arXiv subjects

Frank J. Jiang

Publications and source records attributed to Frank J. Jiang.

18 recordsLinked to original sources

arXiv2026

Demonstration of Space Robot Teleoperation over a Lossy and Delayed Network using ATMOS

We present a demonstration showcasing the Autonomy Testbed for Multi-purpose Orbiting Systems (ATMOS), a planar spacecraft-analog robot designed for hardware-in-the-loop evaluation of guidance and control strategies in microgravity-like conditions. Using ATMOS as the physical test platform, we investigate the design, analysis, and performance evaluation of control architectures for remotely operated spacecraft under round-trip communication delays. In this work, we develop and experimentally validate a control strategy that combines state prediction and trajectory tracking control to perform a docking maneuver, accounting for time-varying random communication latency between ground operators and the ATMOS system. The demonstration includes a long-distance remote control experiment between Seoul and Stockholm, introducing realistic intercontinental delays and variability. The results highlight the capability of ATMOS to support rapid, reliable, and cost-effective testing of spacecraft teleoperation concepts, establishing a first step toward robust validation of on-orbit operations in microgravity-like environments.

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arXiv2025

pyspect: An Extensible Toolbox for Automatic Construction of Temporal Logic Trees via Reachability Analysis

In this paper, we present pyspect, a Python toolbox that simplifies the use of reachability analysis for temporal logic problems. Currently, satisfying complex requirements in cyber-physical systems requires significant manual effort and domain expertise to develop the underlying reachability programs. This high development effort limits the broader adoption of reachability analysis for complex verification problems. To address this, pyspect provides a method-agnostic approach to performing reachability analysis for verifying a temporal logic specification via temporal logic trees (TLTs). It enables the specification of complex safety and liveness requirements using high-level logic formulations that are independent of any particular reachability technique or set representation. As a result, pyspect allows for the comparison of different reachability implementations, such as Hamilton-Jacobi and Hybrid Zonotope-based reachability analysis, for the same temporal logic specification. This design separates the concerns of implementation developers (who develop numerical procedures for reachability) and end-users (who write specifications). Through a simple vehicle example, we demonstrate how pyspect simplifies the synthesis of reachability programs, promotes specification reusability, and facilitates side-by-side comparisons of reachability techniques for complex tasks.

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arXiv2025

Beyond Line-of-Sight: Cooperative Localization Using Vision and V2X Communication

Accurate and robust localization is critical for the safe operation of Connected and Automated Vehicles (CAVs), especially in complex urban environments where Global Navigation Satellite System (GNSS) signals are unreliable. This paper presents a novel vision-based cooperative localization algorithm that leverages onboard cameras and Vehicle-to-Everything (V2X) communication to enable CAVs to estimate their poses, even in occlusion-heavy scenarios such as busy intersections. In particular, we propose a novel decentralized observer for a group of connected agents that includes landmark agents (static or moving) in the environment with known positions and vehicle agents that need to estimate their poses (both positions and orientations). Assuming that (i) there are at least three landmark agents in the environment, (ii) each vehicle agent can measure its own angular and translational velocities as well as relative bearings to at least three neighboring landmarks or vehicles, and (iii) neighboring vehicles can communicate their pose estimates, each vehicle can estimate its own pose using the proposed decentralized observer. We prove that the origin of the estimation error is locally exponentially stable under the proposed observer, provided that the minimal observability conditions are satisfied. Moreover, we evaluate the proposed approach through experiments with real 1/10th-scale connected vehicles and large-scale simulations, demonstrating its scalability and validating the theoretical guarantees in practical scenarios.

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arXiv2025

Towards Open-Source and Modular Space Systems with ATMOS

In the near future, autonomous space systems will compose many of the deployed spacecraft. Their tasks will involve autonomous rendezvous and proximity operations with large structures, such as inspections, assembly, and maintenance of orbiting space stations, as well as human-assistance tasks over shared workspaces. To promote replicable and reliable scientific results for autonomous control of spacecraft, we present the design of a space robotics laboratory based on open-source and modular software and hardware. The simulation software provides a software-in-the-loop architecture that seamlessly transfers simulated results to the hardware. Our results provide an insight into such a system, including comparisons of hardware and software results, as well as control and planning methodologies for controlling free-flying platforms.

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arXiv2024

Polynomial Logical Zonotope: A Set Representation for Reachability Analysis of Logical Systems

In this paper, we introduce a set representation called polynomial logical zonotopes for performing exact and computationally efficient reachability analysis on logical systems. We prove that through this polynomial-like construction, we are able to perform all of the fundamental logical operations (XOR, NOT, XNOR, AND, NAND, OR, NOR) between sets of points exactly in a reduced space, i.e., generator space with reduced complexity. Polynomial logical zonotopes are a generalization of logical zonotopes, which are able to represent up to $2^n$ binary vectors using only $n$ generators. Due to their construction, logical zonotopes are only able to support exact computations of some logical operations (XOR, NOT, XNOR), while other operations (AND, NAND, OR, NOR) result in over-approximations in the generator space. In order to perform all fundamental logical operations exactly, we formulate a generalization of logical zonotopes that is constructed by dependent generators and exponent matrices. While we are able to perform all of the logical operations exactly, this comes with a slight increase in computational complexity compared to logical zonotopes. To illustrate and showcase the computational benefits of polynomial logical zonotopes, we present the results of performing reachability analysis on two use cases: (1) safety verification of an intersection crossing protocol and (2) reachability analysis on a high-dimensional Boolean function. Moreover, to highlight the extensibility of logical zonotopes, we include an additional use case where we perform a computationally tractable exhaustive search for the key of a linear feedback shift register.

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arXiv2024

Towards Safe Autonomous Intersection Management: Temporal Logic-based Safety Filters for Vehicle Coordination

In this paper, we introduce a temporal logic-based safety filter for Autonomous Intersection Management (AIM), an emerging infrastructure technology for connected vehicles to coordinate traffic flow through intersections. Despite substantial work on AIM systems, the balance between intersection safety and efficiency persists as a significant challenge. Building on recent developments in formal methods that now have become computationally feasible for AIM applications, we introduce an approach that starts with a temporal logic specification for the intersection and then uses reachability analysis to compute safe time-state corridors for the connected vehicles that pass through the intersection. By analyzing these corridors, in contrast to single trajectories, we can make explicit design decisions regarding safety-efficiency trade-offs while taking each vehicle's decision uncertainty into account. Additionally, we compute safe driving limits to ensure that vehicles remain within their designated safe corridors. Combining these elements, we develop a service that provides safety filters for AIM coordination of connected vehicles. We evaluate the practical feasibility of our safety framework using a simulated 4-way intersection, showing that our approach performs in real-time for multiple scenarios.

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arXiv2024

Pedestrian Motion Prediction Using Transformer-based Behavior Clustering and Data-Driven Reachability Analysis

In this work, we present a transformer-based framework for predicting future pedestrian states based on clustered historical trajectory data. In previous studies, researchers propose enhancing pedestrian trajectory predictions by using manually crafted labels to categorize pedestrian behaviors and intentions. However, these approaches often only capture a limited range of pedestrian behaviors and introduce human bias into the predictions. To alleviate the dependency on manually crafted labels, we utilize a transformer encoder coupled with hierarchical density-based clustering to automatically identify diverse behavior patterns, and use these clusters in data-driven reachability analysis. By using a transformer-based approach, we seek to enhance the representation of pedestrian trajectories and uncover characteristics or features that are subsequently used to group trajectories into different "behavior" clusters. We show that these behavior clusters can be used with data-driven reachability analysis, yielding an end-to-end data-driven approach to predicting the future motion of pedestrians. We train and evaluate our approach on a real pedestrian dataset, showcasing its effectiveness in forecasting pedestrian movements.

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arXiv2024

Reachability Analysis Using Constrained Polynomial Logical Zonotopes

In this paper, we propose reachability analysis using constrained polynomial logical zonotopes. We perform reachability analysis to compute the set of states that could be reached. To do this, we utilize a recently introduced set representation called polynomial logical zonotopes for performing computationally efficient and exact reachability analysis on logical systems. Notably, polynomial logical zonotopes address the "curse of dimensionality" when analyzing the reachability of logical systems since the set representation can represent $2^h$ binary vectors using $h$ generators. After finishing the reachability analysis, the formal verification involves verifying whether the intersection of the calculated reachable set and the unsafe set is empty or not. Polynomial logical zonotopes lack closure under intersections, prompting the formulation of constrained polynomial logical zonotopes, which preserve the computational efficiency and exactness of polynomial logical zonotopes for reachability analysis while enabling exact intersections. Additionally, an extensive empirical study is presented to demonstrate and validate the advantages of constrained polynomial logical zonotopes.

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arXiv2024

Ensuring Safety at Intelligent Intersections: Temporal Logic Meets Reachability Analysis

In this work, we propose an approach for ensuring the safety of vehicles passing through an intelligent intersection. There are many proposals for the design of intelligent intersections that introduce central decision-makers to intersections for enhancing the efficiency and safety of the vehicles. To guarantee the safety of such designs, we develop a safety framework for intersections based on temporal logic and reachability analysis. We start by specifying the required behavior for all the vehicles that need to pass through the intersection as linear temporal logic formula. Then, using temporal logic trees, we break down the linear temporal logic specification into a series of Hamilton-Jacobi reachability analyses in an automated fashion. By successfully constructing the temporal logic tree through reachability analysis, we verify the feasibility of the intersection specification. By taking this approach, we enable a safety framework that is able to automatically provide safety guarantees on new intersection behavior specifications. To evaluate our approach, we implement the framework on a simulated T-intersection, where we show that we can check and guarantee the safety of vehicles with potentially conflicting paths.

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arXiv2024

Small-Scale Testbed for Evaluating C-V2X Applications on 5G Cellular Networks

In this work, we present a small-scale testbed for evaluating the real-life performance of cellular V2X (C-V2X) applications on 5G cellular networks. Despite the growing interest and rapid technology development for V2X applications, researchers still struggle to prototype V2X applications with real wireless networks, hardware, and software in the loop in a controlled environment. To help alleviate this challenge, we present a testbed designed to accelerate development and evaluation of C-V2X applications on 5G cellular networks. By including a small-scale vehicle platform into the testbed design, we significantly reduce the time and effort required to test new C-V2X applications on 5G cellular networks. With a focus around the integration of small-scale vehicle platforms, we detail the design decisions behind the full software and hardware setup of commonly needed intelligent transport system agents (e.g. sensors, servers, vehicles). Moreover, to showcase the testbed's capability to produce industrially-relevant, real world performance evaluations, we present an evaluation of a simple test case inspired from shared situational awareness. Finally, we discuss the upcoming use of the testbed for evaluating 5G cellular network-based shared situational awareness and other C-V2X applications.

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arXiv2024

Guaranteed Completion of Complex Tasks via Temporal Logic Trees and Hamilton-Jacobi Reachability

In this paper, we present an approach for guaranteeing the completion of complex tasks with cyber-physical systems (CPS). Specifically, we leverage temporal logic trees constructed using Hamilton-Jacobi reachability analysis to (1) check for the existence of control policies that complete a specified task and (2) develop a computationally-efficient approach to synthesize the full set of control inputs the CPS can implement in real-time to ensure the task is completed. We show that, by checking the approximation directions of each state set in the temporal logic tree, we can check if the temporal logic tree suffers from the "leaking corner issue," where the intersection of reachable sets yields an incorrect approximation. By ensuring a temporal logic tree has no leaking corners, we know the temporal logic tree correctly verifies the existence of control policies that satisfy the specified task. After confirming the existence of control policies, we show that we can leverage the value functions obtained through Hamilton-Jacobi reachability analysis to efficiently compute the set of control inputs the CPS can implement throughout the deployment time horizon to guarantee the completion of the specified task. Finally, we use a newly released Python toolbox to evaluate the presented approach on a simulated driving task.

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arXiv2024

Formal Verification of Linear Temporal Logic Specifications Using Hybrid Zonotope-Based Reachability Analysis

In this paper, we introduce a hybrid zonotope-based approach for formally verifying the behavior of autonomous systems operating under Linear Temporal Logic (LTL) specifications. In particular, we formally verify the LTL formula by constructing temporal logic trees (TLT)s via backward reachability analysis (BRA). In previous works, TLTs are predominantly constructed with either highly general and computationally intensive level set-based BRA or simplistic and computationally efficient polytope-based BRA. In this work, we instead propose the construction of TLTs using hybrid zonotope-based BRA. By using hybrid zonotopes, we show that we are able to formally verify LTL specifications in a computationally efficient manner while still being able to represent complex geometries that are often present when deploying autonomous systems, such as non-convex, disjoint sets. Moreover, we evaluate our approach on a parking example, providing preliminary indications of how hybrid zonotopes facilitate computationally efficient formal verification of LTL specifications in environments that naturally lead to non-convex, disjoint geometries.

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arXiv2023

Logical Zonotopes: A Set Representation for the Formal Verification of Boolean Functions

A logical zonotope, which is a new set representation for binary vectors, is introduced in this paper. A logical zonotope is constructed by XOR-ing a binary vector with a combination of other binary vectors called generators. Such a zonotope can represent up to 2^n binary vectors using only n generators. It is shown that logical operations over sets of binary vectors can be performed on the zonotopes' generators and, thus, significantly reduce the computational complexity of various logical operations (e.g., XOR, NAND, AND, OR, and semi-tensor products). Similar to traditional zonotopes' role in the formal verification of dynamical systems over real vector spaces, logical zonotopes can efficiently analyze discrete dynamical systems defined over binary vector spaces. We illustrate the approach and its ability to reduce the computational complexity in two use cases: (1) encryption key discovery of a linear feedback shift register and (2) safety verification of a road traffic intersection protocol.

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arXiv2023

Data-Driven Reachability Analysis of Pedestrians Using Behavior Modes

In this paper, we present a data-driven approach for safely predicting the future state sets of pedestrians. Previous approaches to predicting the future state sets of pedestrians either do not provide safety guarantees or are overly conservative. Moreover, an additional challenge is the selection or identification of a model that sufficiently captures the motion of pedestrians. To address these issues, this paper introduces the idea of splitting previously collected, historical pedestrian trajectories into different behavior modes for performing data-driven reachability analysis. Through this proposed approach, we are able to use data-driven reachability analysis to capture the future state sets of pedestrians, while being less conservative and still maintaining safety guarantees. Furthermore, this approach is modular and can support different approaches for behavior splitting. To illustrate the efficacy of the approach, we implement our method with a basic behavior-splitting module and evaluate the implementation on an open-source data set of real pedestrian trajectories. In this evaluation, we find that the modal reachable sets are less conservative and more descriptive of the future state sets of the pedestrian.

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arXiv2023

Online Control Synthesis for Uncertain Systems under Signal Temporal Logic Specifications

This paper studies the online control synthesis problem for uncertain discrete-time systems subject to signal temporal logic (STL) specifications. Different from existing techniques, this work proposes an approach based on STL, reachability analysis, and temporal logic trees. Firstly, a real-time version of STL semantics and a tube-based temporal logic tree (tTLT) are proposed. We show that the tTLT is an underapproximation for the STL formula, in the sense that a trajectory satisfying an tTLT also satisfies the corresponding STL formula. Secondly, an online control synthesis algorithm is designed. It is shown that when the STL formula is robustly satisfiable and the initial state of the system belongs to the initial root node of the tTLT, it is guaranteed that the trajectory generated by the control synthesis algorithm satisfies the STL formula. The effectiveness of the proposed approach is verified by a simulation example and a practical experiment.

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arXiv2022

Enhancing Data-Driven Reachability Analysis using Temporal Logic Side Information

This paper presents algorithms for performing data-driven reachability analysis under temporal logic side information. In certain scenarios, the data-driven reachable sets of a robot can be prohibitively conservative due to the inherent noise in the robot's historical measurement data. In the same scenarios, we often have side information about the robot's expected motion (e.g., limits on how much a robot can move in a one-time step) that could be useful for further specifying the reachability analysis. In this work, we show that if we can model this side information using a signal temporal logic (STL) fragment, we can constrain the data-driven reachability analysis and safely limit the conservatism of the computed reachable sets. Moreover, we provide formal guarantees that, even after incorporating side information, the computed reachable sets still properly over-approximate the robot's future states. Lastly, we empirically validate the practicality of the over-approximation by computing constrained, data-driven reachable sets for the Small-Vehicles-for-Autonomy (SVEA) hardware platform in two driving scenarios.

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arXiv2020

Temporal Logic Trees for Model Checking and Control Synthesis of Uncertain Discrete-time Systems

We propose algorithms for performing model checking and control synthesis for discrete-time uncertain systems under linear temporal logic (LTL) specifications. We construct temporal logic trees (TLT) from LTL formulae via reachability analysis. In contrast to automaton-based methods, the construction of the TLT is abstraction-free for infinite systems, that is, we do not construct discrete abstractions of the infinite systems. Moreover, for a given transition system and an LTL formula, we prove that there exist both a universal TLT and an existential TLT via minimal and maximal reachability analysis, respectively. We show that the universal TLT is an underapproximation for the LTL formula and the existential TLT is an overapproximation. We provide sufficient conditions and necessary conditions to verify whether a transition system satisfies an LTL formula by using the TLT approximations. As a major contribution of this work, for a controlled transition system and an LTL formula, we prove that a controlled TLT can be constructed from the LTL formula via control-dependent reachability analysis. Based on the controlled TLT, we design an online control synthesis algorithm, under which a set of feasible control inputs can be generated at each time step. We also prove that this algorithm is recursively feasible. We illustrate the proposed methods for both finite and infinite systems and highlight the generality and online scalability with two simulated examples.

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arXiv2016

Learning Quadrotor Dynamics Using Neural Network for Flight Control

Traditional learning approaches proposed for controlling quadrotors or helicopters have focused on improving performance for specific trajectories by iteratively improving upon a nominal controller, for example learning from demonstrations, iterative learning, and reinforcement learning. In these schemes, however, it is not clear how the information gathered from the training trajectories can be used to synthesize controllers for more general trajectories. Recently, the efficacy of deep learning in inferring helicopter dynamics has been shown. Motivated by the generalization capability of deep learning, this paper investigates whether a neural network based dynamics model can be employed to synthesize control for trajectories different than those used for training. To test this, we learn a quadrotor dynamics model using only translational and only rotational training trajectories, each of which can be controlled independently, and then use it to simultaneously control the yaw and position of a quadrotor, which is non-trivial because of nonlinear couplings between the two motions. We validate our approach in experiments on a quadrotor testbed.

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