Complex Autonomous Systems Research Articles

Toward Autonomous Vehicles and Machinery in Mill Yards of the Forest Industry: Technologies and Proposals for Autonomous Vehicle Operations

The use of autonomous systems on the wood processing sites of forest industries can significantly increase safety, productivity, and efficiency by reducing the number of monotonous and dangerous tasks conducted by human labor utilizing heavy machinery. However, autonomous machines are challenging and difficult to implement in the mill yards environment because of the dynamic and complex working environment, and partly unstructured processes. The inherent complexity of wood handling and storage tasks is requiring significant human expertise. Fast advancements in sensor technologies, machine learning techniques, and increases in the computational power enable progress in automated operation framework and algorithms development. This opens the door to introduce novel autonomous systems into this environment. With the aim of gaining a better understanding of current issues and facilitating optimal strategies for deploying high-level autonomous systems for the mill yard environments, this study: (1) Utilized a systematic literature review to map current autonomous technologies and algorithms suitable for adoption by the forest industry in automation of vehicles working in mill yards; (2) Summarizes and discusses the potential feasibility of the considered sensors and systems, adaption strategy, and high-level autonomous machinery implementation challenges in the mill yard environment; and (3) Proposes a system framework that integrates multiple technologies to enable autonomous navigation and material handling in mill yards. The study is the first of its kind as a comprehensive study on autonomous vehicles and machinery in mill yard environments. Our novel framework aids in the identification of follow-up research areas and thus promotes the adoption and use of complex autonomous systems in industrial environments.

Autonomous Vehicle: Security by Design

Security of (semi)-autonomous vehicles is a growing concern, first, due to the increased exposure of the functionality to potential attackers; second, due to the reliance of functionalities on diverse (semi)-autonomous systems; third, due to the interaction of a single-vehicle with myriads of other smart systems in urban traffic infrastructure. Beyond these technical issues, we argue that the security-by-design principle for smart and complex autonomous systems, such as an Autonomous Vehicle (AV) is poorly understood and rarely practiced. Unlike traditional IT systems, where the risk mitigation techniques and adversarial models are well studied and developed with security design principles such as security perimeter and defense-in-depth, the lack of such a framework for connected autonomous systems is plaguing the design and implementation of a secure AV. We attempt to identify the core issues of securing an AV. This is done methodically by developing a security-by-design framework for AV from the first principles. Subsequently, the technical challenges for AV security are identified.

Complete Agent-driven Model-based System Testing for Autonomous Systems

In this position paper, a novel approach to testing complex autonomous transportation systems (ATS) in the automotive, avionic, and railway domains is described. It is intended to mitigate some of the most critical problems regarding verification and validation (V&V) effort for ATS. V&V is known to become infeasible for complex ATS, when using conventional methods only. The approach advocated here uses complete testing methods on the module level, because these establish formal proofs for the logical correctness of the software. Having established logical correctness, system-level tests are performed in simulated cloud environments and on the target system. To give evidence that 'sufficiently many' system tests have been performed with the target system, a formally justified coverage criterion is introduced. To optimise the execution of very large system test suites, we advocate an online testing approach where multiple tests are executed in parallel, and test steps are identified on-the-fly. The coordination and optimisation of these executions is achieved by an agent-based approach. Each aspect of the testing approach advocated here is shown to either be consistent with existing standards for development and V&V of safety-critical transportation systems, or it is justified why it should become acceptable in future revisions of the applicable standards.

