Ovidiu Vermesan, Reiner John, Patrick Pype, G. H. O. Daalderop · 11 authors
The automotive sector digitalization accelerates the technology convergence of perception, computing processing, connectivity, propulsion, and data fusion for electric connected autonomous and shared (ECAS) vehicles. This brings cutting-edge computing paradigms with embedded cognitive capabilities into vehicle domains and data infrastructure to provide holistic intrinsic and extrinsic intelligence for new mobility applications. Digital technologies are a significant enabler in achieving the sustainability goals of the green transformation of the mobility and transportation sectors. Innovation occurs predominantly in ECAS vehicles’ architecture, operations, intelligent functions, and automotive digital infrastructure. The traditional ownership model is moving toward multimodal and shared mobility services. The ECAS vehicle’s technology allows for the development of virtual automotive functions that run on shared hardware platforms with data unlocking value, and for introducing new, shared computing-based automotive features. Facilitating vehicle automation, vehicle electrification, vehicle-to-everything (V2X) communication is accomplished by the convergence of artificial intelligence (AI), cellular/wireless connectivity, edge computing, the Internet of things (IoT), the Internet of intelligent things (IoIT), digital twins (DTs), virtual/augmented reality (VR/AR) and distributed ledger technologies (DLTs). Vehicles become more intelligent, connected, functioning as edge micro servers on wheels, powered by sensors/actuators, hardware (HW), software (SW) and smart virtual functions that are integrated into the digital infrastructure. Electrification, automation, connectivity, digitalization, decarbonization, decentralization, and standardization are the main drivers that unlock intelligent vehicles' potential for sustainable green mobility applications. ECAS vehicles act as autonomous agents using swarm intelligence to communicate and exchange information, either directly or indirectly, with each other and the infrastructure, accessing independent services such as energy, high-definition maps, routes, infrastructure information, traffic lights, tolls, parking (micropayments), and finding emergent/intelligent solutions. The article gives an overview of the advances in AI technologies and applications to realize intelligent functions and optimize vehicle performance, control, and decision-making for future ECAS vehicles to support the acceleration of deployment in various mobility scenarios. ECAS vehicles, systems, sub-systems, and components are subjected to stringent regulatory frameworks, which set rigorous requirements for autonomous vehicles. An in-depth assessment of existing standards, regulations, and laws, including a thorough gap analysis, is required. Global guidelines must be provided on how to fulfill the requirements. ECAS vehicle technology trustworthiness, including AI-based HW/SW and algorithms, is necessary for developing ECAS systems across the entire automotive ecosystem. The safety and transparency of AI-based technology and the explainability of the purpose, use, benefits, and limitations of AI systems are critical for fulfilling trustworthiness requirements. The article presents ECAS vehicles’ evolution toward domain controller, zonal vehicle, and federated vehicle/edge/cloud-centric based on distributed intelligence in the vehicle and infrastructure level architectures and the role of AI techniques and methods to implement the different autonomous driving and optimization functions for sustainable green mobility.
Milan Groshev, Jorge Martín‐Pérez, Kiril Antevski, Antonio de la Oliva · 5 authors
Edge computing have received considerable attention as a promising candidate for the evolution of robotic systems. In this work, we propose COTORRA, an Edge driven robotic testbed that combines context information with robot sensor data to validate innovative concepts for robotic systems prior to being applied in a production environment. We have tested COTORRA in a controlled university environment as an easy applicable, serverless, and modular testbed on top of commodity network infrastructure. COTORRA supports pluggable robotic applications. To verify its feasibility and assess its performance, we ran a set of experiments that show how autonomous navigation applications can achieve target latencies bellow 15 ms, and perform an inter-domain Distributed Ledger Technology (DLT) federation within 19 seconds.
Vyacheslav Petrenko, Фариза Тебуева, Sergey Ryabtsev, Igor Struchkov
Abstract The technological development and popularity of swarm robotics actualizes the issues of increasing the efficiency and safety of consensus achievement between the swarm elements. Currently, most studies have little or no regard for information security issues when consensus achievement among swarm elements in the presence of robots with arbitrarily malfunctioning or malicious behavior. However, in many practical applications, when exploring the external environment, a swarm of one or more malicious robots may be sufficient to allow the current consensus mechanisms to fail. One of the promising ways to ensure information security in collective decision-making is the use of blockchain technology as a distributed system designed to work in conditions of lack of trust between the parties. The use of distributed ledger technologies, due to their complexity, leads to reducing efficiency in consensus achievement. The aim of the work is to improve the safety of the process of consensus achievement in swarms of robots through the use of blockchain technology in collective design making while maintaining the effectiveness of consensus achievement between robots. Increasing the safety of decision-making by a swarm will increase the stability and the possibilities of practical application of swarm robotic systems for solving problems in aggressive environments.
