Abstract

In this paper, we proposed an enhanced path planning strategy for sweeper robots, which were created for the curling Olympic games. The main task for the multi-robot system is to clean the ice surface making a smooth path for a curling stone. The sweeping robots should have a motion planning on how to follow the curling stone slide and to prevent any collisions. In order to find the next position of the sweeping robot, it needs to establish the current position and to compute the next position of the curling stone. The initial and goal points of the sweeping robots are found and set up based on the simulation results from the main server. While the curling stone moves, the sweeping robots measure its position and adjust their motions according to the stone position trajectory. If the distance between the current and the next positions of a curling stone exceeds the threshold value, the sweeping robots should activate the sweeping mechanism preventing collisions with the stone. Since the estimation of the sweeping robot motion solely depends on the stone’s trajectory, the accumulation of errors is undesirable. Thus, the stone trajectory should be recalculated in a certain time step using the trend-adjusted exponential smoothing method. Then, the formation of the sweeping robot system can be calibrated according to the stone path computation. The obtained experimental results proved the efficiency of the proposed path planning method.

Highlights

  • As is well known, robotics shares one of the most important parts in the fourth industrial revolution which is a consequence of the digital transformation as well as a result of the fusion of technologies.Robots are becoming more integrated in our lives and already are a familiar sight in the workplace and home

  • We propose an effective method to predict the path of the curling stone to determine the trajectory of the sweeper robot according to the strategy developed in the main server

  • If the error between the target path and the expected path of the curling stone is larger than the threshold value, the path of the curling stone is changed by reducing the friction of the curling sheet through the sweeping of a broom attached to the lower part of the sweeper robot to move the stone back in the direction of the target path

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Summary

Introduction

Robotics shares one of the most important parts in the fourth industrial revolution which is a consequence of the digital transformation as well as a result of the fusion of technologies. Because the path of the curling stone needs to be estimated in real time it is necessary to use a reliable method with a small amount of calculation [1,2]. For this reason, the sweeper robot uses Holt’s linear trending technique, called trend-adjusted exponential smoothing (TAES), to predict the path of the curling stone. The position of the sweeper robot is determined in such a way that it does not obstruct the path of the stone depending on the type of shot ordered from the main server. If the error between the target path and the expected path of the curling stone is larger than the threshold value, the path of the curling stone is changed by reducing the friction of the curling sheet through the sweeping of a broom attached to the lower part of the sweeper robot to move the stone back in the direction of the target path

Path Prediction of Curling Stone
Target Path Conversion
Initial Path Planning with Formation
Actual Stone Position Estimation
Real‐Time
Revised Movement Path of the Robot
Experiment
Real-Time Curling Stone Data Extraction Experiment Using Kalman
Real‐Time Curling Stone Data Extraction Experiment Using Kalman
Experiment with Trend-Adjusted Exponential Smoothing
Conclusions
11. Experiment
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