HCTNav: A Path Planning Algorithm for Low-Cost Autonomous Robot Navigation in Indoor Environments

Abstract

Low-cost robots are characterized by low computational resources and limited energy supply. Path planning algorithms aim to find the optimal path between two points so the robot consumes as little energy as possible. However, these algorithms were not developed considering computational limitations (i.e., processing and memory capacity). This paper presents the HCTNav path-planning algorithm (HCTLab research group's navigation algorithm). This algorithm was designed to be run in low-cost robots for indoor navigation. The results of the comparison between HCTNav and the Dijkstra's algorithms show that HCTNav's memory peak is nine times lower than Dijkstra's in maps with more than 150,000 cells.

Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environments

“…A Ã is the worst technique as it requires a large computational effort. Eraghi et al 15 compared A Ã , Dijkstra and HCTLab research group's navigation algorithm (HCTNav) that have been proposed in the study by Pala et al 16 HCTNav algorithm is designed for low resources robots navigating in binary maps. HCTNav's concept is to combine the shortest-path search principles of the deterministic approaches with the obstacle detection and avoidance techniques of the reactive approaches.…”

NafisNav: An indoor navigation algorithm for embedded systems and based on grid maps

“…The main variation from the classical Bresenham algorithm is that the original algorithm only gives the cells nearer the center of the straight line, but not all cells partially touched by a robot moving through that line. This is solved adding more Bresenham lines from surrounding cells of the origin and target, as shown in [9]. Therefore, if all the cells returned by this procedure are empty, then a robot can move in straight line without risk of collision.…”

“…Results show a higher speed in execution. The HCTNav algorithm [9] is also a path planning algorithm for grid maps implemented for indoor navigation. It has shown to require lower memory usage than Dijkstra's or A* algorithms, so it is more suitable for low cost robots or systems with limited resources.…”

Implementing a multisensory robotic platform for building collaborative monitored robots

“…The system lets the human operator take corrective action based on real-time information visible in the HMI and in the historical information stored in the database of the SCADA system. This paper shares previous experiences related to positioning and navigation systems [14], [15], [16] and focuses on algorithms for the search of the objective and in the development of the high-standard application which controls the SCADA system operator. The platform to be developed must be prepared to incorporate an e-nose since it is difficult to get a system that can accurately detect a particular smell and finding one is far from the objectives of this project.…”