Search Results for author: Marin Kobilarov

Found 5 papers, 1 papers with code

Closed-Form Minkowski Sum Approximations for Efficient Optimization-Based Collision Avoidance

1 code implementation30 Mar 2022 James Guthrie, Marin Kobilarov, Enrique Mallada

Motion planning methods for autonomous systems based on nonlinear programming offer great flexibility in incorporating various dynamics, objectives, and constraints.

Collision Avoidance Motion Planning

Learn Proportional Derivative Controllable Latent Space from Pixels

no code implementations15 Oct 2021 Weiyao Wang, Marin Kobilarov, Gregory D. Hager

Recent advances in latent space dynamics model from pixels show promising progress in vision-based model predictive control (MPC).

Model Predictive Control

Autonomously Navigating a Surgical Tool Inside the Eye by Learning from Demonstration

no code implementations16 Nov 2020 Ji Woong Kim, Changyan He, Muller Urias, Peter Gehlbach, Gregory D. Hager, Iulian Iordachita, Marin Kobilarov

We show that the network can reliably navigate a needle surgical tool to various desired locations within 137 microns accuracy in physical experiments and 94 microns in simulation on average, and generalizes well to unseen situations such as in the presence of auxiliary surgical tools, variable eye backgrounds, and brightness conditions.

Autonomous Navigation Depth Estimation +1

Combining Neural Networks and Tree Search for Task and Motion Planning in Challenging Environments

no code implementations22 Mar 2017 Chris Paxton, Vasumathi Raman, Gregory D. Hager, Marin Kobilarov

This paper investigates the ability of neural networks to learn both LTL constraints and control policies in order to generate task plans in complex environments.


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