Proposed Smooth-STC Algorithm for Enhanced Coverage Path Planning Performance in Mobile Robot Applications

Abstract

Robotic path planning is a field of research which is gaining traction given the broad domains of interest to which path planning is an important systemic requirement. The aim of path planning is to optimise the efficacy of robotic movement in a defined operational environment. For example, robots have been employed in many domains including: Cleaning robots (such as vacuum cleaners), automated paint spraying robots, window cleaning robots, forest monitoring robots, and agricultural robots (often driven using satellite and geostationary positional satellite data). Additionally, mobile robotic systems have been utilised in disaster areas and locations hazardous to humans (such as war zones in mine clearance). The coverage path planning problem describes an approach which is designed to determine the path that traverses all points in a defined operational environment while avoiding static and dynamic (moving) obstacles. In this paper we present our proposed Smooth-STC model, the aim of the model being to identify an optimal path, avoid all obstacles, prevent (or at least minimise) backtracking, and maximise the coverage in any defined operational environment. The experimental results in a simulation show that, in uncertain environments, our proposed smooth STC method achieves an almost absolute coverage rate and demonstrates improvement when measured against alternative conventional algorithms.

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

“…The wall following algorithm enables the robot to move along the obstacle boundary through the sub-nodes. Meanwhile, Pham et al [77] improved the algorithm to find the optimal path, focusing on minimizing the backtracking and increasing the coverage rate by considering the mega-cells that are partially occupied by obstacles in building the C-space boundary contour. The path is planned through the spanning-tree edge in an anti-clockwise direction to find the next unvisited megacell.…”

Informatics and the Challenge of Determinism

“…Autonomous robotic systems have been developed for multiple domestic and disaster recovery functions as discussed in [42,[100][101][102][103][104]. The research introduces intelligent sensor-derived data processing with autonomous coverage path planning (CPP) in working robots operating in an internal dynamic (static and moving obstacles) domestic environment and a similar dynamic external environment.…”

Emergency Service Provision Using a Novel Hybrid SOM-Spiral STC Model for Group Decision Support under Dynamic Uncertainty

“…In Section 1 we have introduced the paradigm shift in urban living which has resulted in enlargement of urban centres with vastly increased congestion which is an important element in the provision of efficient and timely emergency response. Emergency response systems require effective route planning (in robotics this may be viewed from the perspective of "path planning" [3][4][5]) which must implement avoidance of obstacles (static and moving) to achieve the optimal path in traversing the defined operational environment (DOE).…”