A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms

Abstract

The small battery capacities of the mobile robot and the un-optimized planning efficiency of the industrial robot bottlenecked the time efficiency and productivity rate of coverage tasks in terms of speed and accuracy, putting a great constraint on the usability of the robot applications in various planning strategies in specific environmental conditions. Thus, it became highly desirable to address the optimization problems related to exploration and coverage path planning (CPP). In general, the goal of the CPP is to find an optimal coverage path with generates a collision-free trajectory by reducing the travel time, processing speed, cost energy, and the number of turns along the path length, as well as low overlapped rate, which reflect the robustness of CPP. This paper reviews the principle of CPP and discusses the development trend, including design variations and the characteristic of optimization algorithms, such as classical, heuristic, and most recent deep learning methods. Then, we compare the advantages and disadvantages of the existing CPP-based modeling in the area and target coverage. Finally, we conclude numerous open research problems of the CPP and make suggestions for future research directions to gain insights. INDEX TERMSCoverage path planning, exploration, heuristic algorithm, deep reinforcement learning.

Problem Solving in Crowd Management Using Heuristic Approach

“…They defined heuristic theorizing as the process of proactively generating design theory for prescriptive purposes from problem-solving experiences. A comprehensive article reviews the classical and heuristics algorithms for coverage path planning (CPP) in robotics to explore the solution space and find the optimal trajectory [7]. Gao et al [8] reviewed the state-of-the-art of this metaheuristics to identify the current status of meta-heuristics solving disassembly line balancing, planning, and scheduling problems (DLBPSP) in remanufacturing.…”

Safety-Aware Autonomous Systems : Preparing Robots for Life in the Real World

“…Planning with respect to time is also essential to be able to wait for, or move out of the way of, moving obstacles. This entail that the robot itself must be able to revisit states within the same plan, something which is seldom considered of navigation tasks [3] but which makes the problem even more challenging [176]. Furthermore, a world populated with dynamic obstacles with their own agency is likely to develop differently than according to the most likely prediction of the future.…”

Complete coverage problem of multiple robots with different velocities

“…The implementation of single-robot coverage path planning is beyond the scope of this article, and reviews of such approaches are presented in the literature. 17,18,19…”

“…The implementation of single-robot coverage path planning is beyond the scope of this article, and reviews of such approaches are presented in the literature. 17,18,19 Several research approaches have been proposed in the past to perform multi-robot CCP. Most multi-robot CCP approaches divide the environment into balanced subareas and minimize the maximum subarea of overall robots.…”