Formation and organisation in robot swarms.

A swarm is defined as a large and independent collection of heterogeneous or homogeneous agents operating in a common environment and seemingly acting in a coherent and coordinated manner. Swarm architectures promote decentralisation and self-organisation which often leads to emergent behaviour. The emergent behaviour of the swarm results from the interactions of the swarm with its environment (or fellow agents), but not as a direct result of design. The creation of artificially simulated swarms or practical robot swarms has become an interesting topic of research in the last decade. Even though many studies have been undertaken using a practical approach to swarm construction, there are still many problems need to be addressed. Such problems include the problem of how to control very simple agents to form patterns; the problem of how an attractor will affect flocking behaviour; and the problem of bridging formation of multiple agents in connecting multiple locations. The central goal of this thesis is to develop early novel theories and algorithms to support swarm robots in. pattern formation tasks. To achieve this, appropriate tools for understanding how to model, design and control individual units have to be developed. This thesis consists of three independent pieces of research work that address the problem of pattern formation of robot swarms in both a centralised and a decentralised way.The first research contribution proposes algorithms of line formation and cluster formation in a decentralised way for relatively simple homogenous agents with very little memory, limited sensing capabilities and processing power. This research utilises the Finite State Machine approach.In the second research contribution, by extending Wilensky's (1999) work on flocking, three different movement models are modelled by changing the maximum viewing angle each agent possesses during the course of changing its direction. An object which releases an artificial potential field is then introduced in the centre of the arena and the behaviours of the collective movement model are studied.The third research contribution studies the complex formation of agents in a task that requires a formation of agents between two locations. This novel research proposes the use Of L-Systems that are evolved using genetic algorithms so that more complex pattern formations can be represented and achieved. Agents will need to have the ability to interpret short strings of rules that form the basic DNA of the formation

Bit Communication in Artificial Swarm

Bit communication in swarm agents is a communication process of transmitting data within specific area. The data must be delivered to all agents in the area which this process also closely related to broadcasting manner through bit-communication as a way to spread out the data among all those agents. This research field is supposed to have a deep study of behavior of homogeneous agents by inspecting the reversing and non-reversing approach. It also included the investigation of the independent and characteristic of transmitting and receiving data for random process of swarm. In this paper, swarm technique is implemented which is useful for bit-communication behavior. There are two approaches are used for transmitting and receiving process. For the reverse approach, the data can be resend back to the sender for the next cycle where the program randomly select one-of nearest agent for transmitting the data. While in non-reversing approach, the data cannot retransmit back to the sender in the previous cycle; this approach may increase the system performance and efficiency

Solving Vehicle Routing Problem using Ant Colony Optimisation (ACO) Algorithm

Engineering field usually requires having the best design for an optimum performance, thus optimization plays an important part in this field. The vehicle routing problem (VRP) has been an important problem in the field of distribution and logistics since at least the early 1960s. Hence, this study was about the application of ant colony optimization (ACO) algorithm to solve vehicle routing problem (VRP). Firstly, this study constructed the model of the problem to be solved through this research. The study was then focused on the Ant Colony Optimization (ACO). The objective function of the algorithm was studied and applied to VRP. The effectiveness of the algorithm was increased with the minimization of stopping criteria. The control parameters were studied to find the best value for each control parameter. After the control parameters were identified, the evaluation of the performance of ACO on VRP was made. The good performance of the algorithm reflected on the importance of its parameters, which were number of ants (nAnt), alpha (α), beta (β) and rho (ρ). Alpha represents the relative importance of trail, beta represents the importance of visibility and rho represents the parameter governing pheromone decay. The route results of different iterations were compared and analyzed the performance of the algorithm. The best set of control parameters obtained is with 20 ants, α = 1, β = 1 and ρ = 0.05. The average cost and standard deviation from the 20 runtimes with best set of control parameters were also evaluated, with 1057.839 km and 25.913 km respectively. Last but not least, a conclusion is made to summarize the achievement of the study

CONCEPTUAL DESIGN OF AUTONOMOUS CART FOLLOWER FOR WHEELCHAIR USER

This paper focuses on kinematics of the cart follower and the system identification of propulsion system by using brushed DC motor. The cart follower uses Ackermann configuration as the steering system. The modeling of kinematics equation takes into account the instantaneous center of rotation (ICR), velocity of each tire, heading angle, and simple movement of the cart. The cart is propelled by transaxle brushed DC motor. It is important to approximate an accurate transfer function to represent the motor as the plant module is unavailable. The motor is simulated by using Arduino hardware package in MATLAB®. Rotary encoder is used to record the angular velocity of the shaft. MATLAB® code is created in order to calculate the linear velocity and tabulate the datasets. System Identification Toolbox determines the transfer function of the motor and its performance. The variables measured in experiment to identify the transfer function of the DC motor system are output angular velocity and input voltage. The parameters taken from the DC motor’s mathematical model are derived based on existing literatures. The graph of output velocity against time is plotted and the transfer function is estimated by using System Identification Toolbox in MATLAB®. From the results, it is demonstrated that the motor exhibits second order system