Benjamin Breiling, Bernhard Dieber, Martin Pinzger, Stefan Raß
With the growing popularity of robots, the development of robot applications is subject to an ever increasing number of additional requirements from e.g., safety, legal and ethical sides. The certification of an application for compliance to such requirements is an essential step in the development of a robot program. However, at this point in time it must be ensured that the integrity of this program is preserved meaning that no intentional or unintentional modifications happen to the program until the robot executes it. Based on the abstraction of robot programs as workflows we present in this work a cryptography-powered distributed infrastructure for the preservation of robot workflows. A client composes a robot program and once it is accepted a separate entity provides a digital signature for the workflow and its parameters which can be verified by the robot before executing it. We demonstrate a real-world implementation of this infrastructure using a mobile manipulator and its software stack. We also provide an outlook on the integration of this work into our larger undertaking to provide a distributed ledger-based compliant robot application development environment.
The active introduction of robotics swarm systems into life brings the issues of their information security up to date. Known security approaches often do not take into account the peculiarities of the implementation of swarm systems, such as collective design-making, and only consider the presence of Byzantine robots with a strategy of behavior consisting in voting against a majority when a consensus is reached. The aim of this work is to increase the security of the collective design-making process in a swarm robotics system from the imposition of false and ineffective alternatives by Byzantine robots with a random behavior strategy. It is proposed to use an approach based on the use of a distributed ledger and analysis of deviations in the process of collective design-making, which will allow identifying and isolating harmful effects. The solution to the problem of detecting Byzantine robots is based on the application of the criterion of the degree of confidence of a robot in choosing an alternative when a consensus is reached by the swarm system and is based on the assumption that the distribution of the degree of confidence of a Byzantine robot due to ignoring the parameters of the external environment and voting for random alternatives is significantly different from the behavior an ordinary robot. The elements of novelty of the presented solution include the use of the degree of confidence criterion to ensure the safety of collective design-making and the ability to take into account various strategies of behavior of Byzantine robots. The use of the presented solution makes it possible to increase the efficiency of reaching consensus by a swarm robotics system in the presence of Byzantine robots. The simulation for a swarm of 20 robots, including 5 Byzantine ones with random behavior, showed an increase in the probability of correctly reaching a consensus by 12.5%. The practical significance of the presented solutions lies in the possibility of ensuring the stability of reaching consensus by a swarm robotics system in the presence of robots with harmful behavior.
Saint Petersburg SPIIRAS, A.V. Smirnov, Nikolay Teslya, Saint Petersburg SPIIRAS
During a common goal achieving, a coalition of autonomous robots may face a situation that requires prompt decision-making in order to maintain an initially agreed action plan. In this case, it is proposed to use adaptive decentralized planning mechanisms based on the model of socio-inspired self-organization and implemented using the original protocol ofnegotiations between robots. Negotiations are carried out through the execution of smart contracts that process robots' proposalsюThe contracts are storing and distributing in a distributed ledger implemented with the HyperLedger Fabric platform.
Open access
Modular Robots and Swarm Intelligence
Advanced Research in Systems and Signal Processing
Abstract Fog robotics is an entirely new direction in the robotic field, inspired by the fogcomputing concept. Some fog architectures have been developed for robots groups and robot swarms, yet, to the best of our knowledge, there are no developed mechanisms of data sharing and replication in such structures. So, they are in the focus of this paper. The distributed ledger-based architecture for the fog robot servers is considered and described, as well as some models have been developed to estimate the time needed for data sharing. Simulation results show the expediency of consensus methods usage for distributed ledger-based.
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.
