Esha D. Nerurkar

About

Esha D. Nerurkar is a leading researcher in multi-robot systems, with a primary focus on cooperative localization (CL) under severe communication and computational constraints. Her work addresses a fundamental challenge: how can teams of robots accurately estimate their positions when bandwidth, processing power, and communication reliability are limited? Her most influential contribution is a distributed Maximum A Posteriori (MAP) estimator for multi-robot CL, which reduces memory and processing demands by distributing data across robots—a paper that has garnered 226 citations. She further advanced the field with a Covariance Intersection (CI)-based algorithm that dramatically lowers processing and communication complexity for teams of N robots, cited 173 times. Nerurkar also pioneered frameworks for asynchronous and intermittently disconnected communication networks, and developed hybrid estimation methods that operate under extreme constraints, such as when robots can transmit only a single bit per measurement. Her work is essential reading for anyone working on decentralized robotics, sensor networks, or autonomous systems operating in bandwidth-limited environments.

Research Focus

Key Achievements

Top Papers

1. 1
   Distributed maximum a posteriori estimation for multi-robot cooperative localization

   226 citations · 2009
2. 2
   Decentralized multi-robot cooperative localization using covariance intersection

   173 citations · 2013
3. 3
   Asynchronous Multi-Centralized Cooperative Localization

   31 citations · 2010
4. 4
   A hybrid estimation framework for Cooperative Localization under communication constraints

   22 citations · 2011
5. 5
   A communication-bandwidth-aware hybrid estimation framework for multi-robot cooperative localization

   16 citations · 2013
6. 6
   A hybrid estimation framework for cooperative localization under communication constraints

   2 citations · 2011

Key Collaborators

Contact & Links