84 citations · 420 across the 48 of their papers we have counts for
5 papers · 2 filters
Deep Forward and Inverse Perceptual Models for Tracking and Prediction
Alexander Lambert, Amirreza Shaban, Amit Raj +2
We consider the problems of learning forward models that map state to high-dimensional images and inverse models that map high-dimensional images to state in robotics. Specifically…
Agile Autonomous Driving using End-to-End Deep Imitation Learning
Yunpeng Pan, Ching-An Cheng, Kamil Saigol +4
We present an end-to-end imitation learning system for agile, off-road autonomous driving using only low-cost sensors. By imitating a model predictive controller equipped with adva…
Continuous-Time Gaussian Process Motion Planning via Probabilistic Inference
Mustafa Mukadam, Jing Dong, Xinyan Yan +2
We introduce a novel formulation of motion planning, for continuous-time trajectories, as probabilistic inference. We first show how smooth continuous-time trajectories can be repr…
Sparse Gaussian Processes for Continuous-Time Trajectory Estimation on Matrix Lie Groups
Jing Dong, Byron Boots, Frank Dellaert
Continuous-time trajectory representations are a powerful tool that can be used to address several issues in many practical simultaneous localization and mapping (SLAM) scenarios,…
Approximately Optimal Continuous-Time Motion Planning and Control via Probabilistic Inference
Mustafa Mukadam, Ching-An Cheng, Xinyan Yan +1
The problem of optimal motion planing and control is fundamental in robotics. However, this problem is intractable for continuous-time stochastic systems in general and the solutio…