## About

190

Publications

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Introduction

Sayan Mitra currently works at the Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign. He is affiliated with the Department of Computer Science, the Coordinated Science Lab, and Information Trust Institute. Sayan does research in formal methods, distributed computing, verification, cyber-physical systems, security and privacy of control systems, entropy and estimation. One current project is 'Entropy, Control, and Verification', 'CyPhyHouse for rapid prototyping distributed robotic applications', 'Verification of autonomous vehicles'.

Additional affiliations

August 2007 - August 2008

January 2005 - present

July 1998 - August 1998

Education

September 2001 - August 2007

August 1999 - March 2001

## Publications

Publications (190)

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...

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...

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...

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...

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. Our solution decomposes the overall synthesis problem into two smaller, and more tractable problems: one synthesis problem for an open-loop controller which can produce a reference trajectory, and a second for synthesizing a track...

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...

Automated vulnerability assessment and exploit generation for computing systems have been explored for decades. However, these approaches are incomplete in assessing industrial control systems, where networks of computing devices and physical processes interact for safety-critical missions. We present an attack synthesis algorithm against such cybe...

Finding the minimal bit rate needed for state estimation of a dynamical system is a fundamental problem in control theory. We present two notions of topological entropy, one to lower bound the bit rate needed to estimate the state of a nonlinear dynamical system, with unknown bounded inputs, up to a constant error ϵ. The other is to do the sa...

Finding the minimal bit rate needed for state estimation of a dynamical system is a fundamental problem in control theory. In this paper, we present a notion of topological entropy, to lower bound the bit rate needed to estimate the state of a nonlinear dynamical system, with unknown bounded inputs, up to a constant error ϵ. Since the actual...

We present a demo of DryVR 2.0, a framework for verification and controller synthesis of cyber-physical systems composed of black-box simulators and white-box automata. For verification, DryVR 2.0 takes as input a black-box simulator, a white-box transition graph, a time bound and a safety specification. As output it generates over-approximations o...

We present CODEV, a Matlab-based tool for verifying systems employing Model Predictive Control (MPC). The MPC solution is computed offline and modeled together with the physical system as a hybrid automaton, whose continuous dynamics may be nonlinear with a control solution that remains affine. While MPC is a widely used synthesis technique for con...

We present a new technique for verifying nonlinear and hybrid models with inputs. We observe that once an input signal is fixed, the sensitivity analysis of the model can be computed much more precisely. Based on this result, we propose a new simulation-driven verification algorithm and apply it to a suite of nonlinear and hybrid models of CMOS dig...

We present a new technique for verifying nonlinear and hybrid models with inputs.
We observe that once an input signal is fixed, the sensitivity analysis of the model can be computed much more precisely. Based on this result, we propose a new simulation-driven verification algorithm and apply it to a suite of nonlinear and hybrid models of CMOS di...

Safety analysis of Autonomous Vehicles and Advanced Driver Assist Systems (ADAS) is a central challenge facing the automotive industry. In this paper, we present a recently developed data-driven formal verification technique and demonstrate its applicability in a case study involving integrated safety analysis of an Automatic Emergency Braking (AEB...

Welcome to the proceedings of the 20th ACM International Conference on Hybrid Systems: Computation and Control (HSCC'17), held in Pittsburgh, Pennsylvania. HSCC is the premier research conference on foundations of Cyber-Physical Systems. It covers design, analysis, control synthesis techniques and their applications in various domains such as auton...

We study a notion of estimation entropy for continuous-time nonlinear systems, formulated in terms of the number of system trajectories that approximate all other trajectories up to an exponentially decaying error. We also consider an alternative definition of estimation entropy which uses approximating functions that are not necessarily trajectori...

Simulation-driven verification can provide formal safety guarantees for otherwise intractable nonlinear and hybrid system models. A key step in simulation-driven algorithms is to compute the reach set overapproximations from a set of initial states through numerical simulations and sensitivity analysis. This article addresses this problem by provid...

Rendezvous is a fundamental maneuver in autonomous space operations in which an active chaser spacecraft is required to navigate safely to the proximity of a second passive target spacecraft. Ensuring safety of such control maneuvers is challenging and design errors can be expensive. We present the first verified control solution to a benchmark for...

Presents information on the The 20th ACM International Conference on Hybrid Systems: Computation and Control.

We present the DryVR framework for verifying hybrid control systems that are described by a combination of a black-box simulator for trajectories and a white-box transition graph specifying mode switches. The framework includes (a) a probabilistic algorithm for learning sensitivity of the continuous trajectories from simulation data, (b) a bounded...

In a discrete-time linear multi-agent control system, where the agents are coupled via an environmental state, knowledge of the environmental state is desirable to control the agents locally. However, since the environmental state depends on the behavior of the agents, sharing it directly among these agents jeopardizes the privacy of the agents’ pr...