Sayan Mitra

University of Illinois, Urbana-Champaign | UIUC · Department of Electrical and Computer Engineering

State estimation is a fundamental problem for monitoring and controlling systems. Engineering systems interconnect sensing and computing devices over a shared bandwidth-limited channels, and therefore, estimation algorithms should strive to use bandwidth optimally. We present a notion of entropy for state estimation of switched nonlinear dynamical...

Safety verification of embedded systems modeled as hybrid systems can be scaled up by employing simulation-guided reach set over-approximation techniques. Existing methods are either applicable to only restricted classes of systems , overly conservative, or computationally expensive. We present new techniques to compute a locally optimal bloating f...

We investigate the problem of constructing exponentially converging estimates of the state of a continuous-time system from state measurements transmitted via a limited-data-rate communication channel, so that only quantized and sampled measurements of continuous signals are available to the estimator. Following prior work on topological entropy of...

The iterative consensus problem requires a set of processes or agents with different initial values, to interact and update their states to eventually converge to a common value. Protocols solving iterative consensus serve as building blocks in a variety of systems where distributed coordination is required for load balancing, data aggregation, sen...

C2E2 is a bounded reachability analysis tool for nonlinear dynamical systems and hybrid automaton models. Previously it required users to annotate each system of differential equations of the hybrid automaton with discrepancy functions, and since these annotations are difficult to get for general nonlinear differential equations, the tool had limit...

Testing Automated Driving Systems (ADS) in simulation with realistic driving scenarios is important for verifying their performance. However, converting real-world driving videos into simulation scenarios is a significant challenge due to the complexity of interpreting high-dimensional video data and the time-consuming nature of precise manual scen...

Providing safety guarantees for autonomous systems is difficult as these systems operate in complex environments that require the use of learning-enabled components, such as deep neural networks (DNNs), for visual perception. DNNs are hard to formally verify due to their size (they can have billions of parameters), lack of formal specifications, an...

This paper addresses the problem of visual target tracking in scenarios where a pursuer may experience intermittent loss of visibility of the target. The design of a Switched Visual Tracker (SVT) is presented which aims to meet the competing requirements of maintaining both proximity and visibility. SVT alternates between a visual tracking mode for...

Large Language Models (LLMs) have shown remarkable capabilities in natural language processing, mathematical problem solving, and tasks related to program synthesis. However, their effectiveness in long-term planning and higher-order reasoning has been noted to be limited and fragile. This paper explores an approach for enhancing LLM performance in...

We extend the notion of estimation entropy of autonomous dynamical systems proposed by Liberzon and Mitra [1] to nonlinear dynamical systems with uncertain inputs with bounded variation. We call this new notion the $\epsilon$ -estimation entropy of the system and show that it lower bounds the bit rate needed for state estimation. $\epsilon$ -...

Parallel and distributed computing holds a promise of scaling verification to hard multi-agent scenarios such as the ones involving autonomous interacting vehicles. Exploiting parallelism, however, typically requires handcrafting solutions using knowledge of verification algorithms, the available hardware, and the specific models. The Ray framework...

Runtime assurance (RTA) addresses the problem of keeping an autonomous system safe while using an untrusted (or experimental) controller. This can be done via logic that explicitly switches between the untrusted controller and a safety controller, or logic that filters the input provided by the untrusted controller. While several tools implement sp...

We introduce a novel notion of perception contracts to reason about the safety of controllers that interact with an environment using neural perception. Perception contracts capture errors in ground-truth estimations that preserve invariants when systems act upon them. We develop a theory of perception contracts and design symbolic learning algorit...

We present the Verse library with the aim of making hybrid system verification more usable for multi-agent scenarios. In Verse, decision making agents move in a map and interact with each other through sensors. The decision logic for each agent is written in a subset of Python and the continuous dynamics is given by a black-box simulator. Multiple...

Runtime assurance (RTA) addresses the problem of keeping an autonomous system safe while using an untrusted (or experimental) controller. This can be done via logic that explicitly switches between the untrusted controller and a safety controller, or logic that filters the input provided by the untrusted controller. While several tools implement sp...

L_1$ adaptive control ($L_1$AC) is a control design technique that can handle a broad class of system uncertainties and provide transient performance guarantees. In this work-in-progress abstract, we discuss how existing formal verification tools can be applied to check the performance of $L_1$AC systems. We show that the theoretical transient perf...

We present the Verse library with the aim of making hybrid system verification more usable for multi-agent scenarios. In Verse, decision making agents move in a map and interact with each other through sensors. The decision logic for each agent is written in a subset of Python and the continuous dynamics is given by a black-box simulator. Multiple...

This article presents a new method for model-free verification of a general class of control systems with unknown nonlinear dynamics, where the state space has both a continuum-based and a discrete component. Specifically, we focus on finding what choices of initial states or parameters maximize a given probabilistic objective function over all cho...

A symmetry of a dynamical system is a map that transforms any trajectory to another trajectory. Abstractions have been a key building block in the theory and practice of hybrid automata analysis. We introduce a novel abstraction for hybrid automata based on the symmetries of their modes. The abstraction procedure combines different modes of a concr...

Fully formal verification of perception models is likely to remain challenging in the foreseeable future, and yet these models are being integrated into safety-critical control systems. We present a practical method for reasoning about the safety of such systems. Our method is based on systematically constructing approximations of perception models...

In 2021, the Coordinated Science Laboratory CSL, an Interdisciplinary Research Unit at the University of Illinois Urbana-Champaign, hosted the Future of Computing Symposium to celebrate its 70th anniversary. CSL's research covers the full computing stack, computing's impact on society and the resulting need for social responsibility. In this white...

Vision-based formation control systems recently have attracted attentions from both the research community and the industry for its applicability in GPS-denied environments. The safety assurance for such systems is challenging due to the lack of formal specifications for computer vision systems and the complex impact of imprecise estimations on dis...

Recent algorithms show how the availability of structural knowledge, such as symmetries, can significantly improve autonomous system verification in terms of both running time and sample complexity.

Advances in computer vision and machine learning enable robots to perceive their surroundings in powerful new ways, but these perception modules have well-known fragilities. We consider the problem of synthesizing a safe controller that is robust despite perception errors. The proposed method constructs a state estimator based on Gaussian processes...

Modern autonomous vehicle systems use complex perception and control components and must cope with uncertain data received from sensors. To estimate the probability that such vehicles remain in a safe state, developers often resort to time-consuming simulation methods. This paper presents an alternative methodology for analyzing autonomy pipelines...

We tackle the challenging problem of multi-agent cooperative motion planning for complex tasks described using signal temporal logic (STL), where robots can have nonlinear and nonholonomic dynamics. Existing methods in multi-agent motion planning, especially those based on discrete abstractions and model predictive control (MPC), suffer from limite...

We present , a tool that uses neural networks for predicting reachable sets from executions of a dynamical system. Unlike existing reachability tools, computes a reachability function that outputs an accurate over-approximation of the reachable set for any initial set in a parameterized family. Such reachability functions are useful for online moni...

We tackle the challenging problem of multi-agent cooperative motion planning for complex tasks described using signal temporal logic (STL), where robots can have nonlinear and nonholonomic dynamics. Existing methods in multi-agent motion planning, especially those based on discrete abstractions and model predictive control (MPC), suffer from limite...

Tor has millions of daily users seeking privacy while browsing the Internet. It has thousands of relays to route users’ packets while anonymizing their sources and destinations. Users choose relays to forward their traffic according to probability distributions published by the Tor authorities . The authorities generate these probability distributi...

Statistical model checking is a class of sequential algorithms that can verify specifications of interest on an ensemble of cyber-physical systems (e.g., whether 99% of cars from a batch meet a requirement on their energy efficiency). These algorithms infer the probability that given specifications are satisfied by the systems with provable statist...

Convolutional Neural Networks (CNN) for object detection, lane detection, and segmentation now sit at the head of most autonomy pipelines, and yet, their safety analysis remains an important challenge. Formal analysis of perception models is fundamentally difficult because their correctness is hard if not impossible to specify. We present a techniq...

The key concept for safe and efficient traffic management for Unmanned Aircraft Systems (UAS) is the notion of operation volume (OV). An OV is a 4-dimensional block of airspace and time, which can express an aircraft's intent, and can be used for planning, de-confliction, and traffic management. While there are several high-level simulators for UAS...

We present $$\mathsf {SceneChecker}$$ SceneChecker , a tool for verifying scenarios involving vehicles executing complex plans in large cluttered workspaces. $$\mathsf {SceneChecker}$$ SceneChecker converts the scenario verification problem to a standard hybrid system verification problem, and solves it effectively by exploiting structural properti...

We address the problem of synthesizing provably correct controllers for linear systems with reach-avoid specifications. Discrete abstraction-based controller synthesis techniques have been developed for linear and nonlinear systems with various types of specifications. However, these methods typically suffer from the state space explosion problem....

Motion planning in dynamic and partially unknown environments is a difficult problem requiring both perception and control components. We propose a solution to the control component while cleanly abstracting perception. We show that this clean abstraction can be used to synthesize verifiably safe reference trajectories using a combination of reacha...

Finding the minimal bit rate needed to estimate the state of a dynamical system is a fundamental problem. Several notions of topological entropy have been proposed to solve this problem for closed and switched systems. In this paper, we extend these notions to open nonlinear dynamical systems with slowly-varying inputs to lower bound the bit rate n...

We present a Symmetry-based abstraction refinement algorithm SymAR that is directed towards safety verification of large-scale scenarios with complex dynamical systems. The abstraction maps modes with symmetric dynamics to a single abstract mode and refinements recursively split the modes when safety checks fail. We show how symmetry abstractions c...

A robot’s code needs to sense the environment, control the hardware, and communicate with other robots. Current programming languages do not provide suitable abstractions that are independent of hardware platforms. Currently, developing robot applications requires detailed knowledge of signal processing, control, path planning, network protocols, a...

User guide for the hybrid system verification tool C2E2. Provides a GUI for model creation and editing, simulation-driven verification for linear and nonlinear hybrid systems, command-line operations, and a plotter.

Unmanned Aircraft Systems (UAS) are being increasingly used in delivery, infrastructure surveillance, fire-fighting, and agriculture. According to the Federal Aviation Administration (FAA), the number of active small commercial unmanned aircraft is going to grow from 385K in 2019 to 828K by 2024. UAS traffic management (UTM) system for low-altitude...

We address the problem of synthesizing a controller for non-linear systems with reach-avoid requirements. Our controller consists of a reference trajectory and a tracking controller which drives the actual trajectory to follow the reference trajectory. We identify a type of reference trajectory such that the tracking error between the actual trajec...

We address the problem of synthesizing a controller for nonlinear systems with reach-avoid requirements. Our controller consists of a reference controller and a tracking controller which drives the actual trajectory to follow the reference trajectory. We identify a type of reference trajectory such that the tracking error between the actual traject...

As autonomous systems begin to operate amongst humans, methods for safe interaction must be investigated. We consider an example of a small autonomous vehicle in a pedestrian zone that must safely maneuver around people in a free-form fashion. We investigate two key questions: How can we effectively integrate pedestrian intent estimation into our a...

A symmetry of a dynamical system is a map that transforms one trajectory to another trajectory. We introduce a new type of abstraction for hybrid automata based on symmetries. The abstraction combines different modes in a concrete automaton A, whose trajectories are related by symmetries, into a single mode in the abstract automaton B. The abstract...

Programming languages, libraries, and development tools have transformed the application development processes for mobile computing and machine learning. This paper introduces CyPhyHouse-a toolchain that aims to provide similar programming, debugging, and deployment benefits for distributed mobile robotic applications. Users can develop hardware-ag...

We show that symmetry transformations and caching can enable scalable, and possibly unbounded, verification of multi-agent systems. Symmetry transformations map any solution of the system to another solution. We show that this property can be used to transform cached reachsets to compute new reachsets, for hybrid and multi-agent models. We develop...

We study the differential privacy of sequential statistical inference and learning algorithms that are characterized by random termination time. Using the two examples: sequential probability ratio test and sequential empirical risk minimization, we show that the number of steps such algorithms execute before termination can jeopardize the differen...

We explore application of multi-armed bandit algorithms to statistical model checking (SMC) of Markov chains initialized to a set of states. We observe that model checking problems requiring maximization of probabilities of sets of execution over all choices of the initial states, can be formulated as a multi-armed bandit problem, for appropriate c...

We show that symmetry transformations and caching can enable scalable, and possibly unbounded, verification of multi-agent systems. Symmetry transformations map solutions and to other solutions. We show that this property can be used to transform cached reachsets to compute new reachsets, for hybrid and multi-agent models. We develop a notion of vi...

Input/Output Automata (IOA) is an expressive specification framework with built-in properties for compositional reasoning. It has been shown to be effective in specifying and analyzing distributed and networked systems. The available verification engines for IOA are based on interactive theorem provers such as Isabelle, Larch, PVS, and Coq, and are...

As autonomous systems begin to operate amongst humans, methods for safe interaction must be investigated. We consider an example of a small autonomous vehicle in a pedestrian zone that must safely maneuver around people in a free-form fashion. We investigate two key questions: How can we effectively integrate pedestrian intent estimation into our a...

Programming languages, libraries, and development tools have transformed the application development processes for mobile computing and machine learning. This paper introduces the CyPhyHouse - a toolchain that aims to provide similar programming, debugging, and deployment benefits for distributed mobile robotic applications. Users can develop hardw...

Programming languages, libraries, and development tools have transformed the application development processes for mobile computing and machine learning. This paper introduces the CyPhyHouse-a toolchain that aims to provide similar programming, debugging, and deployment benefits for distributed mobile robotic applications. Users can develop hardwar...

In this paper, we investigate how symmetry transformations of equivariant dynamical systems can reduce the computation effort for safety verification. Symmetry transformations of equivariant systems map solutions to other solutions. We build upon this result, producing reachsets from other previously computed reachsets. We augment the standard simu...

Input/Output Automata (IOA) is an expressive specification framework with built-in properties for compositional reasoning. It has been shown to be effective in specifying and analyzing distributed and networked systems. The available verification engines for IOA are based on interactive theorem provers such as Isabelle, Larch, PVS, and Coq, and are...

Data-driven verification methods utilize execution data together with models for establishing safety requirements. These are often the only tools available for analyzing complex, nonlinear cyber-physical systems, for which purely model-based analysis is currently infeasible. In this chapter, we outline the key concepts and algorithmic approaches fo...

We study the problem of load-balancing in path selection in anonymous networks such as Tor. We first find that the current Tor path selection strategy can create significant imbalances. We then develop a (locally) optimal algorithm for selecting paths and show, using flow-level simulation, that it results in much better balancing of load across the...

Typically platform specific programming models for distributed Cyber-Physical Systems provide limited portability, code reuse, rigorous verification, and synthesis. Koord is a new distributed CPS programming model and language, which treats the platform-independent decision and coordination tasks as a separate concern from platform-dependent concer...

We address the problem of synthesizing provably correct controllers for linear systems with reach-avoid specifications. Our solution uses a combination of an open-loop controller and a tracking controller, thereby reducing the problem to smaller tractable problems. We show that, once a tracking controller is fixed, the reachable states from an init...

We present a new partial order reduction method for reachability analysis of nondeterministic labeled transition systems over metric spaces. Nondeterminism arises from both the choice of the initial state and the choice of actions, and the number of executions to be explored grows exponentially with their length. We introduce a notion of \(\varepsi...