Distributed multi-robot formation control in dynamic environments

Alonso–Mora, Javier; Montijano, Eduardo; Nägeli, Tobias; Hilliges, Otmar; Schwager, Mac; Rus, Daniela

doi:10.1007/s10514-018-9783-9

Cited by 109 publications

(84 citation statements)

References 48 publications

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“…The formula is shown in Equation (3). F i (X) = AES(S N ID , i) + K i,CID * δ(X) = a n−1 X n−1 + a n−2 X n−2 + ... + a 1 X + a 0 (3) where S N ID is the private information held by each component, i is the time slot value, and {a 0 , a 1 , ..., a n−1 } is the polynomial coefficient. When the number of normal components in the cluster m is greater than the number of components being attacked, then n = m + 2; otherwise, n = p + 3.…”

Section: Key Update Instructionmentioning

confidence: 99%

See 1 more Smart Citation

Secure Key Establishment Mechanism for Smart Sensing System Based Robots Network

Qin

et al. 2020

Sensors

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The smart robot is playing an increasingly important role in the social economy, and multi-robot systems will be an important development in robotics. With smart sensing systems, the communications between sensors, actuators, and edge computing systems and robots are prone to be attacked due to the highly dynamic and distributed environment. Since smart robots are often distributed in open environments, as well as due to their limited hardware resources and security protection capabilities, the security requirements of their keys cannot be met with traditional key distribution algorithms. In this paper, we propose a new mechanism of key establishment based on high-order polynomials to ensure the safe key generation and key distribution. Experiments show that the key establishment mechanism proposed in this paper guarantees the security of keys; its storage cost and communication cost are smaller than state-of-the-art mechanisms; and it allows robot components to join and leave the network dynamically, which is more suitable for multi-robot systems. life, and the information security vulnerabilities may lead to leaks, which may cause harm to people in serious cases. Therefore, the safe operation of multi-robot systems requires that the communication among sensors, actuators, and edge computing systems in the system be safe and reliable, and the security of multi-robot networks receives more and more attention from researchers.Cryptographic algorithms are the important means to solve the network security problems. The most critical factor is the security of keys. In multi-node networks, the research on key security has gained significant development. Zhang [6] provided a practical design guide for a secure key generation system that can be changed by a different design. Thai [7] proposed a group key generation mechanism in the physical layer to deliver information through multiple antennas in a wireless network topology. Eschenauer [8] proposed a key pre-distribution algorithm, which performs key pre-distribution by establishing a key pool, but this key pre-distribution algorithm cannot guarantee 100% interworking between nodes. Sencun [9] proposed a localized encryption and authentication protocol (LEAP) to solve the problem of different security requirements when exchanging different types of data between nodes. However, after the initial deployment of the node, the interworking issues when the node and key changes cannot be solved. Jiyong [10] proposed a time-based key management protocol, but the protocol has connectivity issues for node deployment between different time slots. Naor [11] proposed a description schemes for distributing between n servers the evaluation of a function f, which can be used to distribute the operation of a KDC. However, this schemes cannot identify the attacked node in time, and it cannot update the key in time when a component being attacked appears, to avoid the information leakage.Currently, there is much research on key pre-distribution schemes in wireless sensor networks, and so...

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Section: Key Update Instructionmentioning

confidence: 99%

“…With the increasing application of multi-robot systems, there have been many studies in this field, including the study of robot motion trajectories [3], the cooperation of multi-robots [4], and robot safety research. This article focuses on the information security of multi-robot systems.…”

Section: Introductionmentioning

confidence: 99%

Secure Key Establishment Mechanism for Smart Sensing System Based Robots Network

Qin

et al. 2020

Sensors

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“…Classical global planner algorithms are, in general, no longer directly applicable. In these cases, it is necessary to implement alternative algorithms for navigation, such as wall‐ or corridor‐following (e.g., Pasteau, Narayanan, Babel, & Chaumette, ) based only on local information or specifically taking into account the walls, crosses, and lateral galleries that the robots encounter while navigating (Tardioli et al, ) or just relying on relative localization (Alonso‐Mora et al, ). Contrarily, the walls play a double role for the obstacle avoidance algorithms: They can help defining navigation goals and also represent obstacles to avoid.…”

Section: Challengesmentioning

confidence: 99%

Ground robotics in tunnels: Keys and lessons learned after 10 years of research and experiments

Tardioli

Riazuelo

Sicignano

et al. 2019

Journal of Field Robotics

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The work reported in this article describes the research advances and the lessons learned by the Robotics, Perception and Real-Time group over a decade of research in the field of ground robotics in confined environments. This study has primarily focused on localization, navigation, and communications in tunnel-like environments. As will be discussed, this type of environment presents several special characteristics that often make well-established techniques fail. The aim is to share, in an open way, the experience, errors, and successes of this group with the robotics community so that those that work in such environments can avoid (some of) the errors made. At the very least, these findings can be readily taken into account when designing a solution, without needing to sift through the technical details found in the papers cited within this text.

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“…Theorem 2. If system (14) is a directed graph and there is a spanning tree, the system can achieve consensus when the system delay τ d is smaller than the τ max under the action of noise ζ(t), and k 1 ∈ (0, k 0 k 2 2 ). Among them:…”

Section: Consensus Analysis Of Multi-robot With Various Delays and Nomentioning

confidence: 99%

“…As a result, they have better application prospects and higher research value in the fields of reconnaissance, patrol, rescue and environmental survey. Formation control of multi-mobile robots is the basis of multi-mobile robot systems, and has become a hotspot in the field of robotics [2].…”

Section: Introductionmentioning

confidence: 99%

Consensus Algorithms Based Multi-Robot Formation Control under Noise and Time Delay Conditions

Wei¹,

Lv²,

Duo³

et al. 2019

Applied Sciences

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In recent years, the formation control of multi-mobile robots has been widely investigated by researchers. With increasing numbers of robots in the formation, distributed formation control has become the development trend of multi-mobile robot formation control, and the consensus problem is the most basic problem in the distributed multi-mobile robot control algorithm. Therefore, it is very important to analyze the consensus of multi-mobile robot systems. There are already mature and sophisticated strategies solving the consensus problem in ideal environments. However, in practical applications, uncertain factors like communication noise, communication delay and measurement errors will still lead to many problems in multi-robot formation control. In this paper, the consensus problem of second-order multi-robot systems with multiple time delays and noises is analyzed. The characteristic equation of the system is transformed into a quadratic polynomial of pure imaginary eigenvalues using the frequency domain analysis method, and then the critical stability state of the maximum time delay under noisy conditions is obtained. When all robot delays are less than the maximum time delay, the system can be stabilized and achieve consensus. Compared with the traditional Lyapunov method, this algorithm has lower conservativeness, and it is easier to extend the results to higher-order multi-robot systems. Finally, the results are verified by numerical simulation using MATLAB/Simulink. At the same time, a multi-mobile robot platform is built, and the proposed algorithm is applied to an actual multi-robot system. The experimental results show that the proposed algorithm is finally able to achieve the consensus of the second-order multi-robot system under delay and noise interference.

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Distributed multi-robot formation control in dynamic environments

Cited by 109 publications

References 48 publications

Secure Key Establishment Mechanism for Smart Sensing System Based Robots Network

Secure Key Establishment Mechanism for Smart Sensing System Based Robots Network

Ground robotics in tunnels: Keys and lessons learned after 10 years of research and experiments

Consensus Algorithms Based Multi-Robot Formation Control under Noise and Time Delay Conditions

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