TY - GEN
T1 - Spider Monkey Optimization Algorithm Based Collision-Free Navigation and Path Optimization for a Mobile Robot in the Static Environment
AU - Lagaza, Kevin Pirewa
AU - Kashyap, Abhishek Kumar
AU - Pandey, Anish
N1 - Publisher Copyright:
© 2020, Springer Nature Singapore Pte Ltd.
PY - 2020
Y1 - 2020
N2 - This paper concentrates on the recognition of a navigational algorithm, which can resolve path optimization challenges in minimum time. This navigational algorithm helps the mobile robot to avoid collision with obstacles. Implementation of spider monkey optimization (SMO) algorithm is carried out to explain the objectives of this paper. SMO algorithm is established upon the splitting-combination nature of spider monkeys. The proposed algorithm is examined in various terrains to determine the robustness and effectuality of the proposed algorithm. Simulation results confirmed that spider monkey optimization algorithm selects a path, which guides the robot to reach the target in minimum possible time. Subsequently, it decreases the computational cost, as the time for computation is minimized. In extension, we replicated the previously used environment, and the proposed algorithm is compared with the corresponding implemented algorithm. Our results demonstrate that Spider monkey optimization (SMO) provides better results on the basis of time by selecting a path with lesser complexity. To determine the adequacy of the prescribed standard route-outlining control design, the common element of this paper is the numerical simulation.
AB - This paper concentrates on the recognition of a navigational algorithm, which can resolve path optimization challenges in minimum time. This navigational algorithm helps the mobile robot to avoid collision with obstacles. Implementation of spider monkey optimization (SMO) algorithm is carried out to explain the objectives of this paper. SMO algorithm is established upon the splitting-combination nature of spider monkeys. The proposed algorithm is examined in various terrains to determine the robustness and effectuality of the proposed algorithm. Simulation results confirmed that spider monkey optimization algorithm selects a path, which guides the robot to reach the target in minimum possible time. Subsequently, it decreases the computational cost, as the time for computation is minimized. In extension, we replicated the previously used environment, and the proposed algorithm is compared with the corresponding implemented algorithm. Our results demonstrate that Spider monkey optimization (SMO) provides better results on the basis of time by selecting a path with lesser complexity. To determine the adequacy of the prescribed standard route-outlining control design, the common element of this paper is the numerical simulation.
UR - https://www.scopus.com/pages/publications/85079148183
UR - https://www.scopus.com/pages/publications/85079148183#tab=citedBy
U2 - 10.1007/978-981-15-0124-1_128
DO - 10.1007/978-981-15-0124-1_128
M3 - Conference contribution
AN - SCOPUS:85079148183
SN - 9789811501234
T3 - Lecture Notes in Mechanical Engineering
SP - 1459
EP - 1473
BT - Advances in Mechanical Engineering - Select Proceedings of ICRIDME 2018
A2 - Biswal, B.B.
A2 - Sarkar, Bikash Kumar
A2 - Mahanta, P.
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Recent Innovations and Developments in Mechanical Engineering, IC-RIDME 2018
Y2 - 8 November 2018 through 10 November 2018
ER -