Multifunctional Technology of Flexible Manufacturing on a Mechatronics Line with IRM and CAS, Ready for Industry 4.0

A communication and control architecture of a multifunctional technology for flexible manufacturing on an assembly, disassembly, and repair mechatronics line (A/D/RML), assisted by a complex autonomous system (CAS), is presented in the paper. A/D/RML consists of a six-work station (WS) mechatronics line (ML) connected to a flexible cell (FC) equipped with a six-degree of freedom (DOF) industrial robotic manipulator (IRM). The CAS has in its structure two driving wheels and one free wheel (2 DW/1 FW)-wheeled mobile robot (WMR) equipped with a 7-DOF robotic manipulator (RM). On the end effector of the RM, a mobile visual servoing system (eye-in-hand VSS) is mounted. The multifunctionality is provided by the three actions, assembly, disassembly, and repair, while the flexibility is due to the assembly of different products. After disassembly or repair, CAS picks up the disassembled components and transports them to the appropriate storage depots for reuse. Technology operates synchronously with signals from sensors and eye-in-hand VSS. Disassembling or repairing starts after assembling and the final assembled product fails the quality test. Due to the diversity of communication and control equipment such as PLCs, robots, sensors or actuators, the presented technology, although it works on a laboratory structure, has applications in the real world and meets the specific requirements of Industry 4.0.

From driverless dilemmas to more practical commonsense tests for automated vehicles

For the first time in history, automated vehicles (AVs) are being deployed in populated environments. This unprecedented transformation of our everyday lives demands a significant undertaking: endowing complex autonomous systems with ethically acceptable behavior. We outline how one prominent, ethically relevant component of AVs—driving behavior—is inextricably linked to stakeholders in the technical, regulatory, and social spheres of the field. Whereas humans are presumed (rightly or wrongly) to have the “common sense” to behave ethically in new driving situations beyond a standard driving test, AVs do not (and probably should not) enjoy this presumption. We examine, at a high level, how to test the common sense of an AV. We start by reviewing discussions of “driverless dilemmas,” adaptions of the traditional “trolley dilemmas” of philosophy that have sparked discussion on AV ethics but have limited use to the technical and legal spheres. Then, we explain how to substantially change the premises and features of these dilemmas (while preserving their behavioral diagnostic spirit) in order to lay the foundations for a more practical and relevant framework that tests driving common sense as an integral part of road rules testing.

Применение автономной и дистанционно-управляемой техники на открытых горных работах

The article describes design principles for autonomous cargo transportation systems and social aspects of their implementation. Economic prerequisites for creation of autonomous cargo transportation systems in Russia and in the world are analyzed as well as the composition of the complex autonomous system. Issues of economic justification for implementation of autonomous cargo transportation systems, regulatory framework and safety provision of autonomous dump truck application are also addressed.

Design and Fabrication Considerations for Thermo-Resistive Pixel Detectors for Room Temperature Directional Long Wavelength IR Sensing

Rapid growth in application demands for smart sensing has fostered the development of micro-electromechanical-based devices with unique capabilities. Recent developments have led to complex autonomous systems that require a variety of intelligent sensing tasks to render human-machine interactions safe and efficient in workplace environments comprising both a human and robotic workforce. Here we report the design and fabrication of a novel thermo-resistive LWIR detector, for sensing and recalculating the direction of incident LWIR radiation for potential robotic applications. The work employs standard silicon micromachining processes along with sol-gel chemistry to fabricate three-dimensional pixel detectors to approximate an LWIR source's direction of incidence using thermo-resistive material. There have been no prior reports of the thermo-resistive effect in conjunction with directionality in LWIR sensors. In addition to the fabrication process flow, we describe the mathematical framework for sensor operation and present a photoresist deposition process for large 3-D topographic surface structures. We discuss the advantages and challenges of the currently designed and fabricated prototypes and highlight issues that limit their angular LWIR response.

Neural circuit policies enabling auditable autonomy

A central goal of artificial intelligence in high-stakes decision-making applications is to design a single algorithm that simultaneously expresses generalizability by learning coherent representations of their world and interpretable explanations of its dynamics. Here, we combine brain-inspired neural computation principles and scalable deep learning architectures to design compact neural controllers for task-specific compartments of a full-stack autonomous vehicle control system. We discover that a single algorithm with 19 control neurons, connecting 32 encapsulated input features to outputs by 253 synapses, learns to map high-dimensional inputs into steering commands. This system shows superior generalizability, interpretability and robustness compared with orders-of-magnitude larger black-box learning systems. The obtained neural agents enable high-fidelity autonomy for task-specific parts of a complex autonomous system. Inspired by the brain of the roundworm Caenorhabditis elegans, the authors design a highly compact neural network controller directly from raw input pixels. Compared with larger networks, this compact controller demonstrates improved generalization, robustness and interpretability on a lane-keeping task.

