About

Antonin Dallard is a leading researcher in humanoid robotics and human-robot interaction, specializing in teleoperation, motion synchronization, and assistive robotics. His work centers on creating seamless cybernetic avatar systems that enable intuitive human telepresence, allowing robots to mirror human movements with high fidelity. Dallard’s major contributions include a synchronized human-humanoid motion imitation framework that uses minimum-jerk models and recursive filters to achieve upper-body synchrony and walking pace prediction, as well as a closed-loop MPC-based walking controller that eliminates the need for traditional stabilizers in bipedal locomotion. His research on the RHP Friends humanoid robot demonstrates the integration of autonomous and teleoperated tasks for nursing applications, showcasing practical deployment in human-coexisting environments. With over 57 citations across his top papers, Dallard’s work has significantly advanced the fields of teleoperation, bipedal walking, and human-robot handovers. Notably, his 2024 paper on cybernetic avatar systems highlights his vision for connectivity and skill transfer, while his 2025 work on robust walking control represents a breakthrough in humanoid stability. Dallard’s achievements underscore his impact on making humanoid robots more capable and accessible for real-world assistance.

Research Focus

Key Achievements

4
H-Index
5
Papers
57
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Synchronized Human-Humanoid Motion Imitation
20 citations · 2023
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 36
🏛 Institutions: Centre National de la Recherche Scientifique, National Institute of Advanced Industrial Science and Technology, Robotics Research (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago