Hamilton-jacobi reachability: A brief overview and recent advances

S Bansal, M Chen, S Herbert… - 2017 IEEE 56th Annual …, 2017 - ieeexplore.ieee.org
Hamilton-Jacobi (HJ) reachability analysis is an important formal verification method for
guaranteeing performance and safety properties of dynamical systems; it has been applied …

A machine learning approach to visual perception of forest trails for mobile robots

A Giusti, J Guzzi, DC Cireşan, FL He… - IEEE Robotics and …, 2015 - ieeexplore.ieee.org
We study the problem of perceiving forest or mountain trails from a single monocular image
acquired from the viewpoint of a robot traveling on the trail itself. Previous literature focused …

Funnel libraries for real-time robust feedback motion planning

A Majumdar, R Tedrake - The International Journal of …, 2017 - journals.sagepub.com
We consider the problem of generating motion plans for a robot that are guaranteed to
succeed despite uncertainty in the environment, parametric model uncertainty, and …

Continuous-time trajectory optimization for online uav replanning

H Oleynikova, M Burri, Z Taylor, J Nieto… - 2016 IEEE/RSJ …, 2016 - ieeexplore.ieee.org
Multirotor unmanned aerial vehicles (UAVs) are rapidly gaining popularity for many
applications. However, safe operation in partially unknown, unstructured environments …

Survey of optimal motion planning

Y Yang, J Pan, W Wan - IET Cyber‐systems and Robotics, 2019 - Wiley Online Library
Optimal motion planning becomes more and more important these days and is critical for
motion planning algorithms developed in the academia to be applicable to real‐world …

FOSSIL: a software tool for the formal synthesis of lyapunov functions and barrier certificates using neural networks

A Abate, D Ahmed, A Edwards, M Giacobbe… - Proceedings of the 24th …, 2021 - dl.acm.org
This paper accompanies FOSSIL: a software tool for the synthesis of Lyapunov functions
and of barrier certificates (or functions) for dynamical systems modelled as differential …

Exact verification of relu neural control barrier functions

H Zhang, J Wu, Y Vorobeychik… - Advances in neural …, 2023 - proceedings.neurips.cc
Abstract Control Barrier Functions (CBFs) are a popular approach for safe control of
nonlinear systems. In CBF-based control, the desired safety properties of the system are …

Learning certified control using contraction metric

D Sun, S Jha, C Fan - conference on Robot Learning, 2021 - proceedings.mlr.press
In this paper, we solve the problem of finding a certified control policy that drives a robot from
any given initial state and under any bounded disturbance to the desired reference …

Synthesizing barrier certificates using neural networks

H Zhao, X Zeng, T Chen, Z Liu - … of the 23rd international conference on …, 2020 - dl.acm.org
This paper presents an approach of safety verification based on neural networks for
continuous dynamical systems which are modeled as a system of ordinary differential …

Automated and formal synthesis of neural barrier certificates for dynamical models

A Peruffo, D Ahmed, A Abate - … conference on tools and algorithms for the …, 2021 - Springer
We introduce an automated, formal, counterexample-based approach to synthesise Barrier
Certificates (BC) for the safety verification of continuous and hybrid dynamical models. The …