Areas of opportunity related to design of chemical and biological sensors based on liquid crystals

ABSTRACT The societal impact of liquid crystals (LCs) in electrooptical displays arrived after decades of research involving molecular-level design of LCs and their alignment layers, and elucidation of LC electrooptical phenomena at device scales. The anisotropic optical, mechanical and dielectric properties of LCs used in displays also make LCs remarkable amplifiers of their interactions with chemical and biological species, thus opening up the possibility that LCs may play an influential role in a data-driven society that depends on information coming from sensors. In this article, we describe ongoing efforts to design LC systems tailored for chemical and biological sensing, efforts that mirror the challenges and opportunities in LC design and alignment tackled several decades ago during development of LC electrooptical displays. Now, however, traditional design approaches based on structure–property relationships are being supplemented by data-driven methods such as machine learning. Recent studies also show that computational chemistry can greatly increase the rate of discovery of chemically responsive LC systems. Additionally, non-equilibrium states of LCs are being revealed to be useful for design of biological sensors and more complex autonomous systems that integrate self-regulated actuation along with sensing. These topics and others are addressed in this article with the aim of highlighting approaches and goals for future research that will realise the full potential of LC-based sensors.

A Semi-Physical Platform for Guidance and Formations of Fixed-Wing Unmanned Aerial Vehicles.

Unmanned Aerial Vehicles (UAVs) have multi-domain applications, fixed-wing UAVs being a widely used class. Despite the ongoing research on the topics of guidance and formation control of fixed-wing UAVs, little progress is known on implementation of semi-physical validation platforms (software-in-the-loop or hardware-in-the-loop) for such complex autonomous systems. A semi-physical simulation platform should capture not only the physical aspects of UAV dynamics, but also the cybernetics aspects such as the autopilot and the communication layers connecting the different components. Such a cyber-physical integration would allow validation of guidance and formation control algorithms in the presence of uncertainties, unmodelled dynamics, low-level control loops, communication protocols and unreliable communication: These aspects are often neglected in the design of guidance and formation control laws for fixed-wing UAVs. This paper describes the development of a semi-physical platform for multi-fixed wing UAVs where all the aforementioned points are carefully integrated. The environment adopts Raspberry Pi’s programmed in C++, which can be interfaced to standard autopilots (PX4) as a companion computer. Simulations are done in a distributed setting with a server program designed for the purpose of routing data between nodes, handling the user inputs and configurations of the UAVs. Gazebo-ROS is used as a 3D visualization tool.

Extendability Of Solutions To Autonomous Polynomial Differential SystemsExtendability Of Solutions To Autonomous Polynomial Differential Systems

We consider real and complex autonomous polynomial differential systems, both ordinary and completely solvable ones. We prove that in the case of the general position, solutions to these systems are not infinitely extendable in all independent variables. In addition, we give the proper examples.

PSO Based reduced order modelling of autonomous AC microgrid considering state perturbation

Reduced order modelling of complex autonomous microgrid system is crucial to its small signal modelling and stability concerns. To reduce the storage requirements and computational time, the order of such microgrids can be reduced by Model Order Reduction (MOR) techniques. This paper presents an optimal reduction technique, which retains dominant poles of the original system and achieves subsequent error minimization through the Particle Swarm Optimization algorithm (PSO). The 36th order complex microgrid system is reduced to 9th order approximant, which retains the significant dynamics of the original system. The simulation results reflect the superiority of the proposed method as compared to the balanced truncation method in terms of the time and frequency domain analysis of the reduced order equivalents. State perturbation in the state space model has also been considered in full as well as reduced order system dynamics and eigenvalue analysis for system stability.

Modelling and Control of Mechatronics Lines Served by Complex Autonomous Systems.

The aim of this paper is to reverse an assembly line, to be able to perform disassembly, using two complex autonomous systems (CASs). The disassembly is functioning only in case of quality default identified in the final product. The CASs are wheeled mobile robots (WMRs) equipped with robotic manipulators (RMs), working in parallel or collaboratively. The reversible assembly/disassembly mechatronics line (A/DML) assisted by CASs has a specific typology and is modelled by specialized hybrid instruments belonging to the Petri nets class, precisely synchronized hybrid Petri nets (SHPN). The need of this type of models is justified by the necessity of collaboration between the A/DML and CASs, both having characteristics and physical constraints that should be considered and to make all systems compatible. Firstly, the paper proposes the planning and scheduling of tasks necessary in modelling stage as well as in real time control. Secondly, two different approaches are proposed, related to CASs collaboration: a parallel approach with two CASs have simultaneous actions: one is equipped with robotic manipulator, used for manipulation, and the other is used for transporting. This approach is correlated with industrial A/D manufacturing lines where have to transport and handle weights in a wide range of variation. The other is a collaborative approach, A/DML is served by two CASs used for manipulation and transporting, both having simultaneous movements, following their own trajectories. One will assist the disassembly in even, while the other in odd workstations. The added value of this second approach consists in the optimization of a complete disassembly cycle. Thirdly, it is proposed in the paper the real time control of mechatronics line served by CASs working in parallel, based on the SHPN model. The novelty of the control procedure consists in the use of the synchronization signals, in absence of the visual servoing systems, for a precise positioning of the CASs serving the reversible mechatronics line.

Repulsive synchronization in complex networks.

Synchronization in complex networks characterizes what happens when an ensemble of oscillators in a complex autonomous system become phase-locked. We study the Kuramoto model with a tunable phase-lag parameter α in the coupling term to determine how phase shifts influence the synchronization transition. The simulation results show that the phase frustration parameter leads to desynchronization. We find two global synchronization regions for α∈[0,2π) when the coupling is sufficiently large and detect a relatively rare network synchronization pattern in the frustration parameter near α=π. We call this frequency-locking configuration as "repulsive synchronization," because it is induced by repulsive coupling. Since the repulsive synchronization cannot be described by the usual order parameter r, the parameter frequency dispersion is introduced to detect synchronization.

Triple state reliability measurement for a complex autonomous robot system based on extended triangular distribution

Modern manufacturing systems should comply with high reliability and availability standards in order to guarantee efficient planning and optimization. Manufacturing systems including autonomous robots make the problem more challenging. By increasing the number of components in the autonomous manufacturing system and with respect to their intermittent interactions, a complex system is evolved. The reliability of such a system is significant due to high repair costs and failure downtime duration. Therefore, in this paper a reliability measurement framework is developed for a triple state autonomous robot system in an automated manufacturing environment. In this framework, an extension of the triangular probability distribution is proposed. In an implementation study, the effectiveness and computational efficiency of the proposed method is illustrated. In addition, an analysis on the failure rate using the maximum likelihood estimation is reported.

A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data.

Pose estimation of free-form objects is a crucial task towards flexible and reliable highly complex autonomous systems. Recently, methods based on range and RGB-D data have shown promising results with relatively high recognition rates and fast running times. On this line, this paper presents a feature-based method for 6D pose estimation of rigid objects based on the Point Pair Features voting approach. The presented solution combines a novel preprocessing step, which takes into consideration the discriminative value of surface information, with an improved matching method for Point Pair Features. In addition, an improved clustering step and a novel view-dependent re-scoring process are proposed alongside two scene consistency verification steps. The proposed method performance is evaluated against 15 state-of-the-art solutions on a set of extensive and variate publicly available datasets with real-world scenarios under clutter and occlusion. The presented results show that the proposed method outperforms all tested state-of-the-art methods for all datasets with an overall 6.6% relative improvement compared to the second best method.

