160 citations · 403 across the 56 of their papers we have counts for
13 papers · 1 filter
Context-Conditioned Hamilton-Jacobi Reachability for Adaptive Safety Filtering
Ali Fuat Sahin, Yunus Yazoglu, John Talbot +3
Hamilton-Jacobi reachability constructs safety certificates for specified dynamics and safety constraints, tying each certificate to the deployment context for which it is synthesi…
DualGuard MPPI: Safe and Performant Optimal Control by Combining Sampling-Based MPC and Hamilton-Jacobi Reachability
Javier Borquez, Luke Raus, Yusuf Umut Ciftci +1
Designing controllers that are both safe and performant is inherently challenging. This co-optimization can be formulated as a constrained optimal control problem, where the cost f…
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…
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…
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…
Reachability-Based Safety Guarantees using Efficient Initializations
Sylvia L. Herbert, Shromona Ghosh, Somil Bansal +1
Hamilton-Jacobi-Isaacs (HJI) reachability analysis is a powerful tool for analyzing the safety of autonomous systems. This analysis is computationally intensive and typically perfo…
Context-Specific Validation of Data-Driven Models
Somil Bansal, Shromona Ghosh, Alberto Sangiovanni-Vincentelli +2
With an increasing use of data-driven models to control robotic systems, it has become important to develop a methodology for validating such models before they can be deployed to…
Safe and Resilient Multi-vehicle Trajectory Planning Under Adversarial Intruder
Somil Bansal, Mo Chen, Claire J. Tomlin
Provably safe and scalable multi-vehicle trajectory planning is an important and urgent problem. Hamilton-Jacobi (HJ) reachability is an ideal tool for analyzing such safety-critic…
Hamilton-Jacobi Reachability: A Brief Overview and Recent Advances
Somil Bansal, Mo Chen, Sylvia Herbert +1
Hamilton-Jacobi (HJ) reachability analysis is an important formal verification method for guaranteeing performance and safety properties of dynamical systems; it has been applied t…
Provably Safe and Robust Drone Routing via Sequential Path Planning: A Case Study in San Francisco and the Bay Area
Mo Chen, Somil Bansal, Ken Tanabe +1
Provably safe and scalable multi-vehicle path planning is an important and urgent problem due to the expected increase of automation in civilian airspace in the near future. Hamilt…
Goal-Driven Dynamics Learning via Bayesian Optimization
Somil Bansal, Roberto Calandra, Ted Xiao +2
Real-world robots are becoming increasingly complex and commonly act in poorly understood environments where it is extremely challenging to model or learn their true dynamics. Ther…
Learning Quadrotor Dynamics Using Neural Network for Flight Control
Somil Bansal, Anayo K. Akametalu, Frank J. Jiang +2
Traditional learning approaches proposed for controlling quadrotors or helicopters have focused on improving performance for specific trajectories by iteratively improving upon a n…
Plug-and-Play Model Predictive Control for Load Shaping and Voltage Control in Smart Grids
Caroline Le Floch, Somil Bansal, Claire J. Tomlin +2
This paper presents a predictive controller for handling plug-and-play (P&P) charging requests of flexible loads in a distribution system. We define two types of flexible loads: (i…