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Continuous Jumping for Legged Robots on Stepping Stones via Trajectory Optimization and Model Predictive Control

Published in 2022 IEEE 61st Conference on Decision and Control (CDC), 2022

Recommended citation: C. Nguyen*, L. Bao*, Q. Nguyen. (2022). "Continuous Jumping for Legged Robots on Stepping Stones via Trajectory Optimization and Model Predictive Control." 2022 IEEE 61st Conference on Decision and Control (CDC). (* Equal contribution)
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Learning Bipedal Walking on a Quadruped Robot via Adversarial Motion Priors

Published in Annual Conference Towards Autonomous Robotic Systems (TAROS), 2024

Recommended citation: T. Peng, L. Bao, J. Humphreys, A.M. Delfaki, D. Kanoulas, C. Zhou. (2024). "Learning Bipedal Walking on a Quadruped Robot via Adversarial Motion Priors." Annual Conference Towards Autonomous Robotic Systems (TAROS).
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Deep Reinforcement Learning for Robotic Bipedal Locomotion: A Brief Survey

Published in Artificial Intelligence Review, 2025

Recommended citation: L. Bao, J. Humphreys, T. Peng, C. Zhou. (2025). "Deep Reinforcement Learning for Robotic Bipedal Locomotion: A Brief Survey." Artificial Intelligence Review.
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OmniDexter: A Modular Tendon-Driven Robotic Wrist with Enhanced Precision and Versatility

Published in UK Robot Manipulation Workshop 2025, 2025

Recommended citation: M. Song, M. Zhang, A. Lyu, L. Bao, T. Peng, C. Zhou. (2025). "OmniDexter: A Modular Tendon-Driven Robotic Wrist with Enhanced Precision and Versatility." UK Robot Manipulation Workshop 2025.
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Mastering Agile Jumping Skills from Simple Practices with Iterative Learning Control

Published in 2025 IEEE International Conference on Robotics and Automation (ICRA), 2025

Recommended citation: C. Nguyen*, L. Bao*, Q. Nguyen. (2025). "Mastering Agile Jumping Skills from Simple Practices with Iterative Learning Control." 2025 IEEE International Conference on Robotics and Automation (ICRA). (* Equal contribution)
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Hierarchical Intention-Aware Expressive Motion Generation for Humanoid Robots

Published in arXiv preprint arXiv:2506.01563, 2025

Recommended citation: L. Bao, Y. Pan, T. Peng, D. Kanoulas, C. Zhou. (2025). "Hierarchical Intention-Aware Expressive Motion Generation for Humanoid Robots." arXiv preprint arXiv:2506.01563.
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Gait-Conditioned Reinforcement Learning with Multi-Phase Curriculum for Humanoid Locomotion

Published in 2025 IEEE-RAS 24th International Conference on Humanoid Robots (Humanoids), 2025

Recommended citation: T. Peng, L. Bao, C. Zhou. (2025). "Gait-Conditioned Reinforcement Learning with Multi-Phase Curriculum for Humanoid Locomotion." 2025 IEEE-RAS 24th International Conference on Humanoid Robots (Humanoids).
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Sim-to-Real Transfer in Deep Reinforcement Learning for Bipedal Locomotion

Published in arXiv preprint arXiv:2511.06465, 2025

Recommended citation: L. Bao, T. Peng, C. Zhou. (2025). "Sim-to-Real Transfer in Deep Reinforcement Learning for Bipedal Locomotion." arXiv preprint arXiv:2511.06465.
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A High-Fidelity Digital Twin for Robotic Manipulation Based on 3D Gaussian Splatting

Published in arXiv preprint arXiv:2601.03200, 2026

Recommended citation: Z. Sun, L. Bao, T. Peng, J. Sun, C. Zhou. (2026). "A High-Fidelity Digital Twin for Robotic Manipulation Based on 3D Gaussian Splatting." arXiv preprint arXiv:2601.03200.
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SanD-Planner: Sample-Efficient Diffusion Planner in B-Spline Space for Robust Local Navigation

Published in arXiv preprint arXiv:2602.00923, 2026

Recommended citation: J. Wang, L. Bao, T. Yang, D.M. Plasencia, J. Jiao, D. Kanoulas. (2026). "SanD-Planner: Sample-Efficient Diffusion Planner in B-Spline Space for Robust Local Navigation." arXiv preprint arXiv:2602.00923.
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SCDP: Learning Humanoid Locomotion from Partial Observations via Mixed-Observation Distillation

Published in arXiv preprint arXiv:2603.09574, 2026

Recommended citation: M. Carroll, T. Peng, L. Bao, C. Zhou, Z. Li. (2026). "SCDP: Learning Humanoid Locomotion from Partial Observations via Mixed-Observation Distillation." arXiv preprint arXiv:2603.09574.
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UCL–NVIDIA Robotics Day Coordination & Showcase

Published: February 10, 2026

I had the great pleasure of coordinating the UCL–NVIDIA Robotics Day, bringing together colleagues across the UCL Robotics Institute, UCL Advanced Research Computing (ARC), and UCL Engineering to engage deeply with NVIDIA’s cutting-edge robotics stack.

Talk at UCL Robot Society

Published: March 21, 2026

Talk at UCL Robot Society.

COMP0205 Mechatronics and Making

Undergraduate Module, University College London, Department of Computer Science, 2025

Mechatronics is an interdisciplinary field that combines mechanical engineering, electronics, computer science, and control systems, and is crucially important for modern society. In this module, students will learn to design and analyse integrated robotic systems, solve problems and investigate case studies, obtain vital hands-on experience while working with practical small-scale manufacturing hardware, and study various aspects of ethics in application to robotics and AI systems.

COMP0244 Legged Robotics Systems

Undergraduate/Postgraduate Module, University College London, Department of Computer Science, 2025

This module provides students with the opportunity to deepen their knowledge on legged robotic systems. Unlike wheeled robots, which are constrained to flat surfaces, or drones, which face limitations due to safety and power consumption, legged robots offer a versatile alternative. Inspired by natural organisms, these systems have demonstrated remarkable success in navigating challenging environments, from climbing staircases to traversing mountainous terrains while carrying heavy loads.