K. Rajchandar

About

K. Rajchandar is a researcher advancing the frontiers of autonomous robotics, with a primary focus on multi-robot coordination, path planning, and navigation. His work addresses fundamental challenges in deploying intelligent robotic systems, from optimizing task allocation among robot teams to ensuring collision-free movement in complex environments. His most cited paper, "A novel fuzzy and reverse auction‐based algorithm for task allocation with optimal path cost in multi‐robot systems" (2021, 12 citations), introduces a hybrid approach that combines fuzzy logic with auction theory to solve the critical problem of distributing tasks while minimizing path costs and computational time. Rajchandar has also made significant contributions to navigation techniques, as evidenced by his 2024 survey on the topic (9 citations), and continues to push boundaries with recent work on bi-directional virtual search algorithms for dynamic environments (2025). His development of the "Quadrant Selection Method" for multi-objective path planning further demonstrates his commitment to creating efficient, practical solutions for real-world robotic applications, establishing him as a rising voice in the field of autonomous navigation.

Research Focus

Key Achievements

Top Papers

1. 1
   A novel fuzzy and reverse auction‐based algorithm for task allocation with optimal path cost in multi‐robot systems

   12 citations · 2021
2. 2
   Robotics and its Navigation Techniques

   9 citations · 2024
3. 3
   Bi-directional virtual search algorithm for efficient and collision-free path planning in autonomous robots navigating static and dynamic environments

   3 citations · 2025
4. 4
   An Approach to Improve Multi objective Path Planning for Mobile Robot Navigation using the Novel Quadrant Selection Method

   3 citations · 2021

Key Collaborators

Contact & Links