23 research outputs found
Polynomial Logical Zonotopes: 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. 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
order to perform all fundamental logical operations exactly, we formulate a
generalization of logical zonotopes that is constructed by additional dependent
generators and exponent matrices. 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) exactly. 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. We show that we can use
polynomial logical zonotopes to perform exact reachability analysis while
retaining a low computational complexity. 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, (2) and 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.Comment: arXiv admin note: substantial text overlap with arXiv:2210.0859
Homomorphic Data Isolation for Hardware Trojan Protection
The interest in homomorphic encryption/decryption is increasing due to its
excellent security properties and operating facilities. It allows operating on
data without revealing its content. In this work, we suggest using homomorphism
for Hardware Trojan protection. We implement two partial homomorphic designs
based on ElGamal encryption/decryption scheme. The first design is a
multiplicative homomorphic, whereas the second one is an additive homomorphic.
We implement the proposed designs on a low-cost Xilinx Spartan-6 FPGA. Area
utilization, delay, and power consumption are reported for both designs.
Furthermore, we introduce a dual-circuit design that combines the two earlier
designs using resource sharing in order to have minimum area cost. Experimental
results show that our dual-circuit design saves 35% of the logic resources
compared to a regular design without resource sharing. The saving in power
consumption is 20%, whereas the number of cycles needed remains almost the sam
D-SLATS: Distributed Simultaneous Localization and Time Synchronization
Through the last decade, we have witnessed a surge of Internet of Things
(IoT) devices, and with that a greater need to choreograph their actions across
both time and space. Although these two problems, namely time synchronization
and localization, share many aspects in common, they are traditionally treated
separately or combined on centralized approaches that results in an ineffcient
use of resources, or in solutions that are not scalable in terms of the number
of IoT devices. Therefore, we propose D-SLATS, a framework comprised of three
different and independent algorithms to jointly solve time synchronization and
localization problems in a distributed fashion. The First two algorithms are
based mainly on the distributed Extended Kalman Filter (EKF) whereas the third
one uses optimization techniques. No fusion center is required, and the devices
only communicate with their neighbors. The proposed methods are evaluated on
custom Ultra-Wideband communication Testbed and a quadrotor, representing a
network of both static and mobile nodes. Our algorithms achieve up to three
microseconds time synchronization accuracy and 30 cm localization error
Shared Situational Awareness with V2X Communication and Set-membership Estimation
The ability to perceive and comprehend a traffic situation and to estimate
the state of the vehicles and road-users in the surrounding of the ego-vehicle
is known as situational awareness. Situational awareness for a heavy-duty
autonomous vehicle is a critical part of the automation platform and depends on
the ego-vehicle's field-of-view. But when it comes to the urban scenario, the
field-of-view of the ego-vehicle is likely to be affected by occlusion and
blind spots caused by infrastructure, moving vehicles, and parked vehicles.
This paper proposes a framework to improve situational awareness using
set-membership estimation and Vehicle-to-Everything (V2X) communication. This
framework provides safety guarantees and can adapt to dynamically changing
scenarios, and is integrated into an existing complex autonomous platform. A
detailed description of the framework implementation and real-time results are
illustrated in this paper
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