In the context of a smart industrial manufacturing scenario, where autonomous mobile robots (AMRs) from different manufacturers operate in shared environments, it is important to establish a method for verifying the integrity of the robots. To address this issue, we propose a novel framework for verifying the completion of tasks in multi-vendor robotic systems using proof-of-Iocation and distributed ledger technologies. This approach ensures the trustworthiness and reliability of a multi-vendor robotic system. Using dis-tributed ledger technology (DLT), robots can independently and cryptographically verify the completion of each other's tasks. Unlike traditional solutions that require several dedicated robots to participate in the verification process simultaneously, our proposed physical verification method is more efficient and does not require a typical âminingâ stage. Additionally, it can be done asynchronously without adding extra burdens or delays to other ongoing tasks. Simulation results demonstrate that our approach can efficiently and effectively identify malicious robots in a multi-vendor robotic system.
In some instances, intelligent, autonomous robotic systems (IARS) are transforming how the private and public sectors provide emergency services, deliver products, protect national interests, and accomplish their missions. Some futures, however, envision missions performed by cooperative teams of lARS-commonly described as swarms-making the purposeful design of swarms as information processing and communication systems an imperative. Furthermore, more optimal swarm performance depends on the degree to which its design fits its environment. In the context of organizational information processing and transactive memory theories, this paper explores the degree to which the centralization of decision-making and employment of distributed expertise may impact mission performance. Against the backdrop of collecting information on grey whale behaviors and migration routes, three swarm designs, starling, hive, and wolf-pack, are modeled and their simulated performance compared. The wolf-pack design, which is characterized by a largely decentralized decision-making structure and differentiated transactive memory system, out-performed the other designs based upon total work volumes and mission durations. Future studies should empirically investigate the impacts of cognitive slack and other swarm characteristics on mission accomplishment in a broader spectrum of scenarios.
Abdessamed Echikr, Ali Yachir, Chaker Abdelaziz Kerrache, Zakaria Sahraoui
In recent years, the concept of Internet of Robotic Things (IoRT) has gained significant attention, driven by the convergence of robotics, cloud computing, and diverse IoT devices and services. IoRT systems enable the autonomous exchange of data and decision-making within virtual infrastructures. However, managing and controlling diverse robotics applications that interact with IoT devices poses a major challenge in IoRT systems. The conventional centralized approach falls short in providing adequate security and privacy for the IoRT network, particularly due to the mobility of robots and the limited computational and energy resources of IoT devices. To address these limitations, this paper explores the integration of blockchain technology into IoRT networks. Blockchain, known for its distributed ledger based on peer-to-peer communication and trustworthy operations, offers a promising solution. This study provides a comprehensive overview of this integration, starting with an examination of the fundamental characteristics and challenges faced by IoRT networks. It then presents a survey of blockchain technology, highlighting its diverse applications in IoRT systems. Based on our findings, we will propose a new architecture for IoRT that utilizes Blockchain technology to address security and privacy concerns and enhance the overall performance of the network.
In this chapter, we propose the use of blockchain technologies and specifically the concept of decentralized autonomous organizations (DAO) in order to decentralize the Tactile Internet and enhance the performance and execution times of mobile applications. To achieve this objective, different methodologies were applied harnessing the partially or fully decentralized end-user equipment and edge computing server solutions, as well as crowdsourcing of human expertise to perform tasks that teleoperated robots struggle to complete reliably. Also, the concept of blockchain nudge contract was introduced to improve the task completion capabilities of unskilled decentralized members of the DAO. The simulation results provided illustrate that higher decentralization can lead to up to 90 percent improvement in task completion performance for an optimal offloading probability. Also, we demonstrated that crowdsourcing of human intelligence can severely improve task completion performance, especially in cases where robots are failing to complete physical tasks. Thus, to promote skilled user intervention and successfully complete tasks, the concept of nudging was adopted for skills transfer.
The proliferation of smart devices, sensors, autonomous robots, drones, and other similar instruments have profoundly changed the way of implementing and deploying systems in industrial and home environments, for diverse scenarios such as smart agriculture, healthcare, or manufacturing. Devices in these settings are not limited to simply observe and acquire data for monitoring, but they are also equipped with actuation capabilities, as well as the possibility of autonomously processing the incoming data through various techniques. However, given their intrinsic limitations regarding the capacity to store and process computations, it is often necessary to delegate some of these processing tasks to intermediary edge nodes in the network. These nodes, given their unique position can act as orchestrators guiding the decentralized work of the interconnected autonomous devices. Beyond static and pre-defined organization structures, in this work we propose the usage of agent and multi-agent-based models for designing and implementing swarms of edge nodes, conceived to dynamically orchestrate other devices, while meeting quality of service conditions. Allowing the control of intelligent edge nodes as conveyors and orchestrators on swarms of devices, we aim at providing intelligence to the self-organization of edge nodes, which may interchange streaming data, and represent their own capabilities through semantic models. Swarm-inspired behavioral patterns would guide the collaborative distribution of their computational tasks. Finally, we will implement and demonstrate the proposed technologies in an elderly home environment powered with a host of edge computing, sensing, and actuating devices.
