Aalok Patwardhan

Imperial College London

Papers

2

Total Citations

54

H-Index

2

About

Aalok Patwardhan is a leading researcher in distributed multi-robot systems, with a primary focus on scalable coordination, collaborative planning, and decentralized decision-making. His most impactful contribution is the development of **Gaussian Belief Propagation (GBP) Planning**, a novel distributed framework that enables precise, safe, and efficient motion coordination for large robot teams operating in tight spaces—without requiring centralised control. This work, published in 2022, has already garnered **48 citations**, highlighting its significance in overcoming a major scalability bottleneck in multi-robot planning. Patwardhan’s research uniquely integrates local obstacle avoidance, global goal coordination, and collaborative mapping into a unified distributed framework, as demonstrated in his 2024 work on exploration and information acquisition. By solving these traditionally separate problems within a single consensus-driven architecture, he is advancing the practical deployment of robot swarms in real-world applications such as warehouse logistics, search-and-rescue, and environmental monitoring. His work stands out for its theoretical rigor and direct applicability, making him a rising figure in distributed robotics and multi-agent systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
54
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Distributing Collaborative Multi-Robot Planning With Gaussian Belief Propagation
48 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Imperial College London

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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