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Swarming algorithms usually require fast and reliable local information distribution among neighbour-ing nodes. Additionally, many applications also require global information distribution in the shortest possible time. We show that communication links with a range which is small compared to the size of the swarm offer many advantages. We propose a...
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... sample run can be seen in figure 10. The plot shows the real time performance of DDOR (red) for a dynamically changing swarm of varying network graph degree (green). ...
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... expected the average degree of the network is closely linked to the average distance, as figure 11 shows. The plot in figure 12 shows the omnicast time (the time it takes to perform a full exchange of all local information) over the average distance between submarines. ...
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... expected the average degree of the network is closely linked to the average distance, as figure 11 shows. The plot in figure 12 shows the omnicast time (the time it takes to perform a full exchange of all local information) over the average distance between submarines. Outliers which are significantly higher than the majority of plot points are due to a reorganisation of the schedule, as the network changes. ...
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... might appear counter-intuitive that the best performance is reached as the swarm reaches its maximum size, but there is a logical explanation, as indicated before. Figure 13 shows the same experiment plotted against the average degree of the network. The left side of this plot roughly corresponds to the right-hand side of the previous plot. ...
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... results in quicker updates for nodes from their direct neighbours, which is important for swarm control. Figure 14 shows similar results for networks with 40 respectively 30 nodes. In all cases the maximum performance is reached for the largest-possible expansion of the network without disconnection. ...
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... startup is therefore the worst case test scenario for adaptability. Figure 15 shows the behaviour during the first 1000 time slots. During initialisation the number of collisions is high, while the schedules are established. ...
Citations
... The attenuation losses of the acoustic wave communication increase with the increasing of its frequency. And the attenuation loss is only 0.3 db/m for the frequency of 30 KHz carrier [14]. In this frequency, the acoustic wave communication can achieve long distance communication with relatively high output power. ...
... Hence, the network topology should be carefully engineered and post-deployment topology optimization should be performed, when possible [25]. Major challenges in the design of underwater acoustic networks can be listed as follows252627: Severely limited available bandwidth; Severely impaired underwater channel (especially due to time-varying multi-path and fading); High (five orders of magnitude higher than that of radio frequency (RF) terrestrial channels) and extremely variable propagation delay; High bit error rates and temporary losses of connectivity (shadow zones) due to the extreme characteristics of the underwater channel; Limited battery power, usually incapability of battery recharge due to unavailability of solar energy; ...
... Regarding the network protocols, the characteristics of the underwater environment shall be considered during the design in order: to restore the connectivity quickly when it is lost; and to react to unpaired or congested links by taking appropriate action (e.g., dynamical rerouting) in order to meet the given delay bound [25]. In underwater environment, low radio frequencies are less affected by attenuation (compared to high frequency radio frequencies), and offer a suitable alternative for short-range communication with acceptable power consumption and latency; but the limitations on the available bandwidth for data communication still exist [27]. The short range implies that large-scale networks are multi-hop wireless networks. ...
... It also implies that the channel can be space-multiplexed between participants sufficiently far apart. In terms of local and global information distribution in swarms, limited range radio links are actually an advantage [27]. Traditionally submarines have relied on acoustic waves for underwater communication. ...
Research on autonomous vehicles has been a key area of concern especially in the last two-three decades. Underwater vehicles took their share in such studies. In addition to single remotely-controlled and autonomous underwater vehicles, ongoing research deals with construction of coordinated missions to be performed by groups of such vehicles. In this study, which can be considered as a condensed review of the underwater robot swarms, we try to summarize the challenges and practical issues in this area. In addition, we try to illustrate the advantages of a swarm formation with a basic case study.
... For instance, at a carrier frequency of 30 kHz, the waves are attenuated only by 0.3 dB/m. On the other hand, acoustic communications might not be desired for some underwater vehicles for the following reasons [15][16][17]: ...
... On the other hand, it should be noted that high frequency radio waves suffer from severe attenuation in the underwater environment. Hence, the carrier frequency shall be carefully chosen [17]. ...
... Other challenges in the design of underwater acoustic networks can be listed as follows [15][16][17]: ...
Unmanned Underwater Vehicles (UUVs) have gained popularity for the last decades, especially for the purpose of not risking human life in dangerous operations. On the other hand, underwater environment introduces numerous challenges in navigation, control and communication of such vehicles. Certainly, this fact makes the development of these vehicles more interesting and engineering-wise more attractive. In this paper, we first revisit the existing technology and methodology for the solution of aforementioned problems, then we try to come up with a system solution of a generic unmanned underwater vehicles.
... The optimisation of an actual radio link implementation is beyond the scope of this thesis, but a proof of concept prototype has been developed and will be discussed in following sections. A more detailed approach on the design of a low frequency under water radio link is provided in [52]. ...
... The rather slow speed of sound additionally creates large propagation delays, which makes node synchronisation challenging. Generally acoustic communication does not scale well for large scale networks such as robotic swarms [13] [52]. ...
