Optimization of Power Utilization in Multimobile Robot Foraging Behavior Inspired by Honeybees System

Ahmad, Faisul Arif; Ramli, Abdul Rahman; Samsudin, Khairulmizam; Hashim, Shaiful Jahari

doi:10.1155/2014/153162

Cited by 3 publications

(4 citation statements)

References 27 publications

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“…To demonstrate the amenability of the charging pad to be used in various swarm robotic scenarios, where the robot remains on a charging cell for a long period of time (e.g. as a food source, a nest, or a defined charging station [50][51][52][53]), an experiment was conducted to evaluate the pad's thermal profile. A Mona robot was placed, stationary, in the middle of a charging cell and the battery level and charging pad's temperature were recorded.…”

Section: Hardware Feasibilitymentioning

confidence: 99%

Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging

Arvin

Watson

Turgut

et al. 2017

J Intell Robot Syst

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Swarm robotics studies the intelligent collective behaviour emerging from long-term interactions of large number of simple robots. However, maintaining a large number of robots operational for long time periods requires significant battery capacity, which is an issue for small robots. Therefore, recharging systems such as automated battery-swapping stations have been implemented. These systems require that the robots interrupt, albeit shortly, their activity, which influences the swarm behaviour. In this paper, a low-cost on-thefly wireless charging system, composed of several charging cells, is proposed for use in swarm robotic research studies. To determine the system's ability to support perpetual swarm operation, a probabilistic model that takes into account the swarm size, robot behaviour and charging area configuration, is outlined. Based on the model, a prototype system with 12 charging cells and a small mobile robot, Mona, was developed. A series of long-term experiments with different arenas and behavioural configurations indicated the model's accuracy and demonstrated the system's ability to support perpetual operation of multi-robotic system.

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Section: Hardware Feasibilitymentioning

confidence: 99%

Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging

Arvin

Watson

Turgut

et al. 2017

J Intell Robot Syst

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“…To avoid a long wait time and to showcase the replacement process, the battery threshold for replacement is set to 11.5 volts (having a maximum voltage of 12 volts). If there are no charged robots present at the hub for the replacement(s) of a low battery robot(s), the formation will stop and wait for the replacement robot to be available 1 . Some assumptions are made to showcase the efficacy of presented solution on real robots:…”

Section: Robots Carrying Payloadmentioning

confidence: 99%

“…However, this can be extended to multiple batteries on a single robot. The concept of working robots in the home area and foraging area is discussed in [1], where the robots in the home area move to perform a task and robots in a foraging area search for known or unknown power stations. As the power of the robots in the home area is reduced to a certain threshold, the forage robots help them to find the nearest power station.…”

Section: Related Workmentioning

confidence: 99%

Loosely Coupled Payload Transport System with Robot Replacement

Verma¹,

Tallamraju²,

Rawat³

et al. 2019

Preprint

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In this work, we present an algorithm for robot replacement to increase the operational time of a multi-robot payload transport system. Our system comprises a group of non-holonomic wheeled mobile robots traversing on a known trajectory. We design a multi-robot system with loosely coupled robots that ensures the system lasts much longer than the battery life of an individual robot. A system level optimization is presented, to decide on the operational state (charging or discharging) of each robot in the system. The charging state implies that the robot is not in a formation and is kept on charge whereas the discharging state implies that the robot is a part of the formation. Robot battery recharge hubs are present along the trajectory. Robots in the formation can be replaced at these hub locations with charged robots using a replacement mechanism. We showcase the efficacy of the proposed scheduling framework through simulations and experiments with real robots.

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“…The common complex collective behaviors are aggregation [3], foraging [4], flocking [5], cooperation [6], and stigmergy [7]. Models of this system have been proven to solve a difficult and complex real-world problem such as optimization [8,9], and target search [10,11]. The main representatives of SI approaches are particle swarm optimization (PSO) [12], bees algorithm (BA) [13], artificial bee colony optimization (ABC) [14], ant colony optimization (ACO) [15,16], bacterial foraging optimization (BFO) [4], glowworm swarm optimization (GSO) [17], and firefly algorithm (FA) [18].…”

Section: Introductionmentioning

confidence: 99%

Systematic Literature Review of Swarm Robotics Strategies Applied to Target Search Problem with Environment Constraints

Ismail

Hamami

2021

Applied Sciences

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Target searching is a well-known but difficult problem in many research domains, including computational intelligence, swarm intelligence, and robotics. The main goal is to search for the targets within the specific boundary with the minimum time that is required and the obstacle avoidance that has been equipped in place. Swarm robotics (SR) is an extension of the multi-robot system that particularly discovers a concept of coordination, collaboration, and communication among a large number of robots. Because the robots are collaborating and working together, the task that is given will be completed faster compared to using a single robot. Thus, searching for single or multiple targets with swarm robots is a significant and realistic approach. Robustness, flexibility, and scalability, which are supported by distributed sensing, also make the swarm robots strategy suitable for target searching problems in real-world applications. The purpose of this article is to deliver a systematic literature review of SR strategies that are applied to target search problems, so as to show which are being explored in the fields as well as the performance of current state-of-the-art SR approaches. This review extracts data from four scientific databases and filters with two established high-indexed databases (Scopus and Web of Science). Notably, 25 selected articles fell under two main categories in environment complexity, namely empty space and cluttered. There are four strategies which have been compiled for both empty space and cluttered categories, namely, bio-inspired mechanism, behavior-based mechanism, random strategy mechanism, and hybrid mechanism.

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Optimization of Power Utilization in Multimobile Robot Foraging Behavior Inspired by Honeybees System

Cited by 3 publications

References 27 publications

Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging

Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging

Loosely Coupled Payload Transport System with Robot Replacement

Systematic Literature Review of Swarm Robotics Strategies Applied to Target Search Problem with Environment Constraints

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