Papers
12
Total Citations
242
H-Index
6
About
Asher Elmquist is a leading researcher at the intersection of robotics simulation, autonomous vehicle development, and high-fidelity perception modeling. His work has fundamentally shaped how researchers and engineers validate autonomous systems before real-world deployment. His most influential contribution, "On the use of simulation in robotics" (157 citations), provides a critical framework for understanding simulation's role in developing smart robots that operate in dynamic, unstructured environments. Elmquist has pioneered sensor simulation frameworks that enable closed-loop testing of autonomous vehicles and planetary exploration robots, with his work on camera modeling for autonomous vehicles and the IRIS perception simulator for planetary missions demonstrating particular impact. He developed PyChrono and gym-chrono, a deep reinforcement learning framework that leverages multibody dynamics for controlling autonomous vehicles and robots. At NASA's Jet Propulsion Laboratory, Elmquist created Dshell-DARTS, a reusability-focused multi-mission simulation toolkit, and EELS-DARTS, a specialized simulator for planetary snake robots. His SynChrono platform enables scalable testing of groups of interacting autonomous vehicles. Through his open-source, containerized software frameworks, Elmquist has made high-fidelity simulation accessible to the broader robotics community, accelerating the development of safer, more capable autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2Modeling Cameras for Autonomous Vehicle and Robot Simulation: An Overview17 citations · 2021
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