About

Suman Raj is a robotics researcher whose work focuses on solving fundamental challenges in autonomous navigation and bipedal locomotion. His key research areas include visual servoing, image-based navigation, and inverse kinematics for humanoid robots. Raj’s most cited paper, "Appearance-based indoor navigation by IBVS using mutual information" (2016, 9 citations), introduces a novel framework for image-based navigation that eliminates the need for feature extraction, matching, or 3D information by leveraging mutual information. This approach simplifies navigation by representing paths through automatically selected key images from a prior traversal, offering a robust solution for indoor environments. In his more recent work, "Inverse Kinematics Analysis of Cassie Robot using Radial Basis Function Networks" (2021, 2 citations), Raj tackles the high-order nonlinearity and computational complexity of inverse kinematics in bipedal humanoids, proposing a neural network-based method to handle joint constraints efficiently. While his citation counts are modest, Raj’s contributions demonstrate a commitment to advancing practical, computation-friendly robotics—particularly in vision-based control and legged locomotion—making his work relevant for researchers exploring minimalistic, data-driven approaches to robotic autonomy.

Research Focus

Key Achievements

2
H-Index
2
Papers
11
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Appearance-based indoor navigation by IBVS using mutual information
9 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Institut de Recherche en Informatique et Systèmes Aléatoires, Indian Institute of Science Bangalore

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago