160 citations · 403 across the 56 of their papers we have counts for
13 papers · 1 filter
One Filter to Deploy Them All: Robust Safety for Quadrupedal Navigation in Unknown Environments
Albert Lin, Shuang Peng, Somil Bansal
As learning-based methods for legged robots rapidly grow in popularity, it is important that we can provide safety assurances efficiently across different controllers and environme…
Linear Supervision for Nonlinear, High-Dimensional Neural Control and Differential Games
William Sharpless, Zeyuan Feng, Somil Bansal +1
As the dimension of a system increases, traditional methods for control and differential games rapidly become intractable, making the design of safe autonomous agents challenging i…
Enhancing Safety and Robustness of Vision-Based Controllers via Reachability Analysis
Kaustav Chakraborty, Aryaman Gupta, Somil Bansal
Autonomous systems, such as self-driving cars and drones, have made significant strides in recent years by leveraging visual inputs and machine learning for decision-making and con…
Reachability Analysis for Black-Box Dynamical Systems
Vamsi Krishna Chilakamarri, Zeyuan Feng, Somil Bansal
Hamilton-Jacobi (HJ) reachability analysis is a powerful framework for ensuring safety and performance in autonomous systems. However, existing methods typically rely on a white-bo…
System-Level Safety Monitoring and Recovery for Perception Failures in Autonomous Vehicles
Kaustav Chakraborty, Zeyuan Feng, Sushant Veer +4
The safety-critical nature of autonomous vehicle (AV) operation necessitates development of task-relevant algorithms that can reason about safety at the system level and not just a…
Updating Robot Safety Representations Online from Natural Language Feedback
Leonardo Santos, Zirui Li, Lasse Peters +2
Robots must operate safely when deployed in novel and human-centered environments, like homes. Current safe control approaches typically assume that the safety constraints are know…
Gait Switching and Enhanced Stabilization of Walking Robots with Deep Learning-based Reachability: A Case Study on Two-link Walker
Xingpeng Xia, Jason J. Choi, Ayush Agrawal +3
Learning-based approaches have recently shown notable success in legged locomotion. However, these approaches often lack accountability, necessitating empirical tests to determine…
Cooptimizing Safety and Performance with a Control-Constrained Formulation
Hao Wang, Adityaya Dhande, Somil Bansal
Autonomous systems have witnessed a rapid increase in their capabilities, but it remains a challenge for them to perform tasks both effectively and safely. The fact that performanc…
Stable-BC: Controlling Covariate Shift with Stable Behavior Cloning
Shaunak A. Mehta, Yusuf Umut Ciftci, Balamurugan Ramachandran +2
Behavior cloning is a common imitation learning paradigm. Under behavior cloning the robot collects expert demonstrations, and then trains a policy to match the actions taken by th…
Parameterized Fast and Safe Tracking (FaSTrack) using Deepreach
Hyun Joe Jeong, Zheng Gong, Somil Bansal +1
Fast and Safe Tracking (FaSTrack) is a modular framework that provides safety guarantees while planning and executing trajectories in real time via value functions of Hamilton-Jaco…
SAFE-GIL: SAFEty Guided Imitation Learning for Robotic Systems
Yusuf Umut Ciftci, Darren Chiu, Zeyuan Feng +2
Behavior cloning (BC) is a widely-used approach in imitation learning, where a robot learns a control policy by observing an expert supervisor. However, the learned policy can make…
Exact Imposition of Safety Boundary Conditions in Neural Reachable Tubes
Aditya Singh, Zeyuan Feng, Somil Bansal
Hamilton-Jacobi (HJ) reachability analysis is a widely adopted verification tool to provide safety and performance guarantees for autonomous systems. However, it involves solving a…
Providing Safety Assurances for Systems with Unknown Dynamics
Hao Wang, Javier Borquez, Somil Bansal
As autonomous systems become more complex and integral in our society, the need to accurately model and safely control these systems has increased significantly. In the past decade…