Darcy Camargo, Andreas Penzkofer, Sebastian MĂŒller, William H. Sanders
The robust construction of the ledger data structure is an essential ingredient for the safe operation of a distributed ledger. While in traditional linear blockchain systems, permission to append to the structure is leader-based, in Directed Acyclic Graph-based ledgers, the writing access can be organised leaderless. However, this leaderless approach relies on fair treatment of non-referenced blocks, i.e. tips, by honest block issuers. We study the impact of a deviation from the standard tip selection by a subset of block issuers with the aim of halting the confirmation of honest blocks entirely. W e provide models on this so-called orphanage of blocks and validate these through open-sourced simulation studies. A critical threshold for the adversary issuance rate is shown to exist, above which the tip pool becomes unstable, while for values below the orphanage decrease exponentially. We study the robustness of the protocol with an expiration time on tips, also called garbage collection, and modification of the parent references per block.
Modern public and private infrastructure is increasingly large and complex regardless of the industry within which it is deployed - communications, power, transportation, manufacturing, finance, etc. Autonomous Decentralized Systems (ADSs) analogous to living systems with autonomous and decentralized subsystems have been developed to support the requirements of modern infrastructure. Large-scale infrastructure is increasingly a significant source of data on both its own operations as well as the society dependent on it. Big data from infrastructure can thus supply a variety of artificial and augmented intelligence systems. Large complex infrastructures typically require large complex organizations to operate and maintain. Such organizations though are typically centralized and constrained by bureaucratic policies and procedures. Decentralized Autonomous Organizations (DAOs) are emerging that may provide better transparency, autonomy and decentralization for the manner in which these large-scale infrastructures are operated. The paper contrasts DAOs and ADSs before identifying the requirements for DAO administration of an ADS.
This paper proposes a data sharing system among multiple networked robots. The system considers the value and the ownership of shared data in the robot networks based on Ethereum blockchain platform. In this system, the owner robot of important data such as grid maps can receive any rewards from the robots which use the shared data. This study aims to achieve robotic ecosystem including data generation, data sharing and reward compensation to the owners. Since this system is intended to be applied to a large number of robots, the simulation is conducted with multiple robots on Unity and Ethereum private chain. In order to approximate the system configuration in the real world, each robot in the simulator is assumed to be controlled by an independent computer system. Then, a Docker container was built for each robot to control the robots based on ROS platform and connect to the blockchain network and Unity. This paper introduces the whole system configuration integrating the robot network Docker containers, ROS system for navigation tasks, data sharing based on Ethereum and the Unity simulator. In the first simulation, the navigation system of multiple robots was executed. Grid map data of unknown areas is shared in this simulation. The results showed that data sharing and transactions among private Ethereum network participants were achieved as designed.
Distributed ledger technologies, together with AI, smart systems and robotics could provide a scalable and robust platform for the smart underwater and surface marine infrastructures of the close future. They will be harbours or ports, marine farms or remote tourism facilities - only accessible through robotic avatars - for protected areas or for the elders. Autonomous Marine Vehicles, IoT networks, and humans will coexist in highly heterogeneous multivendor multiplatform environments where market transactions and complex administrative procedures will be ubiquitous. Some blockchains such as the Ethereum network are able to provide distributed scalable computing and trustable functionalities, capable of managing both technical interactions and market transactions among very diversified autonomous agents. For these reasons they seem to provide a valuable backbone for the smart marine infrastructure of the coming decades. In this paper we outline our research and innovation strategy and present our results showing the potential benefits of a subsidiary architecture integrating distributed ledger technologies with swarms of autonomous surface robots implemented by a Belief Space Planning approach.
Empowered by blockchain and Web3 technologies, decentralized autonomous organizations (DAOs) are able to redefine resources, production relations, and organizational structures in a revolutionary manner. This article aims to reanalyze DAOs from the perspectives of organization and operation, and provide a more precise definition of DAOs as Decentralized Autonomous Organizations and Operations. Based on this, the fundamental principles and requirements of DAOs are explained, while the infrastructure based on cyberâphysicalâsocial system (CPSS) and parallel intelligence, as well as the supporting technologies, such as digital twins, metaverse, and Web3, are discussed. Besides, a five-layer intelligent architecture is presented, and the closed-loop equation and new function-oriented intelligent algorithms are also proposed. Moreover, the governance mechanisms from the individual, organizational and social perspectives are discussed, and the incentive mechanisms for the human, robot, and digital human are analyzed. This article can be regarded as a stepping stone for further research and developments of DAOs.
Xiujuan Wang, Mengzhen Kang, Hequan Sun, Philippe De Reffye · 5 authors
Briefing: The demand for food is tremendously increasing with the growth of the world population, which necessitates the development of sustainable agriculture under the impact of various factors, such as climate change. To fulfill this challenge, we are developing Metaverses for agriculture, referred to as AgriVerse, under our Decentralized Complex Adaptive Systems in Agriculture (DeCASA) project, which is a digital world of smart villages created alongside the development of Decentralized Sciences (DeSci) and Decentralized Autonomous Organizations (DAO) for Cyber-Physical-Social Systems (CPSSs). Additionally, we provide the architectures, operating modes and major applications of DeCASA in Agri-Verse. For achieving sustainable agriculture, a foundation model based on ACP theory and federated intelligence is envisaged. Finally, we discuss the challenges and opportunities.
Sahar Salimpour, Farhad Keramat, Jorge Peña Queralta, Tomi Westerlund
Multiple opportunities lie at the intersection of multi-robot systems and distributed ledger technologies (DLTs). In this work, we investigate the potential of new DLT solutions such as IOTA, for detecting anomalies and byzantine agents in multi-robot systems in a decentralized manner. Traditional blockchain approaches are not applicable to real-world networked and decentralized robotic systems where connectivity conditions are not ideal. To address this, we leverage recent advances in partition-tolerant and byzantine-tolerant collaborative decision-making processes with IOTA smart contracts. We show how our work in vision-based anomaly and change detection can be applied to detecting byzantine agents within multiple robots operating in the same environment. We show that IOTA smart contracts add a low computational overhead while allowing to build trust within the multi-robot system. The proposed approach effectively enables byzantine robot detection based on the comparison of images submitted by the different robots and detection of anomalies and changes between them.
Abstract Offshore wind farms will play a vital role in the global ambition of net zero energy generation. Future offshore wind farms will be larger and further from the coast, meaning that traditional humanâbased operations and maintenance approaches will become infeasible due to safety, cost, and skills shortages. The use of remotely operated or autonomous robotic assistants to undertake these activities provides an attractive alternative solution. This paper presents an autonomous multirobot system which is able to transport, deploy and retrieve a wind turbine blade inspection robot using an unmanned aerial vehicle (UAV). The proposed solution is a fully autonomous system including a robot deployment interface for deployment, a mechatronic linkâhook module (LHM) for retrieval, both installed on the underside of a UAV, a mechatronic onâload attaching module installed on the robotic payload and an intelligent global mission planner. The LHM is integrated with a 2âDOF hinge that can operate either passively or actively to reduce the swing motion of a slung load by approximately 30%. The mechatronic modules can be coupled and decoupled by special maneuvers of the UAV, and the intelligent global mission planner coordinates the operations of the UAV and the mechatronic modules for synchronous and seamless actions. For navigation in the vicinity of wind turbine blades, a visualâbased localization merged with the location knowledge from Global Navigation Satellite System has been developed. A proofâofâconcept system was field tested on a fullâsize decommissioned windâturbine blade. The results show that the experimental system is able to deploy and retrieve a robotic payload onto and from a wind turbine blade safely and robustly without the need for human intervention. The vicinity localization and navigation system have shown an accuracy of 0.65 and 0.44 m in the horizontal and vertical directions, respectively. Furthermore, this study shows the feasibility of systems toward autonomous inspection and maintenance of offshore windfarms.
Farhad Keramat, Jorge Peña Queralta, Tomi Westerlund
With the increasing ubiquity of autonomous robotic solutions, the interest in their connectivity and in the cooperation within multi-robot systems is rising. Two aspects that are a matter of current research are robot security and secure multi-robot collaboration robust to byzantine agents. Blockchain and other distributed ledger technologies (DLTs) have been proposed to address the challenges in both domains. Nonetheless, some key challenges include scalability and deployment within real-world networks. This paper presents an approach to integrating IOTA and ROS 2 for more scalable DLT-based robotic systems while allowing for network partition tolerance after deployment. This is, to the best of our knowledge, the first implementation of IOTA smart contracts for robotic systems, and the first integrated design with ROS 2. This is in comparison to the vast majority of the literature which relies on Ethereum. We present a general IOTA+ROS 2 architecture leading to partition-tolerant decision-making processes that also inherit byzantine tolerance properties from the embedded blockchain structures. We demonstrate the effectiveness of the proposed framework for a cooperative mapping application in a system with intermittent network connectivity. We show both superior performance with respect to Ethereum in the presence of network partitions, and a low impact in terms of computational resource utilization. These results open the path for wider integration of blockchain solutions in distributed robotic systems with less stringent connectivity and computational requirements.
