Deepkashi Mahajan

Post Apotheke

Papers

2

Total Citations

50

H-Index

2

About

Deepkashi Mahajan is a leading researcher in multi-robot systems and autonomous exploration, with a primary focus on urban search and rescue (USAR) operations. Her most impactful contribution is the development of a novel hybrid algorithm combining Levy Flight (LF) and Particle Swarm Optimization (PSO), known as LF-PSO, which enables efficient multi-robot exploration in unknown, communication-limited environments without GPS. This work, published in 2023, has garnered 39 citations and addresses the critical gap between simulation-based planning and real-world deployment, significantly enhancing the autonomy and coordination of rescue robots in disaster zones. Her 2025 follow-up study, with 11 citations, further validates these findings in physical environments. Mahajan’s research bridges theoretical optimization and practical robotics, offering scalable solutions for time-critical missions. Her work is widely recognized for its potential to save lives by improving the speed and reliability of robotic search teams, making her a key figure in the advancement of field robotics and swarm intelligence.

Research Focus

Key Achievements

2
H-Index
2
Papers
50
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
From Simulations to Reality: Enhancing Multi-Robot Exploration for Urban Search and Rescue
39 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Post Apotheke

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago