Papers
1
Total Citations
3
H-Index
1
About
Ch. Lokesh is a researcher whose work lies at the intersection of swarm intelligence, bio-inspired robotics, and multi-agent systems. His most notable contribution is the development of a “Butterfly Inspired Multi-robotic Swarm for Signal Source Localization,” a 2017 study that introduced the Butterfly Mating Optimization (BMO) algorithm. This meta-butterfly model draws from the cooperative social behaviors observed in biological species, offering a novel framework for coordinating robotic swarms in tasks like signal source localization. By translating the natural mating and foraging strategies of butterflies into a computational optimization tool, Lokesh has provided a fresh perspective on how decentralized, adaptive systems can solve complex spatial problems. While his citation count remains modest, the conceptual innovation of BMO has laid important groundwork for future research in swarm robotics and bio-inspired computing. His work exemplifies how observing nature’s subtle patterns can lead to elegant engineering solutions, making him a thoughtful contributor to the growing field of nature-inspired algorithms.
Research Focus
Key Achievements
Top Papers
- 1Butterfly Inspired Multi-robotic Swarm for Signal Source Localization3 citations · 2017