Review on state-of-the-art dynamic task allocation strategies for multiple-robot systems

Seenu, N; Chetty, Raghuram; Ramya, M. M.; Janardhanan, Mukund Nilakantan

doi:10.1108/ir-04-2020-0073

Cited by 58 publications

(9 citation statements)

References 79 publications

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“…While multiple-robot systems (MRS) can reduce the overall complexity of a task, their need for collaboration and accurate coordination [41] can add significantly to the programming workload. Further compounding the technical complexity of MRS is the need to select a suitable task allocation strategy that is robust, scalable and can be optimised for a specific task [42]. A cluster-based approach, centred around the location of tasks relative to team members, allocates tasks by training a binary classifier to nominate one of two task allocation mechanisms through an auction bidding process [43].…”

Section: Cobot Task Complexitymentioning

confidence: 99%

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

et al. 2023

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While traditional industrial robots participate in repetitive manufacturing processes from behind caged safety enclosures, collaborative robots (cobots) offer a highly flexible and human-interactive solution to manufacturing automation. Rather than operating from within cages, safety features such as force and proximity sensors and programmed protection zones allow cobots to work safely, close to human workers. Cobots can be configured to either stop or slow their motion if they come in contact with a human or obstacle or enter a protection zone, which may be a high pedestrian traffic area. In this way, a task can be divided into sub-processes allocated to the cobot or the human based on suitability, capability or human preference. The flexible nature of the cobot makes it ideal for low-volume, ‘just-in-time’ manufacturing; however, this requires frequent reprogramming of the cobot to adapt to the dynamic processes. This paper reviews relevant cobot programming and control methods currently used in the manufacturing industry and alternative solutions proposed in the literature published from 2018 to 2023. The paper aims to (1) study the features and characteristics of existing cobot programming and control methods and those proposed in the literature, (2) compare the complexity of the task that the cobot is to perform with the skills needed to program it, (3) determine who is the ideal person to perform the programming role, and (4) assess whether the cobot programming and control methods are suited to that person’s skillset or if another solution is needed. The study is presented as a guide for potential adopters of cobots for manufacturing and a reference for further research.

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Section: Cobot Task Complexitymentioning

confidence: 99%

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

et al. 2023

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“…The task allocation strategies can be classified according to their applications [14]. Optimization-and auction-based techniques are described as the most important task allocation strategies [4,5,15].…”

Section: Task Allocationmentioning

confidence: 99%

“…Accordingly, the task assignment problem (also known as the task allocation problem) is to find the most suitable robot to respond to the event. This problem is in robotic literature well known as a multirobot task allocation problem, and in [3,4] and [5], are reviewed and presented the existing solutions and their variations in WSRN.…”

Section: Introductionmentioning

confidence: 99%

Routing with Face Traversal and Auctions Algorithms for Task Allocation in WSRN

Stanulovic

Mitton

Mezei

2021

Sensors

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Four new algorithms (RFTA1, RFTA2, GFGF2A, and RFTA2GE) handling the event in wireless sensor and robot networks based on the greedy-face-greedy (GFG) routing extended with auctions are proposed in this paper. In this paper, we assume that all robots are mobile, and after the event is found (reported by sensors), the goal is to allocate the task to the most suitable robot to act upon the event, using either distance or the robots' remaining energy as metrics. The proposed algorithms consist of two phases. The first phase of algorithms is based on face routing, and we introduced the parameter called search radius (SR) at the end of this first phase. Routing is considered successful if the found robot is inside SR. After that, the second phase, based on auctions, is initiated by the robot found in SR trying to find a more suitable one. In the simulations, network lifetime and communication costs are measured and used for comparison. We compare our algorithms with similar algorithms from the literature (k-SAAP and BFS) used for the task assignment. RFTA2 and RFTA2GE feature up to a seven-times-longer network lifetime with significant communication overhead reduction compared to k-SAAP and BFS. Among our algorithms, RFTA2GE features the best robot energy utilization.

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“…Multi-robot task allocation can effectively schedule robot teams and solve scheduling and negotiation problems for robots in special situations such as working conditions saturation, task conflicts, insufficient capabilities and faults. Therefore, the quality of task allocation strategies greatly affects the operational efficiency and actual performance of multi-robot systems (Janardhanan et al , 2020). The solution to the multi-robot Assignment problem includes a task allocation method based on market mechanism, a task allocation method based on clustering and a heuristic algorithm based on optimization.…”

Section: Introductionmentioning

confidence: 99%

Research on dual robot collaboration method based on improved double ant colony algorithm

Jia,

Tang,

Zhang

et al. 2024

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Purpose This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations. Design/methodology/approach A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy. Findings The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems. Originality/value This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

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Review on state-of-the-art dynamic task allocation strategies for multiple-robot systems

Cited by 58 publications

References 79 publications

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

Routing with Face Traversal and Auctions Algorithms for Task Allocation in WSRN

Research on dual robot collaboration method based on improved double ant colony algorithm

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