scholarly journals A Multiplicatively Weighted Voronoi-Based Workspace Partition for Heterogeneous Seeding Robots

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1813
Author(s):  
Jeongeun Kim ◽  
Chanyoung Ju ◽  
Hyoung Il Son
Keyword(s):  
Clustering Algorithm ◽  
Field Experiments ◽  
Allocation Scheme ◽  
Agricultural Robots ◽  
Distribution Strategy ◽  
Node Clustering ◽  
Robot Systems ◽  
Heterogeneous Robots ◽  
Workload Distribution ◽  
Seed Points

Multi-robot systems (MRSs) are currently being used to perform agricultural tasks. In this regard, the deployment of heterogeneous MRSs will be essential for achieving more efficient and innovative farming in the future. In this paper, we propose a multiplicatively weighted (MW) Voronoi-based task-allocation scheme for heterogeneous agricultural robots. The seed points for area partitioning using a Voronoi diagram are obtained by performing node clustering using a k-means clustering algorithm. Heterogeneous robots have different specifications for performing various tasks. Thus, the proposed MW Voronoi-based area partitioning for heterogeneous robots is applied by considering various weighting factors. The path for each robot is computed such that the robot follows the nodes, and the computed paths serve as inputs for the workload distribution strategy that assigns paths to the robots. Simulations and field experiments were conducted to verify the effectiveness of the proposed approach.

Optimal distributed interconnectivity of multi-robot systems by spatially-constrained clustering

2017 ◽  
Vol 25 (2) ◽  
pp. 96-113 ◽  
Author(s):  
Matin Macktoobian ◽  
Mahdi Aliyari Sh
Keyword(s):  
Clustering Algorithm ◽  
Task Assignment ◽  
Constrained Clustering ◽  
Loosely Coupled ◽  
Robot Systems ◽  
Multi Agent ◽  
Probabilistic Proof ◽  
Data Passing ◽  
Spatially Constrained Clustering ◽  
Multi Robot

A spatially-constrained clustering algorithm is presented in this paper. This algorithm is a distributed clustering approach to fine-tune the optimal distances between agents of the system to strengthen the data passing among them using a set of spatial constraints. In fact, this method will increase interconnectivity among agents and clusters, leading to improvement of the overall communicative functionality of the multi-robot system. This strategy will lead to the establishment of loosely-coupled connections among the clusters. These implicit interconnections will mobilize the clusters to receive and transmit information within the multi-agent system. In other words, this algorithm classifies each agent into the clusters with the lowest cost of local communication with its peers. This research demonstrates that the presented decentralized method will actually boost the communicative agility of the swarm by probabilistic proof of the acquired optimality. Hence, the common assumption regarding the full-knowledge of the agents’ primary locations has been fully relaxed compared to former methods. Consequently, the algorithm’s reliability and efficiency is confirmed. Furthermore, the method’s efficacy in passing information will improve the functionality of higher-level swarm operations, such as task assignment and swarm flocking. Analytical investigations and simulated accomplishments, corresponding to highly-populated swarms, prove the claimed efficiency and coherence.

A Node Clustering Algorithm for the CANON Architecture

2013 ◽  
Vol 17 (4) ◽  
pp. 785-788 ◽  
Author(s):  
Andreas Drakos ◽  
Chris Matrakidis ◽  
Theofanis G. Orphanoudakis ◽  
Alexandros Stavdas
Keyword(s):  
Clustering Algorithm ◽  
Node Clustering

Detecting communities by asymmetric intimacy in directed-weighted network

2017 ◽  
Vol 28 (01) ◽  
pp. 1750006 ◽  
Author(s):  
Xingyuan Wang ◽  
Xiaomeng Qin
Keyword(s):  
Complex Networks ◽  
Community Detection ◽  
Real World ◽  
Potential Application ◽  
Clustering Algorithm ◽  
Intimate Relationship ◽  
Detection Algorithm ◽  
Weighted Network ◽  
Node Clustering ◽  
Public Concerns

