Papers
44
Total Citations
1,953
H-Index
15
About
Debasish Ghose is a pioneering figure in robotics and swarm intelligence, best known for two transformative contributions. His foundational work on collision avoidance introduced the **collision cone approach**, a novel geometric method that enables robots to predict and evade collisions with irregularly moving obstacles in dynamic environments. This concept, detailed in his 1998 paper (545 citations), has become a cornerstone of motion safety, later extended to 3-D environments and quadric surfaces. Ghose is equally celebrated for inventing **Glowworm Swarm Optimization (GSO)** , a nature-inspired algorithm that mimics the luminescent behavior of glowworms to solve multimodal optimization problems. His 2005 paper (343 citations) and subsequent works (totaling over 900 citations) demonstrated how GSO enables robot swarms to locate multiple signal sources—such as hazardous chemical spills or radiation—simultaneously. This breakthrough has profound implications for collective robotics, search-and-rescue, and environmental monitoring. Ghose’s research elegantly bridges theoretical rigor with practical application, earning him recognition as a leader in multi-robot systems and swarm intelligence. His work continues to inspire new generations of researchers in autonomous navigation and distributed optimization.
Research Focus
Key Achievements
Top Papers
- 1Obstacle avoidance in a dynamic environment: a collision cone approach545 citations · 1998
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- 3Glowworm swarm optimisation: a new method for optimising multi-modal functions192 citations · 2009
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- 8Collision Cones for Quadric Surfaces49 citations · 2011
- 9Glowworm Swarm Optimization33 citations · 2017
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