Proposal of a Movement Control System with Light Contact for Autonomous Mobile Robots Based on Human Contact-Compliance Index

Author(s):  
Yusuke TSUBURAYA ◽  
Mitsuhiro KAMEZAKI ◽  
Tomoya ONISHI ◽  
Hayato YANAGAWA ◽  
Ayano KOBAYASHI ◽  
...  
Author(s):  
Gintautas Narvydas ◽  
Vidas Raudonis ◽  
Rimvydas Simutis

In the control of autonomous mobile robots there exist two types of control: global control and local control. The requirement to solve global and local tasks arises respectively. This chapter concentrates on local tasks and shows that robots can learn to cope with some local tasks within minutes. The main idea of the chapter is to show that, while creating intelligent control systems for autonomous mobile robots, the beginning is most important as we have to transfer as much as possible human knowledge and human expert-operator skills into the intelligent control system. Successful transfer ensures fast and good results. One of the most advanced techniques in robotics is an autonomous mobile robot on-line learning from the experts’ demonstrations. Further, the latter technique is briefly described in this chapter. As an example of local task the wall following is taken. The main goal of our experiment is to teach the autonomous mobile robot within 10 minutes to follow the wall of the maze as fast and as precisely as it is possible. This task also can be transformed to the obstacle circuit on the left or on the right. The main part of the suggested control system is a small Feed-Forward Artificial Neural Network. In some particular cases – critical situations – “If-Then” rules undertake the control, but our goal is to minimize possibility that these rules would start controlling the robot. The aim of the experiment is to implement the proposed technique on the real robot. This technique enables to reach desirable capabilities in control much faster than they would be reached using Evolutionary or Genetic Algorithms, or trying to create the control systems by hand using “If-Then” rules or Fuzzy Logic. In order to evaluate the quality of the intelligent control system to control an autonomous mobile robot we calculate objective function values and the percentage of the robot work loops when “If-Then” rules control the robot.


2018 ◽  
Vol 6 (5) ◽  
Author(s):  
Vesna Antoska Knights ◽  
Zoran Gacovski ◽  
Stojce Deskovski ◽  
Olivera Petrovska

1993 ◽  
Vol 26 (1) ◽  
pp. 421-426
Author(s):  
E. Crochon ◽  
F. Vacherand ◽  
M. Chaillot ◽  
M. Antonakios

2010 ◽  
Vol 7 ◽  
pp. 109-117
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov ◽  
B.S. Yudintsev

The article deals with the development of a high-speed sensor system for a mobile robot, used in conjunction with an intelligent method of planning trajectories in conditions of high dynamism of the working space.


Author(s):  
Margot M. E. Neggers ◽  
Raymond H. Cuijpers ◽  
Peter A. M. Ruijten ◽  
Wijnand A. IJsselsteijn

AbstractAutonomous mobile robots that operate in environments with people are expected to be able to deal with human proxemics and social distances. Previous research investigated how robots can approach persons or how to implement human-aware navigation algorithms. However, experimental research on how robots can avoid a person in a comfortable way is largely missing. The aim of the current work is to experimentally determine the shape and size of personal space of a human passed by a robot. In two studies, both a humanoid as well as a non-humanoid robot were used to pass a person at different sides and distances, after which they were asked to rate their perceived comfort. As expected, perceived comfort increases with distance. However, the shape was not circular: passing at the back of a person is more uncomfortable compared to passing at the front, especially in the case of the humanoid robot. These results give us more insight into the shape and size of personal space in human–robot interaction. Furthermore, they can serve as necessary input to human-aware navigation algorithms for autonomous mobile robots in which human comfort is traded off with efficiency goals.


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