Community detection and analysis have attracted wide public concerns over the recent years. Meanwhile, many related algorithms in complex networks have been proposed. However, most of them concentrate on undirected and unweighted networks. Concerning the significant theoretical value and potential application foreground for directed-weighted networks, in this paper, a novel hierarchical communities detection algorithm (termed as DCBAI) has been proposed on the basis of asymmetric intimacy between nodes. Community structures are effectively detected by node clustering algorithm in directed-weighted network, and a set of optimal communities are generated. In addition, a new and asymmetric parameter is adopted to measure the intimate relationship between nodes. We make some simulation using the proposed algorithm in real-world networks and artificial networks, and the result obtained proves that the parameter can describe the direct and indirect relationships between two nodes. Eventually, comparison with similar algorithms shows that our proposed algorithm has better performance.

scholarly journals Field Robots for Intelligent Farms—Inhering Features from Industry

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1638
Author(s):  
Pablo Gonzalez-de-Santos ◽  
Roemi Fernández ◽  
Delia Sepúlveda ◽  
Eduardo Navas ◽  
Luis Emmi ◽  
...  
Keyword(s):  
Environmental Sustainability ◽  
Industrial Robots ◽  
World Population ◽  
Physical Systems ◽  
Agricultural Robots ◽  
Field Robots ◽  
World Population Growth ◽  
Different Types ◽  
Robot Systems ◽  
Management Techniques

Estimations of world population growth urgently require improving the efficiency of agricultural processes, as well as improving safety for people and environmental sustainability, which can be opposing characteristics. Industry is pursuing these objectives by developing the concept of the “intelligent factory” (also referred to as the “smart factory”) and, by studying the similarities between industry and agriculture, we can exploit the achievements attained in industry for agriculture. This article focuses on studying those similarities regarding robotics to advance agriculture toward the concept of “intelligent farms” (smart farms). Thus, this article presents some characteristics that agricultural robots should gain from industrial robots to attain the intelligent farm concept regarding robot morphologies and features as well as communication, computing, and data management techniques. The study, restricted to robotics for outdoor farms due to the fact that robotics for greenhouse farms deserves a specific study, reviews different structures for robot manipulators and mobile robots along with the latest techniques used in intelligent factories to advance the characteristics of robotics for future intelligent farms. This article determines similarities, contrasts, and differences between industrial and field robots and identifies some techniques proven in the industry with an extraordinary potential to be used in outdoor farms such as those derived from methods based on artificial intelligence, cyber-physical systems, Internet of Things, Big Data techniques, and cloud computing procedures. Moreover, different types of robots already in use in industry and services are analyzed and their advantages in agriculture reported (parallel, soft, redundant, and dual manipulators) as well as ground and aerial unmanned robots and multi-robot systems.

scholarly journals Dynamic Multi-hop Routing Protocol Based on Fuzzy-Firefly Algorithm for Data Similarity Aware Node Clustering in WSNs

2018 ◽  
Vol 13 (1) ◽  
pp. 99
Author(s):  
Misbahuddin Misbahuddin ◽  
Anak Agung Putri Ratna ◽  
Riri Fitri Sari
Keyword(s):  
Network Lifetime ◽  
Routing Protocol ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Base Station ◽  
Cluster Heads ◽  
Data Similarity ◽  
Fuzzy Aggregation ◽  
Node Clustering

In multi-hop routing, cluster heads close to the base station functionaries as intermediate nodes for father cluster heads to relay the data packet from regular nodes to base station. The cluster heads that act as relays will experience energy depletion quicker that causes hot spot problem. This paper proposes a dynamic multihop routing algorithm named Data Similarity Aware for Dynamic Multi-hop Routing Protocol (DSA-DMRP) to improve the network lifetime, and satisfy the requirement of multi-hop routing protocol for the dynamic node clustering that consider the data similarity of adjacent nodes. The DSA-DMRP uses fuzzy aggregation technique to measure their data similarity degree in order to partition the network into unequal size clusters. In this mechanism, each node can recognize and note its similar neighbor nodes. Next, K-hop Clustering Algorithm (KHOPCA) that is modified by adding a priority factor that considers residual energy and distance to the base station is used to select cluster heads and create the best routes for intra-cluster and inter-cluster transmission. The DSA-DMRP was compared against the KHOPCA to justify the performance. Simulation results show that, the DSA DMRP can improve the network lifetime longer than the KHOPCA and can satisfy the requirement of the dynamic multi-hop routing protocol.

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