Path-building and localization system for mobile robotic platforms based on Raspberry Pi

E A Ivanov,O A Brylev,A S Belyaev

doi:10.1088/1757-899x/1118/1/012020

Abstract

The paper demonstrates a system for detection of location of robotic platform FESTO Robotino and optimal route building. It processes data from the camera and transmits control signals to the control system of the robot. The whole system is based on Raspberry Pi. It detects robot’s current coordinates, current angular rotation, angular difference (difference between current and previous angular rotation) and displacement of the robot in its own coordinate system. It uses an ArUco marker, placed on the top of the mobile robot for that. System also builds an optimal path, when moving from one point of the surface to another, according to the permeability of the surface. The authors set the permeability of testing surfaces. Using that, a weighted graph is built through the centers of particular surfaces, which are detected via an algorithm on Raspberry Pi. The optimal path is constructed through the edges of the graph via modified Dijkstra algorithm.

Highlights

With technological and industrial development, modern mobile autonomous robotic systems gradually move from laboratories to the harsh environmental conditions
Among the basic mobile robotics’ problems, the navigation task is still actual. It includes detecting current position of the robot via getting the data from the on-board sensor system, and path-planning, according to the permeability of the surface. The latter consists of the optimal route building, obstacle-avoiding algorithm and others [1,2,3,4,5]
The computer processes the image from the camera and the data from the robotic platform, and pushes signals to the mobile robot, moving on the stand

Summary

Introduction

With technological and industrial development, modern mobile autonomous robotic systems gradually move from laboratories to the harsh environmental conditions. Among the basic mobile robotics’ problems, the navigation task is still actual It includes detecting current position of the robot via getting the data from the on-board sensor system, and path-planning, according to the permeability of the surface. The latter consists of the optimal route building, obstacle-avoiding algorithm and others [1,2,3,4,5]. Created computer vision system, mounted above the the testing surface, is used for training and for evaluation of the results It detects the location of the robot via the LEDs, set on it.

Published under licence by IOP Publishing Ltd

Conclusion