activity
20112024
most citedFaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking

80 citations · 167 across the 23 of their papers we have counts for

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Showing 2019Show all

12 papers · 1 filter

cs.RO2019

Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability

Anjian Li, Somil Bansal, Georgios Giovanis +3

In Bansal et al. (2019), a novel visual navigation framework that combines learning-based and model-based approaches has been proposed. Specifically, a Convolutional Neural Network…

cs.RO2019

Design of the First Insect-scale Spinning-wing Robot

Palak Bhushan, Claire Tomlin

Here we present the design of an insect-scale microrobot that generates lift by spinning its wings. This is in contrast to most other microrobot designs at this size scale which re…

cs.RO2019

A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning

Somil Bansal, Andrea Bajcsy, Ellis Ratner +2

Real-world autonomous systems often employ probabilistic predictive models of human behavior during planning to reason about their future motion. Since accurately modeling human be…

math.OC2019

Feedback Linearization for Unknown Systems via Reinforcement Learning

Tyler Westenbroek, David Fridovich-Keil, Eric Mazumdar +4

We present a novel approach to control design for nonlinear systems which leverages model-free policy optimization techniques to learn a linearizing controller for a physical plant…

eess.SY2019

An Iterative Quadratic Method for General-Sum Differential Games with Feedback Linearizable Dynamics

David Fridovich-Keil, Vicenc Rubies-Royo, Claire J. Tomlin

Iterative linear-quadratic (ILQ) methods are widely used in the nonlinear optimal control community. Recent work has applied similar methodology in the setting of multiplayer gener…

eess.SY2019

Closed-loop Model Selection for Kernel-based Models using Bayesian Optimization

Thomas Beckers, Somil Bansal, Claire J. Tomlin +1

Kernel-based nonparametric models have become very attractive for model-based control approaches for nonlinear systems. However, the selection of the kernel and its hyperparameters…