah +2
This paper addresses the problem of planning complex manipulation tasks, in which multiple robots with different end-effectors and capabilities, informed by computer vision, must p…
First Responders' Perceptions of Semantic Information for Situational Awareness in Robot-Assisted Emergency Response
Tianshu Ruan, Zoe Betta, Georgios Tzoumas +2
This study investigates First Responders' (FRs) attitudes toward the use of semantic information and Situational Awareness (SA) in robotic systems during emergency operations. A st…
Hybrid Task and Motion Planning with Reactive Collision Handling for Multi-Robot Disassembly of Complex Products: Application to EV Batteries
Abdelaziz Shaarawy, Cansu Erdogan, Rustam Stolkin +1
This paper addresses the problem of multi-robot coordination for complex manipulation task sequences. We present a vision-driven task-and-motion planning (TAMP) framework for a rea…
Utilizing Vision-Language Models as Action Models for Intent Recognition and Assistance
Cesar Alan Contreras, Manolis Chiou, Alireza Rastegarpanah +2
Human-robot collaboration requires robots to quickly infer user intent, provide transparent reasoning, and assist users in achieving their goals. Our recent work introduced GUIDER,…
Probabilistic Human Intent Prediction for Mobile Manipulation: An Evaluation with Human-Inspired Constraints
Cesar Alan Contreras, Manolis Chiou, Alireza Rastegarpanah +2
Accurate inference of human intent enables human-robot collaboration without constraining human control or causing conflicts between humans and robots. We present GUIDER (Global Us…
An Exploratory Study on Human-Robot Interaction using Semantics-based Situational Awareness
Tianshu Ruan, Aniketh Ramesh, Rustam Stolkin +1
In this paper, we investigate the impact of high-level semantics (evaluation of the environment) on Human-Robot Teams (HRT) and Human-Robot Interaction (HRI) in the context of mobi…
GIFT: Geometry-Induced Functional Transfer for Category-level Object Manipulation
Cristiana de Farias, Luis Figueredo, Riddhiman Laha +5
Robotic manipulation of unfamiliar objects in new environments is challenging due to limited generalisation capabilities. We propose a new skill transfer framework, GIFT (Geometry-…
A Framework for Semantics-based Situational Awareness during Mobile Robot Deployments
Tianshu Ruan, Aniketh Ramesh, Hao Wang +6
Deployment of robots into hazardous environments typically involves a ``Human-Robot Teaming'' (HRT) paradigm, in which a human supervisor interacts with a remotely operating robot…
The ATTUNE model for Artificial Trust Towards Human Operators
Giannis Petousakis, Angelo Cangelosi, Rustam Stolkin +1
This paper presents a novel method to quantify Trust in HRI. It proposes an HRI framework for estimating the Robot Trust towards the Human in the context of a narrow and specified…
A Mini-Review on Mobile Manipulators with Variable Autonomy
Cesar Alan Contreras, Alireza Rastegarpanah, Rustam Stolkin +1
This paper presents a mini-review of the current state of research in mobile manipulators with variable levels of autonomy, emphasizing their associated challenges and application…
Semi-autonomous Robotic Disassembly Enhanced by Mixed Reality
Alireza Rastegarpanah, Cesar Alan Contreras, Rustam Stolkin
In this study, we introduce "SARDiM," a modular semi-autonomous platform enhanced with mixed reality for industrial disassembly tasks. Through a case study focused on EV battery di…
Imitation learning for sim-to-real transfer of robotic cutting policies based on residual Gaussian process disturbance force model
Jamie Hathaway, Rustam Stolkin, Alireza Rastegarpanah
Robotic cutting, or milling, plays a significant role in applications such as disassembly, decommissioning, and demolition. Planning and control of cutting in real-world scenarios…
Haptic-guided assisted telemanipulation approach for grasping desired objects from heaps
Maxime Adjigble, Rustam Stolkin, Naresh Marturi
This paper presents an assisted telemanipulation framework for reaching and grasping desired objects from clutter. Specifically, the developed system allows an operator to select a…
A Supervised Machine Learning Approach to Operator Intent Recognition for Teleoperated Mobile Robot Navigation
Evangelos Tsagkournis, Dimitris Panagopoulos, Giannis Petousakis +3
In applications that involve human-robot interaction (HRI), human-robot teaming (HRT), and cooperative human-machine systems, the inference of the human partner's intent is of crit…
Towards Reuse and Recycling of Lithium-ion Batteries: Tele-robotics for Disassembly of Electric Vehicle Batteries
Jamie Hathaway, Abdelaziz Shaarawy, Cansu Akdeniz +3
Disassembly of electric vehicle batteries is a critical stage in recovery, recycling and re-use of high-value battery materials, but is complicated by limited standardisation, desi…
Learning robotic milling strategies based on passive variable operational space interaction control
Jamie Hathaway, Alireza Rastegarpanah, Rustam Stolkin
This paper addresses the problem of robotic cutting during disassembly of products for materials separation and recycling. Waste handling applications differ from milling in manufa…
Robot Health Indicator: A Visual Cue to Improve Level of Autonomy Switching Systems
Aniketh Ramesh, Madeleine Englund, Andreas Theodorou +2
Using different Levels of Autonomy (LoA), a human operator can vary the extent of control they have over a robot's actions. LoAs enable operators to mitigate a robot's performance…
A Taxonomy of Semantic Information in Robot-Assisted Disaster Response
Tianshu Ruan, Hao Wang, Rustam Stolkin +1
This paper proposes a taxonomy of semantic information in robot-assisted disaster response. Robots are increasingly being used in hazardous environment industries and emergency res…
Robot Vitals and Robot Health: Towards Systematically Quantifying Runtime Performance Degradation in Robots Under Adverse Conditions
Aniketh Ramesh, Rustam Stolkin, Manolis Chiou
This paper addresses the problem of automatically detecting and quantifying performance degradation in remote mobile robots during task execution. A robot may encounter a variety o…