Factors affecting the reliability of data transmission in networks with nodes with periodic availability were considered. The principles of data transfer between robots are described; the need for global connectivity of communications within an autonomous system is shown, since the non-availability of information on the intentions of other robots reduces the effectiveness of the robotics system as a whole and affects the fault tolerance of a team of independent actors performing distributed activities. It is shown that the existing solutions to the problem of data exchange based on general-purpose IP networks have drawbacks; therefore, as the basis for organizing autonomous robot networks, we used developments in the domain of topological models of communication systems allowing us to build self-organizing computer networks. The requirements for the designed network for reliable message transfer between autonomous robots are listed, the option of organizing reliable message delivery using overlay networks, which expand the functionality of underlying networks, is selected. An overview of existing popular controlled and non-controlled overlay networks is given; their applicability for communication within a team of autonomous robots is evaluated. The features and specifics of data transfer in a team of autonomous robots are listed. The algorithms and architecture of the overlay self-organizing network were described by means of generally accepted methods of constructing decentralized networks with zero configurations. As a result of the work, general principles of operation of the designed network were proposed, the message structure for the delivery algorithm was described; two independent data streams were created, i.e. service and payload; an algorithm for sending messages between network nodes and an algorithm for collecting and synchronizing the global network status were developed. In order to increase the dependability and fault tolerance of the network, it is proposed to store the global network status at each node. The principles of operation of a distributed storage are described. For the purpose of notification on changes in the global status of the network, it is proposed to use an additional data stream for intra-network service messages. A flood routing algorithm was developed to reduce delays and speed up the synchronization of the global status of a network and consistency maintenance. It is proposed to provide network connectivity using the HELLO protocol to establish and maintain adjacency relations between network nodes. The paper provides examples of adding and removing network nodes, examines possible scalability problems of the developed overlay network and methods for solving them. It confirms the criteria and indicators for achieving the effect of self-organization of nodes in the network. The designed network is compared with existing alternatives. For the developed algorithms, examples of latency estimates in message delivery are given. The theoretical limitations of the overlay network in the presence of intentional and unintentional defects are indicated; an example of restoring the network after a failure is set forth.
The paper presents an approach of the blockchain and smart contracts utilization for dynamic robot coalition creation. The coalition is forming for solving complex tasks in industry applications that requires sequential united actions from the several robots. The main idea is that the process is split into two stages: scheduling and dynamic execution. On the scheduling stage, the coalition is defined based on the correlation of existing tasks and robot equipment, and the execution plan is formed and stored in smart contracts. The second stage is the plan execution. During this stage, smart contract controls how each robot solves its sub-task and whether it solves the sub-task due to the planned moment of time. In case of any deviation from the plan, smart contacts will provide a solution for returning to the plan or for changing the coalition composition with new robots and an execution plan. The prototype for execution control system has been developed based on the Hyperledger Fabric platform.
Abstract The paper considers the problem of distributed decision making in the robot swarm. The enhancement technique of the related study approach is proposed using the data transmission distance constraints and the weighted voting strategy. The decision making process is organized by means of distributed ledger usage. The information propagation through the swarm is implemented via spreading randomized rumor. The avoidance of routing in the swarm improves the overall energy efficiency of the system. The weighted voting transactions take into account the positions of the robots relating to the unknown objects or obstacles, as well as the voting history, which is stored in a distributed ledger
This paper presents a new consensus protocol based on verifiable delay function. First, we introduce the concept of verifiable delay puzzle (VDP), which resembles the hashing puzzle used in the PoW mechanism but can only be solved sequentially. We then present a VDP implementation based on the continuous verifiable delay function. Further, we show that VDP can be combined with the Nakamoto consensus in a proof-of-stake/proof-of-delay hybrid protocol. We analyze the persistence and liveness of the protocol, and show that compared to PoW, our proposal consumes much less energy; compared to BFT leader-election based consensus algorithms, our proposal achieves better resistance to long-range attacks and DoS attacks targeting the block proposers.
Sara Falcone, Yingsheng Zhang, Agnes Cameron, Amira Abdel-Rahman
This paper proposes a blockchain-based mapping protocol for distributed robotic systems running on embedded hardware. This protocol was developed for a robotic system designed to locomote on lattice structures for space applications. A consensus mechanism, Proof of Validity, is introduced to allow the effort of mining blocks to correlate with the desired tasks the robotic system was designed for. These robots communicate using peer-to-peer LoRa radio. Options, trade-offs and considerations for implementing blockchain technology on an embedded system with wireless radio communication are explored and discussed.
