242 citations · 491 across the 52 of their papers we have counts for
10 papers · 1 filter
OA-MPC: Occlusion-Aware MPC for Guaranteed Safe Robot Navigation with Unseen Dynamic Obstacles
Roya Firoozi, Alexandre Mir, Gadi Sznaier Camps +1
For safe navigation in dynamic uncertain environments, robotic systems rely on the perception and prediction of other agents. Particularly, in occluded areas where cameras and LiDA…
Differentiable Physics Simulation of Dynamics-Augmented Neural Objects
Simon Le Cleac'h, Hong-Xing Yu, Michelle Guo +5
We present a differentiable pipeline for simulating the motion of objects that represent their geometry as a continuous density field parameterized as a deep network. This includes…
Reachable Polyhedral Marching (RPM): An Exact Analysis Tool for Deep-Learned Control Systems
Joseph A. Vincent, Mac Schwager
Neural networks are increasingly used in robotics as policies, state transition models, state estimation models, or all of the above. With these components being learned from data,…
Intention Communication and Hypothesis Likelihood in Game-Theoretic Motion Planning
Makram Chahine, Roya Firoozi, Wei Xiao +2
Game-theoretic motion planners are a potent solution for controlling systems of multiple highly interactive robots. Most existing game-theoretic planners unrealistically assume a p…
NeRF-Loc: Transformer-Based Object Localization Within Neural Radiance Fields
Jiankai Sun, Yan Xu, Mingyu Ding +5
Neural Radiance Fields (NeRFs) have become a widely-applied scene representation technique in recent years, showing advantages for robot navigation and manipulation tasks. To furth…
Learning Deep SDF Maps Online for Robot Navigation and Exploration
Gadiel Sznaier Camps, Robert Dyro, Marco Pavone +1
We propose an algorithm to (i) learn online a deep signed distance function (SDF) with a LiDAR-equipped robot to represent the 3D environment geometry, and (ii) plan collision-free…
Game-Theoretic Planning for Autonomous Driving among Risk-Aware Human Drivers
Rohan Chandra, Mingyu Wang, Mac Schwager +1
We present a novel approach for risk-aware planning with human agents in multi-agent traffic scenarios. Our approach takes into account the wide range of human driver behaviors on…
Self-Supervised Traffic Advisors: Distributed, Multi-view Traffic Prediction for Smart Cities
Jiankai Sun, Shreyas Kousik, David Fridovich-Keil +1
Connected and Autonomous Vehicles (CAVs) are becoming more widely deployed, but it is unclear how to best deploy smart infrastructure to maximize their capabilities. One key challe…
FIG-OP: Exploring Large-Scale Unknown Environments on a Fixed Time Budget
Oriana Peltzer, Amanda Bouman, Sung-Kyun Kim +8
We present a method for autonomous exploration of large-scale unknown environments under mission time constraints. We start by proposing the Frontloaded Information Gain Orienteeri…
Dojo: A Differentiable Physics Engine for Robotics
Taylor A. Howell, Simon Le Cleac'h, Jan Brüdigam +5
We present Dojo, a differentiable physics engine for robotics that prioritizes stable simulation, accurate contact physics, and differentiability with respect to states, actions, a…