In the age of respiratory illnesses like COVID 19, we understand the necessity for a robot based delivery system to ensure safe and contact free courier delivery. A blockchain based Dynamic IDentifier gives people total power over their identities while preserving auditability and anonymity. A human mobile phone and a robot are machines created with a chip, making it simple to deploy a physical unclonable function based verification system between the robot and the customer. This article presents a novel framework and a first customer verification scheme for verified courier delivery utilizing the blockchain enabled DID and PUF enabled robots. We employ DID for customer authentication between a robot (a service provider) and a customer and PUF for robot verification by the customer. We ve also put the proposed work into practice and demonstrated its capabilities in terms of throughput, latency, computing cost, and communication cost. We also show formal security proof for the proposed user verification scheme based on the tamarin prover.
Salma Salimi, Paola Torrico Morón, Jorge Peña Queralta, Tomi Westerlund
In recent years, multi-robot systems have received increasing attention from both industry and academia. Besides the need of accurate and robust estimation of relative localization, security and trust in the system are essential to enable wider adoption. In this paper, we propose a framework using Hyperledger Fabric for multi-robot collaboration in industrial applications. We rely on blockchain identities for the interaction of ground and aerial robots, and use smart contracts for collaborative decision making. The use of ultra-wideband (UWB) localization for both autonomous navigation and robot collaboration extends our previous work in Fabric-based fleet management. We focus on an inventory management application which uses a ground robot and an aerial robot to inspect a warehouse-like environment and store information about the found objects in the blockchain. We measure the impact of adding the blockchain layer, analyze the transaction commit latency and compare the resource utilization of blockchain-related processes to the already running data processing modules.
Visual homing is a lightweight approach to robot visual navigation. Based upon stored visual information of a home location, the navigation back to this location can be accomplished from any other location in which this location is visible by comparing home to the current image. However, a key challenge of visual homing is that the target home location must be within the robot's field of view (FOV) to start homing. Therefore, this work addresses such a challenge by integrating blockchain technology into the visual homing navigation system. Based on the decentralized feature of blockchain, the proposed solution enables visual homing robots to share their visual homing information and synchronously access the stored data (visual homing information) in the decentralized ledger to establish the navigation path. The navigation path represents a per-robot sequence of views stored in the ledger. If the home location is not in the FOV, the proposed solution permits a robot to find another robot that can see the home location and travel towards that desired location. The evaluation results demonstrate the efficiency of the proposed framework in terms of end-to-end latency, throughput, and scalability.
Eduardo Castelló Ferrer, Ivan Berman, Aleksandr Kapitonov, Vadim Manaenko · 6 authors
The physical autonomy of robots is well understood both theoretically and practically. By contrast, there is almost no research exploring their potential economic autonomy. In this paper, we present the first economically autonomous robot -- a robot able to produce marketable goods while having full control over the use of its generated income. Gaka-chu ("painter" in Japanese) is a 6-axis robot arm that creates paintings of Japanese characters from an autoselected keyword. By using a blockchain-based smart contract, Gaka-chu can autonomously list a painting it made for sale in an online auction. In this transaction, the robot interacts with the human bidders as a peer not as a tool. Using the blockchain-based smart contract, Gaka-chu can then use its income from selling paintings to replenish its resources by autonomously ordering materials from an online art shop. We built the Gaka-chu prototype with an Ethereum-based smart contract and ran a 6-month long experiment, during which the robot created and sold four paintings, simultaneously using its income to purchase supplies and repay initial investors. In this work, we present the results of the experiments conducted and discuss the implications of economically autonomous robots.
Salma Salimi, Jorge Peña Queralta, Tomi Westerlund
Trust is increasingly becoming a key consideration in the design of autonomous robotic systems. In industrial applications, security and trust in the system are requirements for widespread adoption. Blockchain technologies have emerged as a potential solution to address identity management and secure data aggregation and control. However, the vast majority of works to date utilize Ethereum and smart contracts that are not scalable or well suited for industrial applications. This paper presents what is, to the best of our knowledge, the first integration of ROS 2 with the Hyperledger Fabric blockchain. With a framework that leverages Fabric smart contracts and ROS 2 through a Go application, we delve into the potential of using blockchain for controlling robots, and gathering and processing their data. We demonstrate the applicability of the proposed framework to an inventory management use-case where different robots are used to detect objects of interest in a given area. Designed to meet the requirements of distributed robotic systems, we show that the performance of the robots is not impacted significantly by the blockchain layer. At the same time, we provide examples for developing other applications that integrate Fabric smart contracts with ROS 2. Our results pave the way for further adoption of blockchain technologies in autonomous robotic systems for building trustable data sharing.