Runtime management and quantitative evaluation of changing system goals in complex autonomous systems

A key challenge in cyber-physical systems (CPS) design is their highly dynamic nature including runtime changes of system goals. Additional safety regulations or changed priorities may apply, e.g. (temporarily) focusing on safety goals after some incident occurred. Goal-aware CPS continuously evaluate goal achievement and autonomously perform adaptations for re-achievement at runtime. For complex system goals capturing dependencies, priorities, and conflicts, efficient goal evaluation techniques are required. To enable a fine-grained balancing of the cost-benefit ratio of autonomous decisions at runtime, a qualitative evaluation of goals is not sufficient. We provide an algorithm that efficiently calculates the quantitative “distance” between a system state and the system goals. We organise various goal types, their parent-children-relationships, context-dependent importances, and dependency relations in a hierarchical goal model. Due to its modular structure, goals can easily be added, removed, and changed at runtime. We illustrate our approach with an exemplary autonomous air drone delivery system and discuss it based on illustrative example scenarios. We argue that our approach enables a) the design of complex context-dependent quantitative goal models for autonomous goal-aware systems, b) the measurement of the impact of autonomous decisions at runtime, and c) the efficient runtime management of changing system goals.

Sustainability development: part 3 - the cybernetics of co-evolution through amenity

This is the third part of a three-part paper. The first part explored the nature of complex autonomous human activity systems, showing that they may be represented as third order cybernetic systems. In part 2 sustainability development was explored as an agency coevolving supersystem composed of interactive autonomous agency systems. In this third part of the paper, five systems are adopted in the supersystem that contributes to sustainability development. The supersystem and systems each have amenities. These change with system evolution. A literature review is undertaken to validate the suggested prime amenity of each system. Cultural Agency Theory (CAT) is used to model both the agencies and their interactive environment, all of which should have a capacity for sustainability. Each agency model has living system characteristics, with eigenvalues that are indicative of system stability, and eigenbehaviour that determines potential patterns of behaviour.

Sustainability development: part 3 - the cybernetics of co-evolution through amenity

This is the third part of a three-part paper. The first part explored the nature of complex autonomous human activity systems, showing that they may be represented as third order cybernetic systems. In part 2 sustainability development was explored as an agency coevolving supersystem composed of interactive autonomous agency systems. In this third part of the paper, five systems are adopted in the supersystem that contributes to sustainability development. The supersystem and systems each have amenities. These change with system evolution. A literature review is undertaken to validate the suggested prime amenity of each system. Cultural Agency Theory (CAT) is used to model both the agencies and their interactive environment, all of which should have a capacity for sustainability. Each agency model has living system characteristics, with eigenvalues that are indicative of system stability, and eigenbehaviour that determines potential patterns of behaviour.

Cross-catalytic hairpin assembly-based exponential signal amplification for CRET assay with low background noise

A toehold-mediated strand displacement (TMSD)-based cross-catalytic hairpin assembly (C-CHA) is demonstrated in this study, achieving exponential amplification of nucleic acids. Functionally, this system consists of four hairpins (H1, H2, H3 and H4) and one single-stranded initiator (I). Upon the introduction of I, the first CHA reaction (CHA1) is triggered, leading to the self-assembly of hybrid H1·H2 that then initiates the second CHA reaction (CHA2) to obtain the hybrid H3·H4. Since the single-stranded region in H3·H4 is identical to I, a new CHA1 is initiated, which thus achieves cross operation of CHA1 and CHA2 and exponential growth kinetics. Interestingly, because the C-CHA performs in a cascade manner, this system can be considered as multi-level molecular logic circuits with feedback mechanism. Moreover, through incorporating G-quadruplex subunits and fluorescein isothiocyanate (FITC) in the product of H1·H2, this C-CHA is readily utilized to fabricate a chemiluminescence resonance energy transfer (CRET) biosensing platform, achieving sensitive and selective detection of DNA and microRNA in real samples. Since the high background signal induced by FITC in the absence of initiator is greatly reduced through labeling quencher in H1, the signal-to-noise ratio and detection sensitivity are improved significantly. Therefore, our proposed C-CHA protocol holds a great potential for further applications in not only building complex autonomous systems but also the development of biosensing platforms and DNA nanotechnology.