Thesis
Machine Learning Driven Multimodal Control for Human-Robot Interaction
PhD thesis, University of Brighton
Publications
Journal articles, published conference papers, reviews and selected working papers, with direct links to the publisher or open version where available.
Showing 12 publications
Thesis
PhD thesis, University of Brighton
Journal article
Concurrency and Computation: Practice and Experience · Vol. 38, Issue 6, e70643 · Open access
AI-RTGM: an end-to-end framework that couples CNN-based gesture recognition (GESTID) with trajectory generation and execution (TAGEM) for real-time task control of a 7-DoF manipulator.
Review
Working paper
Book chapter
SAFER-TEA 2024 — 2nd EAI International Conference on Safe, Secure, Ethical, Responsible Technologies and Emerging Applications · Springer LNICST, pp. 201–218
Conference
IEEE International Conference on Advanced Robotics and Mechatronics (ICARM 2025) · IEEE ICARM 2025 · pp. 452–457 · Portsmouth, UK
GPT-4-based few-shot prompting converts English and German instructions into robot commands for beverage preparation on a Franka Emika Panda — 83% overall task accuracy, with a 3% gap between languages.
Review
SN Computer Science · Vol. 6, Article 588 · Springer Nature
A review of how transformer-based language and vision models are being integrated with robot control for task planning, decision-making and adaptive manipulation, and where they still fall short.
Conference
First German Robotics Conference, Nuremberg · Peer-reviewed conference abstract · full text on arXiv
Sinusoidal trajectory generation with velocity scaling to reduce energy use while keeping motion smooth and accurate, evaluated on a 7-DoF arm in PyBullet.
Conference
IEEE International Conference on Emerging Technologies and Innovation for Sustainability (EmergIN 2025) · IEEE EmergIN 2025 · pp. 886–890
LLM-based task planning on top of RL-based low-level control (PPO/SAC), evaluated in PyBullet with a simulated Franka Emika Panda.
Conference
ICRA@40 — 40th Anniversary of the IEEE Conference on Robotics and Automation · Rotterdam, Netherlands, 23–26 September 2024 · peer-reviewed
Preprint
arXiv preprint · arXiv:2409.06503 [cs.RO]
Preprint
arXiv preprint · arXiv:2409.06419 · work from Jamia Millia Islamia
Preprint
arXiv preprint · arXiv:2409.04785
Citation counts change constantly, so they are not reproduced here — Google Scholar has the current figures. Formal author lists and citation exports remain available from the linked publisher records.