Dwindling nonrenewable fuel reserves, progressing severe environmental pollution, and accelerating climate change require society to reevaluate existing transportation concepts. While electric vehicles (EVs) have become more popular and slowly gain widespread adoption, the corresponding battery charging infrastructures still limits EVs' use in our everyday life. This is especially true for EV owners that do not have the option to operate charging hardware, such as wall boxes, at their premises. Charging an EV without an at-home wall box is time-consuming since the owner has to drive to the charger, charge the vehicle while waiting nearby, and finally drive back home. Thus, a convenient and easy-to-use solution is required to overcome the issue and incentivize EVs for daily commuters. Therefore, we propose an ecosystem and a service platform for (semi-)autonomous electric vehicles that allow them to utilize their "free"-time, e.g., at night, to access public and private charging infrastructure, charge their batteries, and get back home before the owner needs the car again. To do so, we utilize the concept of the Machine-to-Everything Economy (M2X Economy) and outline a decentralized ecosystem for smart machines that transact, interact and collaborate via blockchain-based smart contracts to enable a convenient battery charging marketplace for (semi-)autonomous EVs.
Xianjia Yu, Jorge Peña Queralta, Jukka Heikkonen, Tomi Westerlund
Autonomous systems are becoming inherently ubiquitous with the advancements of computing and communication solutions enabling low-latency offloading and real-time collaboration of distributed devices. Decentralized technologies with blockchain and distributed ledger technologies (DLTs) are playing a key role. At the same time, advances in deep learning (DL) have significantly raised the degree of autonomy and level of intelligence of robotic and autonomous systems. While these technological revolutions were taking place, raising concerns in terms of data security and end-user privacy has become an inescapable research consideration. Federated learning (FL) is a promising solution to privacy-preserving DL at the edge, with an inherently distributed nature by learning on isolated data islands and communicating only model updates. However, FL by itself does not provide the levels of security and robustness required by today’s standards in distributed autonomous systems. This survey covers applications of FL to autonomous robots, analyzes the role of DLT and FL for these systems, and introduces the key background concepts and considerations in current research.
This paper presents a smart contract-based solution for autonomous administration of construction progress payments. It bridges the gap between payments (cash flow) and the progress assessments at job sites (product flow) enabled by reality capture technologies and building information modeling (BIM). The approach eliminates the reliance on the centralized and heavily intermediated mechanisms of existing payment applications. The construction progress is stored in a distributed manner using content addressable file sharing; it is broadcasted to a smart contract which automates the on-chain payment settlements and the transfer of lien rights. The method was successfully used for processing payments to 7 subcontractors in two commercial construction projects where progress monitoring was performed using a camera-equipped unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV) equipped with a laser scanner. The results show promise for the method's potential for increasing the frequency, granularity, and transparency of payments. The paper is concluded with a discussion of implications for project management, introducing a new model of project as a singleton state machine.
Kiril Antevski, Milan Groshev, Gabriele Baldoni, Carlos J. Bernardos
The concept of federation in 5G and NFV networks aims to provide orchestration of services across multiple administrative domains. Edge robotics, as a field of robotics, implements the robot control on the network edge by relying on low-latency and reliable access connectivity. In this paper, we propose a solution that enables Edge robotics service to expand its service footprint or access coverage over multiple administrative domains. We propose application of Distributed ledger technologies (DLTs) for the federation procedures to enable private, secure and trusty interactions between undisclosed administrative domains. The solution is applied on a real-case Edge robotics experimental scenario. The results show that it takes around 19 seconds to deploy & federate a Edge robotics service in an external/anonymous domain without any service down-time.
This conceptual paper overviews how blockchain technology is involving the operation of multi-robot collaboration for combating COVID-19 and future pandemics. Robots are a promising technology for providing many tasks such as spraying, disinfection, cleaning, treating, detecting high body temperature/mask absence, and delivering goods and medical supplies experiencing an epidemic COVID-19. For combating COVID-19, many heterogeneous and homogenous robots are required to perform different tasks for supporting different purposes in the quarantine area. Controlling and decentralizing multi-robot play a vital role in combating COVID-19 by reducing human interaction, monitoring, delivering goods. Blockchain technology can manage multi-robot collaboration in a decentralized fashion, improve the interaction among them to exchange information, share representation, share goals, and trust. We highlight the challenges and provide the tactical solutions enabled by integrating blockchain and multi-robot collaboration to combat COVID-19 pandemic. The framework of our conceptual proposed can increase the intelligence, decentralization, and autonomous operations of connected multi-robot collaboration in the blockchain network. We overview blockchain potential benefits to defining a framework of multi-robot collaboration applications to combat COVID-19 epidemics such as monitoring and outdoor and hospital End to End (E2E) delivery systems. Furthermore, we discuss the challenges and opportunities of integrated blockchain, multi-robot collaboration, and the Internet of Things (IoT) for combating COVID-19 and future pandemics.
In the next few years, Blockchain will play a central role in IoT as a technology. It enables the traceability of processes between multiple parties independent of a central instance. Blockchain allows to make the processes more transparent, cheaper, and safer. This research paper was conducted as systematic literature search. Our aim is to understand current state of implementation in context of Blockchain Technology for digital protection of communication in industrial cyber-physical systems. We have extracted 28 primary papers from scientific databases and classified into different categories using visualizations. The results show that the focus in around 14\% papers is on solution proposal and implementation of use cases "Secure transfer of order data" using Ethereum Blockchain, 7\% papers applying Hyperledger Fabric and Multichain. The majority of research (around 43\%) is focusing on solution development for supply chain and process traceability.
One of the key challenges in the collaboration within heterogeneous multi-robot systems is the optimization of the amount and type of data to be shared between robots with different sensing capabilities and computational resources. In this paper, we present a novel approach to managing collaboration terms in heterogeneous multi-robot systems with blockchain technology. Leveraging the extensive research of consensus algorithms in the blockchain domain, we exploit key technologies in this field to be integrated for consensus in robotic systems. We propose the utilization of proof of work systems to have an online estimation of the available computational resources at different robots. Furthermore, we define smart contracts that integrate information about the environment from different robots in order to evaluate and rank the quality and accuracy of each of the robots' sensor data. This means that the key parameters involved in heterogeneous robotic collaboration are integrated within the Blockchain and estimated at all robots equally without explicitly sharing information about the robots' hardware or sensors. Trustability is based on the verification of data samples that are submitted to the blockchain within each data exchange transaction and validated by other robots operating in the same environment. Initial results are reported which show the viability of the concepts presented in this paper.
The concept of a blockchain has given way to the development of cryptocurrencies, enabled smart contracts, and unlocked a plethora of other disruptive technologies. But, beyond its use case in cryptocurrencies, and in network coordination and automation, blockchain technology may have serious sociotechnical implications in the future co-existence of robots and humans. Motivated by the recent explosion of interest around blockchains, and our extensive work on open-source blockchain technology and its integration into robotics - this paper provides insights in ways in which blockchains and other decentralized technologies can impact our interactions with robot agents and the social integration of robots into human society.
Ilya Afanasyev, Alexander Kolotov, Ruslan Rezin, Konstantin Danilov · 13 authors
Decentralization, immutability and transparency make of Blockchain one of the most innovative technology of recent years. This paper presents an overview of solutions based on Blockchain technology for multi-agent robotic systems, and provide an analysis and classification of this emerging field. The reasons for implementing Blockchain in a multi-robot network may be to increase the interaction efficiency between agents by providing more trusted information exchange, reaching a consensus in trustless conditions, assessing robot productivity or detecting performance problems, identifying intruders, allocating plans and tasks, deploying distributed solutions and joint missions. Blockchain-based applications are discussed to demonstrate how distributed ledger can be used to extend the number of research platforms and libraries for multi-agent robotic systems.
A blockchain, during its lifetime, records large amounts of data, that in a common usage its kept on its entirety. In a robotics environment, the old information is useful for human evaluation, or oracles interfacing with the blockchain but it is not useful for the robots that require only current information in order to continue their work. This causes a storage problem in blockchain nodes that have limited storage capacity, such as in the case of nodes attached to robots that are usually built around embedded solutions. This paper presents a time-segmentation solution for devices with limited storage capacity, integrated in a particular robot-directed blockchain called RobotChain. Results are presented regarding the proposed solution that show that the goal of restricting each node's capacity is reached without compromising all the benefits that arise from the use of blockchains in these contexts, and on the contrary, it allows for cheap nodes to use this blockchain, reduces storage costs and allows faster deployment of new nodes.
Ilya Afanasyev, Alexander Kolotov, Ruslan Rezin, Konstantin Danilov · 6 authors
The possibilities of decentralization and immutability make blockchain\nprobably one of the most breakthrough and promising technological innovations\nin recent years. This paper presents an overview, analysis, and classification\nof possible blockchain solutions for practical tasks facing multi-agent robotic\nsystems. The paper discusses blockchain-based applications that demonstrate how\ndistributed ledger can be used to extend the existing number of research\nplatforms and libraries for multi-agent robotic systems.\n
Blockchain is a disruptive technology that is normally used within financial applications, however it can be very beneficial also in certain robotic contexts, such as when an immutable register of events is required. Among the several properties of Blockchain that can be useful within robotic environments, we find not just immutability but also decentralization of the data, irreversibility, accessibility and non-repudiation. In this paper, we propose an architecture that uses blockchain as a ledger and smart-contract technology for robotic control by using external parties, Oracles, to process data. We show how to register events in a secure way, how it is possible to use smart-contracts to control robots and how to interface with external Artificial Intelligence algorithms for image analysis. The proposed architecture is modular and can be used in multiple contexts such as in manufacturing, network control, robot control, and others, since it is easy to integrate, adapt, maintain and extend to new domains.
As a disruptive technology, blockchain, particularly its original form of bitcoin as a type of digital currency, has attracted great attentions. The innovative distributed decision making and security mechanism lay the technical foundation for its success, making us consider to penetrate the power of blockchain technology to distributed control and cooperative robotics, in which the distributed and secure mechanism is also highly demanded. Actually, security and distributed communication have long been unsolved problems in the field of distributed control and cooperative robotics. It has been reported on the network failure and intruder attacks of distributed control and multi-robotic systems. Blockchain technology provides promise to remedy this situation thoroughly. This work is intended to create a global picture of blockchain technology on its working principle and key elements in the language of control and robotics, to provide a shortcut for beginners to step into this research field.
Konstantin Danilov, Ruslan Rezin, Alexander Kolotov, Ilya Afanasyev
The decentralized trading market approach, where both autonomous agents and people can consume and produce services expanding own opportunities to reach goals, looks very promising as a part of the Fourth Industrial revolution. The key component of the approach is a blockchain platform that allows an interaction between agents via liability smart contracts. Reliability of a service provider is usually determined by a reputation model. However, this solution only warns future customers about an extent of trust to the service provider in case it could not execute any previous liabilities correctly. From the other hand a blockchain consensus protocol can additionally include a validation procedure that detects incorrect liability executions in order to suspend payment transactions to questionable service providers. The paper presents the validation methodology of a liability execution for agent-based service providers in a decentralized trading market, using the Model Checking method based on the mathematical model of finite state automata and Temporal Logic properties of interest. To demonstrate this concept, we implemented the methodology in the Duckietown application, moving an autonomous mobile robot to achieve a mission goal with the following behavior validation at the end of a completed scenario.
Eduardo Castelló Ferrer, Ognjen Rudovic, Thomas Hardjono, Alex Pentland
Robots have potential to revolutionize the way we interact with the world around us. One of their largest potentials is in the domain of mobile health where they can be used to facilitate clinical interventions. However, to accomplish this, robots need to have access to our private data in order to learn from these data and improve their interaction capabilities. Furthermore, to enhance this learning process, the knowledge sharing among multiple robot units is the natural step forward. However, to date, there is no well-established framework which allows for such data sharing while preserving the privacy of the users (e.g., the hospital patients). To this end, we introduce RoboChain - the first learning framework for secure, decentralized and computationally efficient data and model sharing among multiple robot units installed at multiple sites (e.g., hospitals). RoboChain builds upon and combines the latest advances in open data access and blockchain technologies, as well as machine learning. We illustrate this framework using the example of a clinical intervention conducted in a private network of hospitals. Specifically, we lay down the system architecture that allows multiple robot units, conducting the interventions at different hospitals, to perform efficient learning without compromising the data privacy.
Swarms of robots will revolutionize many industrial applications, from targeted material delivery to precision farming. However, several of the heterogeneous characteristics that make them ideal for certain future applications --- robot autonomy, decentralized control, collective emergent behavior, etc. --- hinder the evolution of the technology from academic institutions to real-world problems. Blockchain, an emerging technology originated in the Bitcoin field, demonstrates that by combining peer-to-peer networks with cryptographic algorithms a group of agents can reach an agreement on a particular state of affairs and record that agreement without the need for a controlling authority. The combination of blockchain with other distributed systems, such as robotic swarm systems, can provide the necessary capabilities to make robotic swarm operations more secure, autonomous, flexible and even profitable. This work explains how blockchain technology can provide innovative solutions to four emergent issues in the swarm robotics research field. New security, decision making, behavior differentiation and business models for swarm robotic systems are described by providing case scenarios and examples. Finally, limitations and possible future problems that arise from the combination of these two technologies are described.