Narrendar RaviChandran

University of Auckland

Papers

2

Total Citations

34

H-Index

2

About

Narrendar RaviChandran is a pioneering researcher at the intersection of soft robotics, intelligent control, and human-centric automation. His work focuses on two transformative challenges: enhancing robotic manipulation through machine learning and developing accessible, body-powered prosthetic technologies. In his highly cited 2018 study (23 citations), RaviChandran pioneered the use of genetic algorithms and unsupervised machine learning to predict robotic manipulation failures during force-sensitive tasks, addressing a critical bottleneck in industrial automation where traditional sensor-heavy approaches fall short. This work demonstrated that intelligent algorithms could compensate for limited sensory data, significantly improving the reliability of pick-and-place operations. More recently, his 2022 research (11 citations) introduced a novel body-powered soft hydraulic actuator for prosthetic hands, leveraging the inherent compliance and dexterity of soft robotics to create lightweight, portable alternatives to rigid prosthetics. By harnessing natural body movements to power the actuator, RaviChandran’s design promises greater accessibility and intuitive control for amputees. His contributions are shaping a future where robots work more safely alongside humans and where prosthetic devices are both more functional and more affordable.

Research Focus

Key Achievements

2
H-Index
2
Papers
34
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Genetic algorithms and unsupervised machine learning for predicting robotic manipulation failures for force-sensitive tasks
23 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Auckland

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago