Optimal path planning for mobile robot using Intelligent Water Drops algorithm

Abstract

In this paper, the generalized intelligent water drops (IWD) algorithm is proposed to solve robot path planning problem. Path planning is modeled by IWD algorithm, because there is inherent similarity between this and finding most appropriate route in natural rivers, that occurs by interaction between water drops and the river bed. The proposed algorithm has two levels; first level, finds the best global feasible path. Second level, performs local search at relatively near distances of global path and reduces its length and time to reach optimal solution. The IWD algorithm, like other inspired nature algorithms, has not a mechanism to deal with constrained optimization problem in its original version. So, a mechanism has been proposed based on repair of infeasible solutions. In this mechanism, a fuzzy inference system is proposed for selecting the best possible infeasible solution and then the local search operator repairs any of them in violation locations. Another innovation of this paper provides a mechanism to local soil update, which is based on fuzzy systems and is independent of size and complexity of environment and its soil altering will be defined in fixed range. Simulation result shows ability of IWD algorithm in finding of the optimal path.

Water‐Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP‐Hard Problems

“…In particular, it has been applied to many scheduling problems (see, e.g., [31][32][33][34]), as well as to minimize the energy consumption in a power system that requires meeting a given total power demand at each moment [35]. It has also been used to reduce the energy consumption in wireless sensor networks [36], to deal with the robot path planning [37], and even to compress images [38].…”

Hybrid IWD-GA: An Approach for Path Optimization and Control of Multiple Mobile Robot in Obscure Static and Dynamic Environments

“…Hosseini 7,8 has used the IWD algorithm to extract a solution for an n-queen puzzle and TSP problem. Salmanpour et al 9,10 used a generalized IWD algorithm with fuzzy interface for path tracking problem of robots. Bansal et al 11 have used an IWD algorithm to decode the graph-based TSP problem.…”

A Review of Path Planning Methods for Marine Autonomous Surface Vehicles

“…However, despite their numerous potential applications, coordinating the motion control of ASVs presents significant challenges. These challenges stem from factors such as the multiplicity of ASVs, the complexity of vehicle interactions, the formation of fleets with collision avoidance requirements, and the limited communication bandwidth available in marine environments [125]. The path planning methods of multi-ASV collaboration are still very lacking.…”