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Global Path Optimization of Humanoid NAO in Static Environment Using Prim’s Algorithm
M.K. Muni, D.R. Parhi, P.B. Kumar, , P.R. Dhal, S. Kumar
Published in Springer Science and Business Media Deutschland GmbH
Volume: 185 LNNS
Pages: 25 - 34
This paper focuses on navigation of a humanoid robot cluttered with obstacles, avoiding collisions in static environment using Prim’s algorithm. Prim’s algorithm is a minimum spanning tree (MST) method with greedy approach which uses the concept of sets. It generates the MST by selecting least weights from the weighted graph and randomly forms disjoint sets with picking one least weight edge from the ones remaining for creating node incident to form the tree. Similar approach repeats for selecting all ‘n – 1’ edges to the tree which is the path direction to humanoid NAO. The developed algorithm is implemented in both simulation and experimental platforms to obtain the navigational results. The simulation and experimental navigational results confirm the efficiency of the path planning strategy as the percentage of deviations of navigational parameters is below 6%. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetLecture Notes in Networks and Systems
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH