31 citations · 103 across the 16 of their papers we have counts for
6 papers · 1 filter
NeuralSim: Augmenting Differentiable Simulators with Neural Networks
Eric Heiden, David Millard, Erwin Coumans +2
Differentiable simulators provide an avenue for closing the sim-to-real gap by enabling the use of efficient, gradient-based optimization algorithms to find the simulation paramete…
Augmenting Differentiable Simulators with Neural Networks to Close the Sim2Real Gap
Eric Heiden, David Millard, Erwin Coumans +1
We present a differentiable simulation architecture for articulated rigid-body dynamics that enables the augmentation of analytical models with neural networks at any point of the…
Confidence-rich grid mapping
Ali-akbar Agha-mohammadi, Eric Heiden, Karol Hausman +1
Representing the environment is a fundamental task in enabling robots to act autonomously in unknown environments. In this work, we present confidence-rich mapping (CRM), a new alg…
Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots
Eric Heiden, Luigi Palmieri, Kai O. Arras +2
Planning smooth and energy-efficient motions for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics. Ove…
LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments
Kamak Ebadi, Yun Chang, Matteo Palieri +9
Simultaneous Localization and Mapping (SLAM) in large-scale, unknown, and complex subterranean environments is a challenging problem. Sensors must operate in off-nominal conditions…
Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics
David Millard, Eric Heiden, Shubham Agrawal +1
A key ingredient to achieving intelligent behavior is physical understanding that equips robots with the ability to reason about the effects of their actions in a dynamic environme…