... The particular problems with long-wave radio communication are the limited bandwidth due to the low carrier frequency and the difficulty of designing efficient small antennas. Additionally, water as a medium for radio waves has effects on the signal quality, such as frequency-dependent dispersion and attenuation [51] [52]. It is therefore desirable to use a narrow bandwidth to reduce dispersion and signal alterations and to be able to use tuned high gain antennas. ...
In this paper, an improved Media Access (MAC) layer protocol with Time Division Multiple Access (TDMA) scheduling algorithm is proposed for swarms of Autonomous underwater Vehicles (AUV) using low frequency Electromagnetic (EM) waves. The exchange of global variables in swarms of underwater Autonomous Vehicles (AUV) becomes very useful for many practical purposes. So a scheduling algorithm with distributive control is used to achieve the necessary many to many exchange of global variable. The knowledge of the propagation delay which is present in the system is used to overlap node communication through scheduling and thereby increase the channel utilization. Modeling and simulation of the algorithm is presented and the results show that there is a significant increase in the channel throughput.
In this paper, the frog-call-inspired anti-phase synchronization algorithm is investigated and applied to allocate communication time slots among robotic swarms. The main goal of the work is to solve interference and jamming problems which becomes vital in swarm robot communication and sensing, especially in underwater application. A novel distributed model of this biologically-inspired approach is investigated to improve scalability and enable decentralization of the algorithm. It is proven from the simulated experiment that the model can be applied for scheduling underwater swarm communication within a limited local communication range, however with an acceptable amount (less than 5%) of packet loss. In the end, a real robot experiment using underwater swarm robot platforms is also presented.
Interference and jamming become very crucial issues in swarm robot communication and sensing, especially in underwater applications. In this paper, bio-inspired approaches are proposed to construct a robust communication scheduling to solve the problem. The scheduling mechanism is combined from two well-known bio-inspired algorithms, the firefly-inspired phase synchronization algorithm and the frog-call-inspired anti-phase synchronization algorithm. Novel distributed models for both algorithms are also investigated to improve scalability and provide decentralization of the algorithms. It is proven from a series of simulated experiments that the model is robust and viable for scheduling underwater swarm communication and sensing. In the end, a real robot experiment using underwater swarm robot platforms is also performed.
Collective robotics is young and promising research field, where many robots work as one team, group or swarm to achieve a common goal. Collective systems provide several essential advantages such as extended reliability, scalability, flexibility and reconfigurability, capabilities for emergent and self-organizing phenomena. Depending on size, complexity and underlying principles of interaction and information transfer, there are different small-, middle- and large-scale systems, denoted as cooperative, networked, swarm and nano-robotics. All these systems utilize different mechanisms of perception, coordination and learning. Lately, research on swarm, reconfigurable and evolutionary robotics leaded to an appearance of morphogenetic systems, so-called artificial organisms, with advanced homeostatic and adaptive functionality. Collective systems became attractive for different underwater, aerial and industrial applications as well as for new areas of nano- and biological (bacterial) robotics. This book describes basic principles underlying collective systems, discusses such issues as design of emergence, fault tolerance, self-properties, artificial evolution, appearance of robot cultures and indicates main application areas.
12.1 Introduction This chapter focusses on adaptivity as a pivotal enabler of future robotic systems. It is the fundamental premise of our vision that future robots will have to be capa-ble of autonomous adaptation, that is, able to change their control systems without human intervention. This vision has also been articulated by Nelson et al., cf. [Nel-son et al. (2009)], who phrased it as follows: Advanced autonomous robots may someday be required to negotiate environments and situations that their designers had not anticipated. The future designers of these robots may not have adequate expertise to provide appropriate control algo-rithms in the case that an unforeseen situation is encountered in a remote environ-ment in which a robot cannot be accessed. It is not always practical or even possible to define every aspect of an autonomous robot's environment, or to give a tractable dynamical systems-level description of the task the robot is to perform. The robot must have the ability to learn control without human supervision. To define adaptation –"learning control without human supervision"– clearly, consider a robot's controller as a process that maps inputs, read from the robot's sensors and internal states, to outputs, typically actuator and state set-tings. Adaptation is then defined as any changes to this mapping process, including the setting of its parameters.
This article discusses the complete processing chain of a high-precision as well as robust underwater localization method. Range and azimuth as well as relative heading are determined for ranges up to 90 m. For ranges up to 10 m the measured precision is 0.05 m for range, 2 deg for direction, and 5 deg for heading of neighboring vehicles. The system is also designed to be deployable in swarms of vehicles as acoustic localization signals are separated by time slots and maximum length sequence (MLS) signatures. The proposed method is based on the consequent exploitation of MLS broadband signal characteristics and the exploration of several methods for each vehicle to estimate ranges, azimuths, and headings of neighboring vehicles. An existing radio-based swarm communication system provides additional support and leads to enhanced measurement precision and interference robustness. The capabilities and limitations of the proposed systems are experimentally determined and discussed. © 2010 Wiley Periodicals, Inc.