Jason A. Tran, Gowri Ramachandran, Palash M Shah, Claudiu Danilov · 6 authors
Blockchain technology has the potential to disrupt applications beyond cryptocurrencies. This work applies the concepts of blockchain technology to swarm robotics applications. Swarm robots typically operate in a distributed fashion, wherein the collaboration and coordination between the robots are essential to accomplishing the application goals. However, robot swarms may experience network partitions either due to navigational and communication challenges or in order to perform certain tasks efficiently. We propose a novel protocol, SwarmDAG, that enables the maintenance of a distributed ledger based on the concept of extended virtual synchrony while managing and tolerating network partitions.
Vicent Cholvi, Antonio Fernández Anta, Chryssis Georgiou, Nicolas Nicolaou
This work provides a proper formalization for Distributed Ledger Objects (as first defined in [Antonio Fernández Anta et al., 2018]), when processes may be Byzantine. The formal definitions are accompanied by algorithms to implement Byzantine Distributed Ledgers by utilizing a Byzantine Atomic Broadcast service.
Volker Strobel, Eduardo Castelló Ferrer, Marco Dorigo
While swarm robotics systems are often claimed to be highly fault-tolerant, so far research has limited its attention to safe laboratory settings and has virtually ignored security issues in the presence of Byzantine robots---i.e., robots with arbitrarily faulty or malicious behavior. However, in many applications one or more Byzantine robots may suffice to let current swarm coordination mechanisms fail with unpredictable or disastrous outcomes. In this paper, we provide a proof-of-concept for managing security issues in swarm robotics systems via blockchain technology. Our approach uses decentralized programs executed via blockchain technology (blockchain-based smart contracts) to establish secure swarm coordination mechanisms and to identify and exclude Byzantine swarm members. We studied the performance of our blockchain-based approach in a collective decision-making scenario both in the presence and absence of Byzantine robots and compared our results to those obtained with an existing collective decision approach. The results show a clear advantage of the blockchain approach when Byzantine robots are part of the swarm.
In this vision paper, we present an approach that makes it possible to protect developed ideas and early concepts even during their systematical development. We take the Design Thinking process as an example, in which interfaces are used for individual stages (understand, observe, define, ideate, prototype, test) to digitally record verbal, written or sketched, and even modeled or constructed outcome. This outcome is recorded and linked to the originating person. To guarantee both proof-of-existence and proof-of-origin, a unique hash is generated from each digital artifact stored and embedded into the Bitcoin Blockchain by the OriginStamp decentralized trusted timestamping service. Once this unique fingerprint is embedded in a transaction in the underlying Blockchain network, it can be proven where particular contributions originated due to the characteristics of Blockchain architecture. By setting up a decentralized tamper-proof means of record keeping, the entire innovation chain from the first ideation to the beginning of production is verifiably stored. By providing a clear proof-of-origin, all innovators (even competitors) could continue to work on existing problem-solving process and add their contribution proportionately, depending on the state of innovation development. This concept enables an Open Innovation ecosystem, which has the potential to increase the innovation potential of companies immensely. Additionally, inventions that are not patentable because they do not comply with the strict regulations of patent law can still be published and protected because the information about the origin of the respective contribution is guaranteed.
Open access
Computability, Logic, AI Algorithms
Physical Unclonable Functions (PUFs) and Hardware Security
The HPlane IoT framework abstracts security and privacy concerns of critical IoT infrastructure in a Remote Healthcare Monitoring (RHM) environment. Despite its usefulness, the framework lacks a scalable access control mechanism leading to performance and scalability challenges. Some of these challenges can be overcome by using Byzcoin blockchain that provides strong consistency guarantee. However, we found limitations in Byzcoin with respect to reliability, performance and high failure probability due to the use of unreliable Collective Cosigning (CoSi) protocol. Our practical analysis shows that on an average 10-30% CoSi protocols fail when it uses a spanning tree topology to scale Schnorr multisignature. Thus use of Byzcoin poses a significant risk to critical IoT infrastructure. In this paper, we present a robust spanning tree topology along with an implementation of BLS multisignature. Our enhanced topology successfully tackles reliability limitation while BLS multisignature improves performance and lowers failure probability. This work also summarizes how blockchains can serve as a controller application to provide an effective scalable access control in HPlane IoT framework.
This paper examines the current state of smart homes and proposes an alternative model based on biomimicry. It is argued that a house that is modeled on a basic living organism will be more efficient for the inhabitants, and more effective to insulate them from the unpredictable effects of climate change in the near future. By using an organism as a model, the house will be able to self-organize its systems, and adapt to both its inhabitants as well as environmental perturbations. This can be accomplished with the use of sensors and actuators in a decentralized configuration with artificial life programming. Since organisms are autonomous by definition, off-grid housing systems are infused to create a new housing model that is zero-emission, zerowaste, and can serve as a model for other forms of infrastructure at greater scales.
