Zobrazeno 1 - 10
of 306
pro vyhledávání: '"McLoone, Sean"'
QUB-PHEO: A Visual-Based Dyadic Multi-View Dataset for Intention Inference in Collaborative Assembly
QUB-PHEO introduces a visual-based, dyadic dataset with the potential of advancing human-robot interaction (HRI) research in assembly operations and intention inference. This dataset captures rich multimodal interactions between two participants, one
Externí odkaz:
http://arxiv.org/abs/2409.15560
Reinforcement Learning (RL) or Deep Reinforcement Learning (DRL) is a powerful approach to solving Markov Decision Processes (MDPs) when the model of the environment is not known a priori. However, RL models are still faced with challenges such as ha
Externí odkaz:
http://arxiv.org/abs/2406.00732
Autor:
Olayemi, Kabirat, Van, Mien, McLoone, Sean, Sun, Yuzhu, Close, Jack, Nhat, Nguyen Minh, McIlvanna, Stephen
Autonomous ground vehicle (UGV) navigation has the potential to revolutionize the transportation system by increasing accessibility to disabled people, ensure safety and convenience of use. However, UGV requires extensive and efficient testing and ev
Externí odkaz:
http://arxiv.org/abs/2403.15067
Autor:
Sun, Yuzhu, Van, Mien, McIlvanna, Stephen, Nhat, Nguyen Minh, Olayemi, Kabirat, Close, Jack, McLoone, Seán
The evolution and growing automation of collaborative robots introduce more complexity and unpredictability to systems, highlighting the crucial need for robot's adaptability and flexibility to address the increasing complexities of their environment
Externí odkaz:
http://arxiv.org/abs/2403.13090
In this research, we present SLYKLatent, a novel approach for enhancing gaze estimation by addressing appearance instability challenges in datasets due to aleatoric uncertainties, covariant shifts, and test domain generalization. SLYKLatent utilizes
Externí odkaz:
http://arxiv.org/abs/2402.01555
To enable safe and effective human-robot collaboration (HRC) in smart manufacturing, seamless integration of sensing, cognition, and prediction into the robot controller is critical for real-time awareness, response, and communication inside a hetero
Externí odkaz:
http://arxiv.org/abs/2304.06923
In advanced manufacturing, strict safety guarantees are required to allow humans and robots to work together in a shared workspace. One of the challenges in this application field is the variety and unpredictability of human behavior, leading to pote
Externí odkaz:
http://arxiv.org/abs/2304.06867
Autor:
Sun, Yuzhu, Van, Mien, McIlvanna, Stephen, Nhat, Nguyen Minh, McLoone, Sean, Ceglarek, Dariusz, Ge, Shuzhi Sam
Physical human-robot collaboration (pHRC) requires both compliance and safety guarantees since robots coordinate with human actions in a shared workspace. This paper presents a novel fixed-time adaptive neural control methodology for handling time-va
Externí odkaz:
http://arxiv.org/abs/2303.02456
We develop a new framework for trajectory planning on predefined paths, for general N-link manipulators. Different from previous approaches generating open-loop minimum time controllers or pre-tuned motion profiles by time-scaling, we establish analy
Externí odkaz:
http://arxiv.org/abs/2211.05342
This paper proposes a novel fixed-time integral sliding mode controller for admittance control to enhance physical human-robot collaboration. The proposed method combines the benefits of compliance to external forces of admittance control and high ro
Externí odkaz:
http://arxiv.org/abs/2208.05065