About

Manarshhjot Singh’s research lies at the intersection of robotics, energy optimization, and system health management, with a focus on wheeled mobile robots (WMRs) and continuum manipulators. His work introduces a curve-based geometric framework for optimal trajectory planning that minimizes energy consumption in WMRs, a critical advancement for autonomous systems where battery life and efficiency are paramount. Singh also pioneered the use of bond graph modeling—a graphical, energy-based approach—to estimate power consumption across multiple driving modes and to enable prognosis and health management in mechatronic systems, using energy activity as a key fault-detection parameter. His research extends to continuum robots, where he developed methods for accurate shape reconstruction and unified geometric planning for mobile-continuum manipulators, enhancing dexterity in structured environments for applications in medical, military, and exploration domains. Though early in his career, with his most-cited paper garnering 3 citations, Singh’s contributions are foundational, offering novel, integrated solutions for energy-aware robotics and system reliability. His work is particularly notable for bridging theoretical modeling with practical, real-world autonomous systems, setting the stage for safer, more efficient robotic operations.

Research Focus

Key Achievements

2
H-Index
5
Papers
11
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Curve-based Approach for Optimal Trajectory Planning with Optimal Energy Consumption: application to Wheeled Mobile Robots
3 citations · 2020
📈 Most Prolific Year: 2018 (3 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Polytech Lille, Laboratoire de Conception et d'Intégration des Systèmes, Université de Lille, Centre National de la Recherche Scientifique, Centre de Recherche en Informatique, Signal et Automatique de Lille

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago