arXiv subjects

Paul Bremner

Publications and source records attributed to Paul Bremner.

4 recordsLinked to original sources

arXiv2026

Design and Evaluation of a Touchscreen-Based Teleoperation Interface for Robotic Manipulators

Intuitive teleoperation interfaces are crucial for the safe and effective operation of robotic manipulators in challenging environments. In the nuclear industry, surface contact tasks such as swab sampling require precise path and force tracking, obstacle avoidance, and sustained operator attention, which conventional joystick interfaces struggle to support effectively. This study designs and evaluates a novel touchscreen teleoperation interface that maps continuous finger movements directly to robotic manipulator motions, provides finer velocity control, and integrates control with visualization, enabling more natural, precise, and intuitive surface interaction than conventional controllers. A comparative user study with 20 participants evaluated task performance and workload using the proposed touchscreen, a conventional joystick, and a single-click autonomous mode. Tasks simulated realistic surface manipulation using a Franka Emika Panda arm, remotely controlled from another country. Kinematic, physiological, and behavioral data were recorded to comprehensively assess task performance, cognitive load, and operator trust across each control condition. Participants completed teleoperation tasks more efficiently and accurately with the touchscreen interface, achieving a 53.5% reduction in completion time (median: 2.50 vs. 5.38 min), higher in-area coverage on the sinusoidal path (90.7% vs. 84.1%), and lower overshoot on both path geometries compared with the joystick. Cognitive load, quantified via NASA-TLX (0-100), decreased from joystick to touchscreen (mean TLX 52 to 43; -9 points, -17.3%) and was lowest under the autonomous one-click mode (31; -21 points vs. joystick, -40.4%; -12 vs. touchscreen, -27.9%). This research presents an easy-to-implement touchscreen interface that improves performance in teleoperated surface tasks while reducing cognitive load.

cs.RO↗

arXiv2026

Robot Learning from Human Demonstrations: Handwritten Alphabet Trajectories and Human-Likeness Evaluation

Learning from demonstration (LfD) provides a developmental framework through which robots can develop motor skills by observing and imitating human dynamics, reducing reliance on explicit programming to teach a skill to a robot. The resulting human-like robot motion is recognised as a key factor in building trust and enabling natural collaboration in human-robot interaction. This paper presents a framework for learning human-like robot motion from demonstration, including data collection, probabilistic trajectory learning, and perceptual user evaluation. A dataset of 3,142 handwriting demonstrations was collected from 22 participants across all 52 Latin alphabet character-case combinations via a touchscreen teleoperation interface, capturing planar position, contact force, and timing. Building on the widely used Gaussian Mixture Model and Gaussian Mixture Regression approach for learning from demonstration, the framework is extended in this work by incorporating force and normalised time dimensions to enable richer representation of human dynamics, and adapting it to handle non-continuous, multi-segment trajectories, enabling generalisation across demonstrations. A user study with 21 participants evaluated the perceived human-likeness of the generated trajectories using a continuous scale anchored between robotic and human-like motion, normalised to 0-100 where 50 represents the neutral midpoint. The generated trajectories achieved an overall human-likeness score of 71.50 (SD=22.56), indicating that the majority of trajectories were perceived as more human-like. Participants identified geometric positioning and trajectory sequence as the most influential perceptual factors, and reported positive attitudes toward human-like robot behaviour. The datasets are released as open-source, providing a reproducible benchmark for developing and evaluating human-like robot motion methods.

cs.RO↗

arXiv2024

The Ballad of the Bots: Sonification Using Cognitive Metaphor to Support Immersed Teleoperation of Robot Teams

As an embodied and spatial medium, virtual reality is proving an attractive proposition for robot teleoperation in hazardous environments. This paper examines a nuclear decommissioning scenario in which a simulated team of semi-autonomous robots are used to characterise a chamber within a virtual nuclear facility. This study examines the potential utility and impact of sonification as a means of communicating salient operator data in such an environment. However, the question of what sound should be used and how it can be applied in different applications is far from resolved. This paper explores and compares two sonification design approaches. The first is inspired by the theory of cognitive metaphor to create sonifications that align with socially acquired contextual and ecological understanding of the application domain. The second adopts a computationalist approach using auditory mappings that are commonplace in the literature. The results suggest that the computationalist approach outperforms the cognitive metaphor approach in terms of predictability and mental workload. However, qualitative data analysis demonstrates that the cognitive metaphor approach resulted in sounds that were more intuitive, and were better implemented for spatialisation of data sources and data legibility when there was more than one sound source.

cs.RO↗

arXiv2020

Towards an immersive user interface for waypoint navigation of a mobile robot

In this paper, we investigate the utility of head-mounted display (HMD) interfaces for navigation of mobile robots. We focus on the selection of waypoint positions for the robot, whilst maintaining an egocentric view of the robot's environment. Inspired by virtual reality (VR) gaming, we propose a target selection method that uses the 6 degrees-of-freedom tracked controllers of a commercial VR headset. This allows an operator to point to the desired target position, in the vicinity of the robot, which the robot then autonomously navigates towards. A user study (37 participants) was conducted to examine the efficacy of this control strategy when compared to direct control, both with and without a communication delay. The results of the experiment showed that participants were able to learn how to use the novel system quickly, and the majority of participants reported a preference for waypoint control. Across all recorded metrics (task performance, operator workload and usability) the proposed waypoint control interface was not significantly affected by the communication delay, in contrast to direct control. The simulated experiment indicated that a real-world implementation of the proposed interface could be effective, but also highlighted the need to manage the negative effects of HMDs - particularly VR sickness.

cs.RO↗