papers

Publications (55)

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…

cs.RO2024

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…

cs.NE2024

An accelerate Prediction Strategy for Dynamic Multi-Objective Optimization

Ru Lei, Lin Li, Rustam Stolkin +1

This paper addresses the challenge of dynamic multi-objective optimization problems (DMOPs) by introducing novel approaches for accelerating prediction strategies within the evolut…

cs.RO2022

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…

cs.RO2025

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…

cs.RO2017

Human-in-the-loop optimisation: mixed initiative grasping for optimally facilitating post-grasp manipulative actions

Amir M. Ghalamzan Esfahani, Firas Abi-Farraj, Paolo Robuffo Giordano +1

This paper addresses the problem of mixed initiative, shared control for master-slave grasping and manipulation. We propose a novel system, in which an autonomous agent assists a h…

cs.RO2023

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…

cs.RO2022

Robot-Assisted Nuclear Disaster Response: Report and Insights from a Field Exercise

Manolis Chiou, Georgios-Theofanis Epsimos, Grigoris Nikolaou +4

This paper reports on insights by robotics researchers that participated in a 5-day robot-assisted nuclear disaster response field exercise conducted by Kerntechnische Hilfdienst G…

cs.RO2023

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…

cs.RO2024

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…

cs.RO2024

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…

cs.CV2023

Local Region-to-Region Mapping-based Approach to Classify Articulated Objects

Ayush Aggarwal, Rustam Stolkin, Naresh Marturi

Autonomous robots operating in real-world environments encounter a variety of objects that can be both rigid and articulated in nature. Having knowledge of these specific object pr…

cs.RO2026

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-…

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.RO2025

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…

cs.RO2020

Mixed-Initiative variable autonomy for remotely operated mobile robots

Manolis Chiou, Nick Hawes, Rustam Stolkin

This paper presents an Expert-guided Mixed-Initiative Control Switcher (EMICS) for remotely operated mobile robots. The EMICS enables switching between different levels of autonomy…

cs.RO2017

Safe Robotic Grasping: Minimum Impact-Force Grasp Selection

Nikos Mavrakis, Amir M. Ghalamzan E., Rustam Stolkin

This paper addresses the problem of selecting from a choice of possible grasps, so that impact forces will be minimised if a collision occurs while the robot is moving the grasped…

cs.RO2025

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…

cs.CV2017

A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition

Cheng Zhao, Li Sun, Rustam Stolkin

This paper addresses the problem of simultaneous 3D reconstruction and material recognition and segmentation. Enabling robots to recognise different materials (concrete, metal etc.…

cs.RO2023

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…

cs.RO2020

VFH+ based shared control for remotely operated mobile robots

Pantelis Pappas, Manolis Chiou, Georgios-Theofanis Epsimos +2

This paper addresses the problem of safe and efficient navigation in remotely controlled robots operating in hazardous and unstructured environments; or conducting other remote rob…

cs.RO2025

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…

cs.RO2026

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…

cs.RO2019

Automatic Detection of Myocontrol Failures Based upon Situational Context Information

Karoline Heiwolt, Claudio Zito, Markus Nowak +2

Myoelectric control systems for assistive devices are still unreliable. The user's input signals can become unstable over time due to e.g. fatigue, electrode displacement, or sweat…

cs.RO2026

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…

cs.RO2022

Trust, Shared Understanding and Locus of Control in Mixed-Initiative Robotic Systems

Manolis Chiou, Faye McCabe, Markella Grigoriou +1

This paper investigates how trust, shared understanding between a human operator and a robot, and the Locus of Control (LoC) personality trait, evolve and affect Human-Robot Intera…

cs.RO2017

Single-Shot Clothing Category Recognition in Free-Configurations with Application to Autonomous Clothes Sorting

Li Sun, Gerardo Aragon-Camarasa, Simon Rogers +2

This paper proposes a single-shot approach for recognising clothing categories from 2.5D features. We propose two visual features, BSP (B-Spline Patch) and TSD (Topology Spatial Di…

cs.RO2019

Robust and fast generation of top and side grasps for unknown objects

Brice Denoun, Beatriz Leon, Claudio Zito +3

In this work, we present a geometry-based grasping algorithm that is capable of efficiently generating both top and side grasps for unknown objects, using a single view RGB-D camer…

cs.RO2019

Let's Push Things Forward: A Survey on Robot Pushing

Jochen Stüber, Claudio Zito, Rustam Stolkin

As robot make their way out of factories into human environments, outer space, and beyond, they require the skill to manipulate their environment in multifarious, unforeseeable cir…

cs.RO2023

Asservissement visuel 3D direct dans le domaine spectral

Maxime Adjigble, Brahim Tamadazte, Cristiana de Farias +2

This paper presents a direct 3D visual servo scheme for the automatic alignment of point clouds (respectively, objects) using visual information in the spectral domain. Specificall…

cs.RO2021

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.RO2023

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…

cs.RO2025

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,…

cs.RO2024

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…

cs.RO2019

Estimation and Exploitation of Objects' Inertial Parameters in Robotic Grasping and Manipulation: A Survey

