Somil Bansal | DeepAI

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∙ 09/19/2023

Hamilton-Jacobi Reachability Analysis for Hybrid Systems with Controlled and Forced Transitions

Hybrid dynamical systems with non-linear dynamics are one of the most ge...

0 Javier Borquez, et al. ∙

∙ 11/04/2022

Discovering Closed-Loop Failures of Vision-Based Controllers via Reachability Analysis

Machine learning driven image-based controllers allow robotic systems to...

0 Kaustav Chakraborty, et al. ∙

∙ 10/03/2022

Online Update of Safety Assurances Using Confidence-Based Predictions

Robots such as autonomous vehicles and assistive manipulators are increa...

0 Kensuke Nakamura, et al. ∙

∙ 09/29/2022

Parameter-Conditioned Reachable Sets for Updating Safety Assurances Online

Hamilton-Jacobi (HJ) reachability analysis is a powerful tool for analyz...

0 Javier Borquez, et al. ∙

∙ 09/25/2022

Generating Formal Safety Assurances for High-Dimensional Reachability

Providing formal safety and performance guarantees for autonomous system...

0 Albert Lin, et al. ∙

∙ 01/21/2022

Computation of Regions of Attraction for Hybrid Limit Cycles Using Reachability: An Application to Walking Robots

Contact-rich robotic systems, such as legged robots and manipulators, ar...

0 Jason J. Choi, et al. ∙

∙ 02/14/2021

FaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking

Real-time, guaranteed safe trajectory planning is vital for navigation i...

0 Mo Chen, et al. ∙

∙ 11/04/2020

DeepReach: A Deep Learning Approach to High-Dimensional Reachability

Hamilton-Jacobi (HJ) reachability analysis is an important formal verifi...

0 Somil Bansal, et al. ∙

∙ 03/20/2020

Visual Navigation Among Humans with Optimal Control as a Supervisor

Real world navigation requires robots to operate in unfamiliar, dynamic ...

5 Varun Tolani, et al. ∙

∙ 12/20/2019

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

In Bansal et al. (2019), a novel visual navigation framework that combin...

20 Anjian Li, et al. ∙

∙ 10/29/2019

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

Real-world autonomous systems often employ probabilistic predictive mode...

0 Somil Bansal, et al. ∙

∙ 09/12/2019

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

Kernel-based nonparametric models have become very attractive for model-...

0 Thomas Beckers, et al. ∙

∙ 05/01/2019

An Efficient Reachability-Based Framework for Provably Safe Autonomous Navigation in Unknown Environments

Real-world autonomous vehicles often operate in a priori unknown environ...

0 Andrea Bajcsy, et al. ∙

∙ 03/06/2019

Combining Optimal Control and Learning for Visual Navigation in Novel Environments

Model-based control is a popular paradigm for robot navigation because i...

10 Somil Bansal, et al. ∙

∙ 02/27/2019

A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics

We consider the problem of extracting safe environments and controllers ...

0 Shromona Ghosh, et al. ∙

∙ 02/14/2018

Context-Specific Validation of Data-Driven Models

With an increasing use of data-driven models to control robotic systems,...

0 Somil Bansal, et al. ∙

∙ 09/10/2017

MBMF: Model-Based Priors for Model-Free Reinforcement Learning

Reinforcement Learning is divided in two main paradigms: model-free and ...

0 Somil Bansal, et al. ∙

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