Time-aware Traffic Shaper using Time-based Packet Scheduling on Intel I210

By 2015, the Institute of Electrical and Electronics Engineers (IEEE) time-sensitive networking (TSN) task group has released several TSN standards. Amongst them is 802.1Qbv, also known as a time-aware shaper, aiming to provide performance assurances of latency and delivery variation to enable applications in a TSN network. While there are several products and evaluation kits that employ 802.1Qbv in the market now, it is still not widely adopted yet due to the maturity of the standard. Hardware-enabled 802.1Qbv use hardware queues and timers to achieve accurate transmission of packets in the switch and bridge. This research aims to investigate the feasibility of using an existing end-station Ethernet controller, Intel I210, and its launch time control feature (commonly known as time-based packet scheduling) to shape traffic compatible to 802.1Qbv-enabled network bridges. A software solution is developed by implementing a software configurable gate-control list and employing open-source Linux RFC patches for per-packet transmit time specification. By configuring the kernel and mapping kernel-layer traffic classes to the hardware queues, packets can be transmitted out at precise times while attaching 802.1Q VLAN tags, required by bridges to identify packets. Through analysis, it is found that this solution will require an additional 30 μs transmit offset to be used effectively. That is 55% more time is needed to transmit a packet in a back-to-back connection and 17.6% on a 3-switch network to improve period peak jitter performance to just 8.9  μs compared to 1 ms on solutions that send packets out periodically using software sleep functions

Formation and organisation in robot swarms

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PAPR PERFORMANCE ANALYSIS FOR COMBINATION OF SELECTIVE MAPPING (SLM) AND EXPONENTIAL COMPANDING TECHNIQUE

OFDM is a multicarrier transmission scheme that increase data transmission rate. However, OFDM has high PAPR problem which can cause signal distortion. A PAPR reduction scheme known as SLM-Exp was introduce in this paper to overcome high PAPR problem of OFDM. To evaluate the PAPR performance of SLM-Exp, SLM-Exp scheme along with SLM-Mu and Exponential were simulated in MATLAB for PAPR value at 1 X 10 -3of CCDF plot. PAPR performance of SLM-Exp was compare with SLM-Mu, and Exponential scheme as number of subcarrier, phase sequence and modulation scheme varied. The number of subcarrier concern in this project were 64, 128, 256, and 512. Number of phase sequence concern in this project were 8, 16 and 32. For modulation scheme, QPSK, 16 QAM, and 64 QAM were concern in this project. The result shows that PAPR value of SLM-Exp at 1 X 10-3of CCDF plot was better than SLM-Muby 0.53dB to 2.31dB and 0.10dB to 0.61dB for Exponential scheme as number of subcarrier varied. Result also shows that PAPR performance of SLM-Exp is better than SLM-Mu by 0.99dB to 1.63dB as number of phase sequence varied

Numerical Investigation of Thermal Efficiency of a Solar Cell

Solar air and water heaters are beneficial in many countries across the globe where solar radiation is massive in the daytime. As the surface temperature of the photovoltaic cell increases, the efficiency of the cell scales down. We carried out the cooling of solar panels in order to maximize their efficiency. In the present work, we examined the dependence of the inlet boundary condition on the area average temperature at the outlet of the tube. The tube comprises a square cross-section and carries three folds in order to maximize the area in contact with a solar panel. We investigated the dependency of thermal efficiency of solar panels on inlet boundary conditions and observed that with the increase in Reynolds number, i.e., velocity at the inlet, the thermal efficiency initially increases up to Re = 700 and then remains constant at 94%. We also found that when 40% of the heat input was carried away by cooling water, 20% electrical efficiency was achieved

Image Processing of UAV Imagery for River Feature Recognition of Kerian River, Malaysia

The impact of floods is the most severe among the natural calamities occurring in Malaysia. The knock of floods is consistent and annually forces thousands of Malaysians to relocate. The lack of information from the Ministry of Environment and Water, Malaysia is the foremost obstacle in upgrading the flood mapping. With the expeditious evolution of computer techniques, processing of satellite and unmanned aerial vehicle (UAV) images for river hydromorphological feature detection and flood management have gathered pace in the last two decades. Different image processing algorithms—structure from motion (SfM), multi-view stereo (MVS), gradient vector flow (GVF) snake algorithm, etc.—and artificial neural networks are implemented for the monitoring and classification of river features. This paper presents the application of the k-means algorithm along with image thresholding to quantify variation in river surface flow areas and vegetation growth along Kerian River, Malaysia. The river characteristic recognition directly or indirectly assists in studying river behavior and flood monitoring. Dice similarity coefficient and Jaccard index are numerated between thresholded images that are clustered using the k-means algorithm and manually segmented images. Based on quantitative evaluation, a dice similarity coefficient and Jaccard index of up to 97.86% and 94.36% were yielded for flow area and vegetation calculation. Thus, the present technique is functional in evaluating river characteristics with reduced errors. With minimum errors, the present technique can be utilized for quantifying agricultural areas and urban areas around the river basin