52 citations · 201 across the 50 of their papers we have counts for
6 papers · 1 filter
Risk-Bounded Control with Kalman Filtering and Stochastic Barrier Functions
Shakiba Yaghoubi, Georgios Fainekos, Tomoya Yamaguchi +2
In this paper, we study Stochastic Control Barrier Functions (SCBFs) to enable the design of probabilistic safe real-time controllers in presence of uncertainties and based on nois…
PerceMon: Online Monitoring for Perception Systems
Anand Balakrishnan, Jyotirmoy Deshmukh, Bardh Hoxha +2
Perception algorithms in autonomous vehicles are vital for the vehicle to understand the semantics of its surroundings, including detection and tracking of objects in the environme…
Neural Network Repair with Reachability Analysis
Xiaodong Yang, Tom Yamaguchi, Hoang-Dung Tran +3
Safety is a critical concern for the next generation of autonomy that is likely to rely heavily on deep neural networks for perception and control. Formally verifying the safety an…
Reachability Analysis of Convolutional Neural Networks
Xiaodong Yang, Tomoya Yamaguchi, Hoang-Dung Tran +3
Deep convolutional neural networks have been widely employed as an effective technique to handle complex and practical problems. However, one of the fundamental problems is the lac…
Safe Navigation in Human Occupied Environments Using Sampling and Control Barrier Functions
Keyvan Majd, Shakiba Yaghoubi, Tomoya Yamaguchi +3
Sampling-based methods such as Rapidly-exploring Random Trees (RRTs) have been widely used for generating motion paths for autonomous mobile systems. In this work, we extend time-b…
Discovering IoT Physical Channel Vulnerabilities
Muslum Ozgur Ozmen, Xuansong Li, Andrew Chu +3
Smart homes contain diverse sensors and actuators controlled by IoT apps that provide custom automation. Prior works showed that an adversary could exploit physical interaction vul…