5 papers
Uncertainty Guided Exploratory Trajectory Optimization for Sampling-Based Model Predictive Control
O. Goktug Poyrazoglu, Yukang Cao, Rahul Moorthy +1
Trajectory optimization depends heavily on initialization. In particular, sampling-based approaches are highly sensitive to initial solutions, and limited exploration frequently le…
Fast Navigation Through Occluded Spaces via Language-Conditioned Map Prediction
Rahul Moorthy Mahesh, Oguzhan Goktug Poyrazoglu, Yukang Cao +1
In cluttered environments, motion planners often face a trade-off between safety and speed due to uncertainty caused by occlusions and limited sensor range. In this work, we invest…
C-Free-Uniform: A Map-Conditioned Trajectory Sampler for Model Predictive Path Integral Control
Yukang Cao, Rahul Moorthy, O. Goktug Poyrazoglu +1
Trajectory sampling is a key component of sampling-based control mechanisms. Trajectory samplers rely on control input samplers, which generate control inputs u from a distribution…
An Unsupervised C-Uniform Trajectory Sampler with Applications to Model Predictive Path Integral Control
O. Goktug Poyrazoglu, Rahul Moorthy, Yukang Cao +2
Sampling-based model predictive controllers generate trajectories by sampling control inputs from a fixed, simple distribution such as the normal or uniform distributions. This sam…
C-Uniform Trajectory Sampling For Fast Motion Planning
O. Goktug Poyrazoglu, Yukang Cao, Volkan Isler
We study the problem of sampling robot trajectories and introduce the notion of C-Uniformity. As opposed to the standard method of uniformly sampling control inputs (which lead to…