scholarly journals Fast Breadth-First Search in Still Less Space

Author(s):  
Torben Hagerup
Keyword(s):  
Author(s):  
Muhammad Aria

Abstrak – Pada penelitian ini dirancang algoritma alternatif untuk perencanaan jalur kendaraan otonom. Algoritma yang diusulkan adalah hibridisasi dari algoritma Breadth First Search (BFS) dan algoritma path smoothing (BFS – path smoothing). Berdasarkan pengamatan dari hasil pengujian, keuntungan dari algoritma BFS adalah dapat memberikan solusi yang menuju solusi optimal, tetapi memiliki kelemahan dari waktu komputasi yang tinggi. Agar diperoleh solusi yang optimal, maka jalur yang dihasilkan oleh algoritma BFS akan diproses lebih lanjut oleh algoritma path smoothing. Walaupun algoritma BFS - path smoothing memiliki waktu komputasi yang tinggi, tetapi untuk tujuan mendapatkan solusi yang optimal, waktu komputasi BFS – path smoothing masih lebih rendah daripada algoritma RRT* untuk mendapatkan solusi yang optimal. Algoritma RRT* adalah salah satu algoritma yang umum digunakan untuk perencanaan jalur pada kendaraan otonom. Proses hibridisasi ini dilakukan dengan cara menjalankan algoritma BFS terlebih dahulu untuk memberikan solusi awal. Solusi awal tersebut kemudian ditingkatkan kualitasnya menggunakan algoritma path smoothing untuk memperoleh solusi yang optimal. Pengujian algoritma BFS-path smoothing ini dilakukan secara simulasi menggunakan beberapa kasus benchmark yang ada, yaitu lingkungan narrow, maze, trap dan clutter. Kriteria optimalitas yang dibandingkan adalah biaya jalur dan waktu komputasi. Pada pengujian, performansi dari algoritma BFS-path smoothing dibandingkan dengan performansi dari algoritma RRT*. Kami menunjukkan bahwa algoritma yang diusulkan dapat menghasilkan output jalur dengan kualitas yang lebih tinggi daripada jalur yang diproduksi oleh RRT*.   Kata Kunci : Beadth First Search, path smoothing, perencanaan jalur, pengujian simulasi, RRT*


Author(s):  
Mark Newman

This chapter gives a discussion of search processes on networks. It begins with a discussion of web search, including crawlers and web ranking algorithms such as PageRank. Search in distributed databases such as peer-to-peer networks is also discussed, including simple breadth-first search style algorithms and more advanced “supernode” approaches. Finally, network navigation is discussed at some length, motivated by consideration of Milgram's letter passing experiment. Kleinberg's variant of the small-world model is introduced and it is shown that efficient navigation is possible only for certain values of the model parameters. Similar results are also derived for the hierarchical model of Watts et al.


Author(s):  
Mark Newman

This chapter introduces some of the fundamental concepts of numerical network calculations. The chapter starts with a discussion of basic concepts of computational complexity and data structures for storing network data, then progresses to the description and analysis of algorithms for a range of network calculations: breadth-first search and its use for calculating shortest paths, shortest distances, components, closeness, and betweenness; Dijkstra's algorithm for shortest paths and distances on weighted networks; and the augmenting path algorithm for calculating maximum flows, minimum cut sets, and independent paths in networks.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4156
Author(s):  
Luís B. P. Nascimento ◽  
Dennis Barrios-Aranibar ◽  
Vitor G. Santos ◽  
Diego S. Pereira ◽  
William C. Ribeiro ◽  
...  

The planning of safe paths is an important issue for autonomous robot systems. The Probabilistic Foam method (PFM) is a planner that guarantees safe paths bounded by a sequence of structures called bubbles that provides safe regions. This method performs the planning by covering the free configuration space with bubbles, an approach analogous to a breadth-first search. To improve the propagation process and keep the safety, we present three algorithms based on Probabilistic Foam: Goal-biased Probabilistic Foam (GBPF), Radius-biased Probabilistic Foam (RBPF), and Heuristic-guided Probabilistic Foam (HPF); the last two are proposed in this work. The variant GBPF is fast, HPF finds short paths, and RBPF finds high-clearance paths. Some simulations were performed using four different maps to analyze the behavior and performance of the methods. Besides, the safety was analyzed considering the new propagation strategies.


2016 ◽  
Vol 45 (2) ◽  
pp. 233-252
Author(s):  
Pepijn Viaene ◽  
Alain De Wulf ◽  
Philippe De Maeyer

Landmarks are ideal wayfinding tools to guide a person from A to B as they allow fast reasoning and efficient communication. However, very few path-finding algorithms start from the availability of landmarks to generate a path. In this paper, which focuses on indoor wayfinding, a landmark-based path-finding algorithm is presented in which the endpoint partition is proposed as spatial model of the environment. In this model, the indoor environment is divided into convex sub-shapes, called e-spaces, that are stable with respect to the visual information provided by a person’s surroundings (e.g. walls, landmarks). The algorithm itself implements a breadth-first search on a graph in which mutually visible e-spaces suited for wayfinding are connected. The results of a case study, in which the calculated paths were compared with their corresponding shortest paths, show that the proposed algorithm is a valuable alternative for Dijkstra’s shortest path algorithm. It is able to calculate a path with a minimal amount of actions that are linked to landmarks, while the path length increase is comparable to the increase observed when applying other path algorithms that adhere to natural wayfinding behaviour. However, the practicability of the proposed algorithm is highly dependent on the availability of landmarks and on the spatial configuration of the building.


2011 ◽  
Vol 201-203 ◽  
pp. 24-29
Author(s):  
Zhou Bo Xu ◽  
Tian Long Gu ◽  
Liang Chang ◽  
Feng Ying Li

The compact storage and efficient evaluation of feasible assembly sequences is one crucial concern for assembly sequence planning. The implicitly symbolic ordered binary decision diagram (OBDD) representation and manipulation technique has been a promising way. In this paper, Sharafat’s recursive contraction algorithm and cut-set decomposition method are symbolically implemented, and a novel symbolic algorithm for generating mechanical assembly sequences is presented using OBDD formulations of liaison graph and translation function. The algorithm has the following main procedures: choosing any one of vertices in the liaison graph G as seed vertex and scanning all connected subgraphs containing seed vertex by breadth first search; transforming the problem of enumerating all cut-sets in liaison graph into the problem of generating all the partitions: two subsets V1and V2of a set of vertices V where both the induced graph of vertices V1and V2are connected; checking the geometrical feasibility for each cut-set. Some applicable experiments show that the novel algorithm can generate feasible assembly sequences correctly and completely.


1994 ◽  
Vol 49 (1) ◽  
pp. 45-50 ◽  
Author(s):  
C. Rhee ◽  
Y.Daniel Liang ◽  
S.K. Dhall ◽  
S. Lakshmivarahan

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