Himani Sinhmar

Himani Sinhmar

Postdoctoral Research Associate  ·  Princeton University

I develop control and decision-making frameworks for resource-constrained robots operating in dynamic, uncertain, and crowded environments.

I am a Postdoctoral Research Associate at Princeton University working on robotics, control theory, neuromorphic decision-making, and game theory. I study how robots can make fast, reliable decisions and coordinate in challenging real-world environments using only local sensing and minimal onboard resources. My work develops decentralized frameworks for multi-agent systems that operate without GPS, WiFi, explicit communication, or centralized coordination. Instead of relying on long-horizon optimization or repeated replanning, I am interested in continuous adaptation through dynamical interaction rules, where safe and coordinated collective behavior emerges online from local information. More broadly, my research explores how these mechanisms can support scalable environment monitoring and autonomous operation in the wild.

Research · connected projects
Origami MetaBot,Bio-inspired Robotics Origami MetaBot Swarm Encapsulation,Swarm Intelligence Swarm Control UAV Motion Planning,Safe Control UAV Planning Consensus under Sensor Bias,Multi-Agent Systems Consensus & Bias Task & Motion Planning,Formal Methods Task & Motion Spacecraft Rendezvous,Safe Control Spacecraft Nav
Swarm Intelligence Safe Control Formal Methods Bio-inspired Hover to explore · Click to read

I am currently working with Prof. Naomi Leonard at Princeton. I did my PhD at Cornell University with Prof. Hadas Kress-Gazit, and my Bachelor's and Master's in Aerospace Engineering at IIT Bombay. I have also collaborated with the Cohen Group and Laboratory for Molecular Engineering on autonomous micron-scale origami robots.

Outside of work I run, hike, and read — mostly about world affairs, human psychology, and philosophy of science.

My research asks a common question across scales and platforms: how can robots make fast, reliable, and provably safe decisions when sensing, computation, communication, or actuation are limited? I approach this through tools from control theory, nonlinear dynamics, and collective intelligence, with an emphasis on decentralized algorithms that remain both mathematically analyzable and practically deployable. Research statement →

2024
Practical and Safe Navigation Function Based Motion Planning of UAVs
Himani Sinhmar, Marcus Greiff, Stefano Di Cairano
International Conference on Robotics and Automation (ICRA 2024)
Multi-Source Encapsulation With Guaranteed Convergence Using Minimalist Robots
Himani Sinhmar, Hadas Kress-Gazit
Distributed Autonomous Robotic Systems (DARS 2024)
Microscopic, continuum, compliant, and electronically configurable metasheet robots
Qingkun Liu*, Wei Wang*, Himani Sinhmar, Itay Griniasty, Jason Z. Kim, et al.
Nature Materials, 2024
Design and Control of Microscopic Robot Sheet
Himani Sinhmar, Itay Griniasty, Qingkun Liu, Wei Wang, Itai Cohen, Hadas Kress-Gazit
ICRA 2024 Workshop
Motion Planning and Control with Multi-Stage Construction of Invariant Sets
Marcus Greiff, Stefano Di Cairano, Himani Sinhmar
US Patent, Pending,Filed March 2024
2023
Guaranteed Encapsulation of Targets with Unknown Motion by a Minimalist Robotic Swarm
Himani Sinhmar, Hadas Kress-Gazit
IEEE Transactions on Robotics (TRO), 2023
2022
Decentralized Control of Minimalistic Robotic Swarms For Guaranteed Target Encapsulation
Himani Sinhmar, Hadas Kress-Gazit
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)
Consensus of networked double integrator systems under sensor bias
Pallavi Sinha, Srikant Sukumar, Himani Sinhmar
International Journal of Adaptive Control and Signal Processing, November 2022
Earlier
Distributed model independent algorithm for spacecraft synchronization under relative measurement bias
Himani Sinhmar, Srikant Sukumar
5th CEAS Conference on Guidance, Navigation and Control
Relative Autonomous Navigation Without Communication Between Spacecraft Using Line of Sight Measurements
Himani Sinhmar, Vinod Kumar
8th IEEE/CSAA GNC Conference, Xiamen, China, 2018
Direct Theoretical Approach to Jet Propulsion Principles based on Pressure Variation inside the Engine
Himani Sinhmar, Pallavi Rastogi, Shripad P. Mahulikar