Nikos Mavrakis, Rustam Stolkin

Inertial parameters characterise an object's motion under applied forces, and can provide strong priors for planning and control of robotic actions to manipulate the object. Howeve…

cs.CV2018

Sensors, SLAM and Long-term Autonomy: A Review

Mubariz Zaffar, Shoaib Ehsan, Rustam Stolkin +1

Simultaneous Localization and Mapping, commonly known as SLAM, has been an active research area in the field of Robotics over the past three decades. For solving the SLAM problem,…

cs.RO2023

Learning effects in variable autonomy human-robot systems: how much training is enough?

Manolis Chiou, Mohammed Talha, Rustam Stolkin

This paper investigates learning effects and human operator training practices in variable autonomy robotic systems. These factors are known to affect performance of a human-robot…

cs.RO2023

3D Spectral Domain Registration-Based Visual Servoing

Maxime Adjigble, Brahim Tamadazte, Cristiana de Farias +2

This paper presents a spectral domain registration-based visual servoing scheme that works on 3D point clouds. Specifically, we propose a 3D model/point cloud alignment method, whi…

cs.RO2021

Simultaneous Tactile Exploration and Grasp Refinement for Unknown Objects

Cristiana de Farias, Naresh Marturi, Rustam Stolkin +1

This paper addresses the problem of simultaneously exploring an unknown object to model its shape, using tactile sensors on robotic fingers, while also improving finger placement t…

cs.RO2018

Learning monocular visual odometry with dense 3D mapping from dense 3D flow

Cheng Zhao, Li Sun, Pulak Purkait +2

This paper introduces a fully deep learning approach to monocular SLAM, which can perform simultaneous localization using a neural network for learning visual odometry (L-VO) and d…

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.RO2019

2D Linear Time-Variant Controller for Human's Intention Detection for Reach-to-Grasp Trajectories in Novel Scenes

Claudio Zito, Tomasz Deregowski, Rustam Stolkin

Designing robotic assistance devices for manipulation tasks is challenging. This work is concerned with improving accuracy and usability of semi-autonomous robots, such as human op…

cs.RO2019

Metrics and Benchmarks for Remote Shared Controllers in Industrial Applications

Claudio Zito, Maxime Adjigble, Brice D. Denoun +3

Remote manipulation is emerging as one of the key robotics tasks needed in extreme environments. Several researchers have investigated how to add AI components into shared controll…

cs.CV2024

Self-supervised cross-modality learning for uncertainty-aware object detection and recognition in applications which lack pre-labelled training data

Irum Mehboob, Li Sun, Alireza Astegarpanah +1

This paper shows how an uncertainty-aware, deep neural network can be trained to detect, recognise and localise objects in 2D RGB images, in applications lacking annotated train-ng…

cs.CV2017

Dense RGB-D semantic mapping with Pixel-Voxel neural network

Cheng Zhao, Li Sun, Pulak Purkait +1

For intelligent robotics applications, extending 3D mapping to 3D semantic mapping enables robots to, not only localize themselves with respect to the scene's geometrical features…

cs.RO2022

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…

cs.CV2018

Weather Classification: A new multi-class dataset, data augmentation approach and comprehensive evaluations of Convolutional Neural Networks

Jose Carlos Villarreal Guerra, Zeba Khanam, Shoaib Ehsan +2

Weather conditions often disrupt the proper functioning of transportation systems. Present systems either deploy an array of sensors or use an in-vehicle camera to predict weather…

cs.RO2025

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…

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.RO2019

Hypothesis-based Belief Planning for Dexterous Grasping

Claudio Zito, Valerio Ortenzi, Maxime Adjigble +3

Belief space planning is a viable alternative to formalise partially observable control problems and, in the recent years, its application to robot manipulation problems has grown.…

cs.RO2017

Grasp that optimises objectives along post-grasp trajectories

Amir M Ghalamzan E, Nikos Mavrakis, Rustam Stolkin

In this article, we study the problem of selecting a grasping pose on the surface of an object to be manipulated by considering three post-grasp objectives. These objectives includ…

cs.RO2021

Dual Quaternion-Based Visual Servoing for Grasping Moving Objects

Cristiana de Farias, Maxime Adjigble, Brahim Tamadazte +2

This paper presents a new dual quaternion-based formulation for pose-based visual servoing. Extending our previous work on local contact moment (LoCoMo) based grasp planning, we de…

cs.RO2023

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…

cs.RO2022

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.CV2017

Weakly-supervised DCNN for RGB-D Object Recognition in Real-World Applications Which Lack Large-scale Annotated Training Data

Li Sun, Cheng Zhao, Rustam Stolkin

This paper addresses the problem of RGBD object recognition in real-world applications, where large amounts of annotated training data are typically unavailable. To overcome this p…