Water cycle algorithm: an approach for improvement of navigational strategy of multiple humanoid robots

Abstract

This paper presents an efficient water cycle algorithm based on the processes of water cycle with movement of streams and rivers in to the sea. This optimization algorithm is applied to obtain the optimal feasible path with minimum travel duration during motion planning of both single and multiple humanoid robots in both static and dynamic cluttered environments. This technique discards the rainfall process considering falling water droplets forming streams during raining and the process of flowing. The flowing process searches the solution space and finds the more accurate solution and represents the local search. Motion planning of humanoids is carried out in V-REP software. The performance of proposed algorithm is tested in experimental scenario under laboratory conditions and shows the developed algorithm performs well in terms of obtaining optimal path length and minimum time span of travel. Here, navigational analysis has been performed on both single as well as multiple humanoid robots. Statistical analysis of results obtained from both simulation and experimental environments is carried out for both single and multiple humanoids, along with the comparison with another existing optimization technique that indicate the strength and effectiveness of the proposed water cycle algorithm.

Tailoring the motion planning of humanoids in complex arena: a regression-firefly-based approach

“…Kumar et al [25] perform navigational analysis using their developed intelligent motion planner on a humanoid robot. Muni et al [26][27][28][29][30][31] introduced and successfully implemented various artificial intelligence algorithms toward motion planning analysis of legged robots in obstacle-prone environments.…”

Trajectory planning and control of multiple mobile robot using hybrid MKH-fuzzy logic controller

“…Fen et al [24] have presented an improved ACO technique for the analysis of problems. Muni et al [25][26][27] have developed fuzzy and water cycle approaches for navigational control of a humanoid robots. Kumar et al [28] have proposed a hybrid model for trajectory planning of mobile robots.…”

Navigation of a wheeled mobile robotic agent using modified grey wolf optimization controller

“…The goals of optimization involved are the length of the path, the degree of evenness and the degree of safety of the route. Muni et al (2020a, 2020b, 2020c, 2020d, 2021) have proposed the hybrid artificial intelligent technique for control over humanoid robots. Kumar et al (2020a, 2020b, 2021) have proposed hybrid sine cosine and ACO technique path planning of mobile robot.…”

“…The goals of optimization involved are the length of the path, the degree of evenness and the degree of safety of the route. Muni et al (2020aMuni et al ( , 2020bMuni et al ( , 2020cMuni et al ( , 2020dMuni et al ( , 2021 have proposed the hybrid artificial intelligent technique for control over humanoid robots. Kumar et al (2020aKumar et al ( , 2020bKumar et al ( , 2021 Several techniques studied in the literature survey are already proposed by the researchers concerning navigational problems of the mobile robot, but no one confirms the generated path is optimal or not.…”