no code implementations • 18 Feb 2024 • Inigo Incer, Noel Csomay-Shanklin, Aaron Ames, Richard M. Murray
We consider the problem of reasoning about networked and layered control systems using assume-guarantee specifications.
no code implementations • 7 Apr 2023 • Prithvi Akella, Apurva Badithela, Richard M. Murray, Aaron D. Ames
By filtering control inputs to maintain the positivity of this function, we ensure that the system trajectory satisfies the desired STL specification.
no code implementations • 12 Aug 2022 • SooJean Han, Michelle Effros, Richard M. Murray
Towards the informed design of large-scale distributed data-gathering architectures under real-world assumptions such as nonzero communication delays and unknown environment dynamics, this paper considers the effects of allowing feedback communication from the central processor to external sensors.
1 code implementation • 6 Apr 2022 • Josefine Graebener, Apurva Badithela, Richard M. Murray
We present a framework for merging unit tests for autonomous systems.
no code implementations • 15 Jan 2022 • Ersin Daş, Richard M. Murray
A high-gain input observer method is adapted to estimate the time-varying unmodelled dynamics of the CBF with an error bound using the first-order time derivative of the CBF.
no code implementations • 9 Sep 2021 • Mohamadreza Ahmadi, Ugo Rosolia, Michel D. Ingham, Richard M. Murray, Aaron D. Ames
In this paper, we consider the problem of designing policies for MDPs and POMDPs with objectives and constraints in terms of dynamic coherent risk measures, which we refer to as the constrained risk-averse problem.
no code implementations • 12 Aug 2021 • Apurva Badithela, Richard M. Murray
We an algorithm, based on network flows, for synthesizing a test graph by restricting transitions, represented by edge deletions, on the original graph induced by the Kripke structures.
no code implementations • 16 May 2021 • Apurva Badithela, Tichakorn Wongpiromsarn, Richard M. Murray
In many autonomy applications, performance of perception algorithms is important for effective planning and control.
no code implementations • 24 Mar 2021 • Josefine Graebener, Tung Phan-Minh, Jiaqi Yan, Qiming Zhao, Richard M. Murray
Increased complexity in cyber-physical systems calls for modular system design methodologies that guarantee correct and reliable behavior, both in normal operations and in the presence of failures.
no code implementations • 4 Dec 2020 • Mohamadreza Ahmadi, Ugo Rosolia, Michel D. Ingham, Richard M. Murray, Aaron D. Ames
We consider the problem of designing policies for Markov decision processes (MDPs) with dynamic coherent risk objectives and constraints.
1 code implementation • 20 Jan 2020 • Yuxiao Chen, Sumanth Dathathri, Tung Phan-Minh, Richard M. Murray
There is a growing interest in building autonomous systems that interact with complex environments.
1 code implementation • 10 Dec 2019 • Francesca Baldini, Animashree Anandkumar, Richard M. Murray
In this work, we propose a new learning approach for autonomous navigation and landing of an Unmanned-Aerial-Vehicle (UAV).
no code implementations • 27 Sep 2019 • Mohamadreza Ahmadi, Masahiro Ono, Michel D. Ingham, Richard M. Murray, Aaron D. Ames
We consider the problem of designing policies for partially observable Markov decision processes (POMDPs) with dynamic coherent risk objectives.
1 code implementation • 21 Mar 2019 • Richard Cheng, Gabor Orosz, Richard M. Murray, Joel W. Burdick
Reinforcement Learning (RL) algorithms have found limited success beyond simulated applications, and one main reason is the absence of safety guarantees during the learning process.
1 code implementation • 11 Mar 2018 • Sumanth Dathathri, Stephan Zheng, Tianwei Yin, Richard M. Murray, Yisong Yue
Deep neural networks are vulnerable to adversarial examples, which dramatically alter model output using small input changes.
1 code implementation • 11 Aug 2015 • Ioannis Filippidis, Richard M. Murray
This work proposes a symbolic algorithm for the construction of assume-guarantee specifications that allow multiple agents to cooperate.
Logic in Computer Science Systems and Control