Modern ocean exploration and sensing approaches have been mainly based on Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), and/or static Underwater Acoustic Sensor Networks (UASNs) deployments. Individual AUVs and ROVs represent a single point of failure in addition to being bulky and expensive as vehicles are usually full-featured and sophisticated. UASNs have traditionally been statically deployed. This limits their use to original deployment locations and renders them unsuitable for search tasks. Swarm Robotics (SR) are a natural, better alternative. Swarms possess superior features over a sophisticated AUV; they are smaller, cheaper, robust, reliable, and scalable by design and definition. They also have the sensing capabilities of UASNs and built-in active mobility.\nDesigning successful swarm missions in harsh aquatic environments is an involved task. We address this by analyzing the indispensable stages of a typical mission and carefully designing decentralized algorithms to achieve the desired per-stage goals. Important system and environmental parameters are taken into consideration to achieve the end goal: completing mission requirements while respecting time constraint, with best possible performance and minimum loss of agents. Special attention is given to target search, task identification and allocation, and mission-stage integration due to their importance. Identifying target location in an unbounded environment is challenging. Bandwidth limited and intermittent communication complicates the process further. Therefore, we develop global search algorithms that use minimal communication and utilize flocking to maintain cohesion. These algorithms have multiple advantages over traditional ones in terms of convergence time, omni-directionality, consideration of physical constraints, and being self-bounding. At the target, tasks are autonomously identified and allocated in a completely decentralized manner. Validation of the developed techniques is done through realistic simulations and analytical comparisons.\nOur main contributions are: 1) a general framework for underwater mission planning, 2) three novel global search algorithms for unbounded underwater environment, 3) an algorithm for initial self-organization, 4) an optimized same-position reorientation algorithm for use in certain mission stages, 5) three autonomous task allocation algorithms, 6) three local target search algorithms, 7) a measure of mission utility, and 8) the design of a human brain-inspired model to support learning and complete autonomy.
Self-organization provides a suitable model for developing self-managed complex distributed systems, such as grid computing and sensor networks. Unlike current related studies, which propose only a single principle of self-organization, this mechanism synthesizes the three principles of self-organization: cloning/ spawning, resource exchange and relation adaptation. Based on this mechanism, an agent can autonomously generate new agents when it is overloaded, exchange resources with other agents if necessary, and modify relations with other agents to achieve a better agent network structure. In this way, agents can adapt to dynamic environments. The proposed mechanism is evaluated through a comparison with three other approaches, each of which represents state-of-the-art research in each of the three self-organization principles. Experimental results demonstrate that the proposed mechanism outperforms the three approaches in terms of the profit of individual agents and the entire agent network, the load-balancing among agents, and the time consumption to finish a simulation run. In addition, in a dynamic environment, it is nearly impossible to use a static, design time generated system structure for efficient problem solving. Instead, the system needs to be able to self-organize at runtime, which means that the components of the system are responsible for adapting themselves to suit the dynamic environment. Self-organization is usually defined as "the mechanism or the process enabling the system to change its organization without explicit external command during its execution time.
ubiant, Lyon,
France, Sébastien Mazac, Frédéric Armetta, Salima Hassas
The theory of cognitive development from Jean Piaget (1923) is a constructivist perspective of learning that has substantially influenced cognitive science domain.Indeed it seems that constructivism is a possible trail in order to overcome the limitations of classical techniques stemming from cognitivism or connectionism and create autonomous agents, fitted with strong adaptation ability within their environment, modelled on biological organisms.Potential applications concern intelligent agents in interaction with a complex environment, with objectives that cannot be predefined.There are numerous interesting works in developmental robotics going in this direction.In this work we investigate the application of these principles to a close domain: Ambient intelligence, which is extremely challenging but which also presents interesting aspects to exploit, like the participation of human users.From the perspective of a constructivist theory, the learning agent has to build a representation of the world that relies on the learning of sensori-motor patterns starting from its own experience only.This step is difficult to set up for systems evolving in continuous environments, using raw data from sensors without a priori modelling, primarily because they face a bootstrap problem.In this paper we address this particular issue and propose a decentralized approach based on a multi-agent framework, where the system's representations are constructed through a self-organization process that handles the dynamics between experience discretization and learning.