Sanjaya Mallikarachchi, Can Dai, Oshani Seneviratne, Isuru S. Godage
The growing number of applications in Cyber-Physical Systems (CPS) involving different types of robots while maintaining interoperability and trust is an ongoing challenge faced by traditional centralized systems. This paper presents what is, to the best of our knowledge, the first integration of the Robotic Operating System (ROS) with the Ethereum blockchain using physical robots. We implement a specialized smart contract framework called âSwarm Contractsâ that rely on blockchain technology in real-world applications for robotic agents with human interaction to perform collaborative tasks while ensuring trust by motivating the agents with incentives using a token economy with a self-governing structure. The use of open-source technologies, including robot hardware platforms such as TurtleBot3, Universal Robot arm, and ROS, enables the ability to connect a wide range of robot types to the framework we propose. Going beyond simulations, we demonstrate the robustness of the proposed system in real-world conditions with actual hardware robots.
The Ph.D research project aims to explore the potential of the Decentralized Autonomous Organization paradigm in conjunction with classic software architectures for Artificial Intelligence applications. The intended goal is to investigate and formalize a possible integration path between Multi-agent System architectures and Decentralized Autonomous Organizations. Starting from the Foundation for Intelligent Physical Agents standards, we will extend basic primitives to integrate Multi-agent Systems on Distributed Ledger Technology networks. Possible deployment of services and applications in the Internet-of-Things, Artificial Intelligence and Distributed Machine Learning areas will be tested. Application of Data Analysis techniques on datasets built on such a framework will be also addressed.
The proliferation of Internet of Things (IoT) devices and applications that need to cooperate unattended highlights the need for seamless interoperability and intrinsic security. We argue that Distributed Ledger Technologies (DLTs), due to their decentralized nature, transparent operations, immutability, and availability, can enhance the security, reliability, and interoperability of such IoT systems. In this paper, we advance the integration of W3C's Web of Things (WoT) standards with DLTs and smart contracts, introducing smart contracts as âDigital Twinsâ of (physical) devices, or whole Cyber-Physical subsystems. Namely, we introduce a DLT-based architecture for controlling devices across federated IoT systems, securely, reliably, and with full auditability. The proposed architecture provides mass actuation and service composition with notable security properties, such as full auditability, transparency, and high availability. Specifically, a single request, with multiple action parameters and conditions, can trigger the reliable and secure actuation of a large number of possibly physically dispersed actuators.
Blockchains can be either permissioned or permissionless. Existing blockchain consensus algorithms used to create permissioned blockchains to not allow new validators to be dynamically added to the blockchain during runtime. This can be a problem when blockchain is used in swarm robotics, where redundancy is required. Besides, popular algorithms such as proof of work (PoW) that offer redundancy consume a lot of resources, making them unsuitable to run on the powerless robots used in swarm robotics. In addition, such algorithms are also vulnerable to threats such as the 51% attack. This research proposes a novel proof-of-identity (PoI) blockchain consensus algorithm to create a dynamically permissioned blockchain to be used in swarm robotics. This algorithm uses a swarm controller to generate a private-public key pair that is used to authorise validators. Tests carried out showed that the PoI algorithm is immune to the 51% attack threat and can run on low-powered devices such as Raspberry Pi 3. Moreover, the consensus time was also shown to be shorter in comparison to PoW.
A random beacon provides a continuous public source of randomness and its applications range from public lotteries to zero-knowledge proofs. Existing random beacon protocols sacrifice either the fault tolerance or the communication complexity for security, or ease of reconfigurability. This work overcomes the challenges with the existing works through a novel communication efficient combination of state machine replication and (Publicly) Verifiable Secret Sharing (PVSS/VSS).
Interest in multirobot systems is rising rapidly both in academia and in industry. The use of multiple robots working in a coordinated way, rather than a single robot, has several advantages in a diverse range of applications. However, few studies have focused on operations in which robots can behave maliciously and alter the outcome of the collective mission. In this article, we present a set of Byzantine Follow The Leader (BFTL) problems, in which a subset of robots in the system shows unintended or inconsistent behavior (i.e., Byzantine robots). In the BFTL problems,leadersdiscover routes from their starting positions to specific destinations and guide thefollowers, whileByzantinerobots try to hinder the leaders and mislead the followers. In this research, blockchain technology is used as a communication tool within multirobot systems, forleadersto broadcast directions to the whole group. We propose algorithms to tackle the BFTL problems, prove their correctness, and validate them in simulated experiments of realistic scenarios. Results show that the proposed algorithms mitigate the impact of Byzantine robots in multirobot systems conducting a BFTL mission. Our analysis provides minimum and maximum boundary calculations for important metrics including number of robots reaching their destination, number of steps taken, and weight requirements of the chain used during the mission. Our results provide a path toward the deployment of byzantine-resistant real-world multirobot systems.