Robot Navigation in dynamic environment for an indoor human monitoring

Abstract

This paper proposes a technique for navigation of a monitoring robot to watch over persons in a dynamic environment. In order to make an environmental map around the robot, localization of the robot and path finding to the target position are required so that the robot can move autonomously in the dynamic environment. In this study the position of robot and the environmental map are obtained by using Simultaneous Localization and Mapping (SLAM) which makes the map by using LRF with characteristic markers. Path finding to the target position is executed by using Navigation function that is a type of Artificial Potential Field (APF) method. Navigation function projects the work space and the obstacles to a topology space, and calculates value of APF. An effectiveness of the presented algorithm was confirmed since the point mass robot can reach the target position by avoiding moving objects through the simulation.

Bridging Requirements, Planning, and Evaluation: A Review of Social Robot Navigation

“…More recently, Iizuka et al [273] proposed a modified APF approach resistant to the local minimum issue in multiobstacle environments, while Weerakoon et al [274] presented a deadlock-free APF-based path-planning algorithm. Similarly, Azzabi and Nouri [275] developed an approach that addresses the common issues of the original APF, namely local minima and the goal being nonreachable with obstacles nearby.…”