Self-diagnosis System of an Autonomous Mobile Robot Using Sensory Information

2000 ◽  
Vol 12 (2) ◽  
pp. 72-77 ◽  
Author(s):  
Shinnosuke Okina ◽  
◽  
Kuniaki Kawabata ◽  
Teruo Fujii ◽  
Yasuharu Kunii ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Intelligent Systems ◽  
Sensory Information ◽  
Point Of View ◽  
Magnetic Sensors ◽  
Autonomous Mobile Robot ◽  
Diagnosis System ◽  
The Real ◽  
Multiple Sensors ◽  
Sensing System

In this paper, we describe a basic sensing system for self-diagnosing an autonomous mobile robot. In recent years, many researches on intelligent robots and systems have been done. But, when such robots and systems work in the real environment, it is important for those robots and systems to have the ability to recognize their own conditions for detecting faults. On the point of view, we should consider pay more attention to diagnose in such intelligent systems. Therefore we try to construct an internal sensing system as a self-diagnosis system on a real robot. Especially, in this paper, we discuss about motor system of an autonomous omnidirectional mobile robot, which was developed in RIKEN. The self-diagnosis system consists of multiple sensors, which are voltage, current, encoder, and magnetic sensors. We show some diagnosing experimental results using the real system. From the results, we could collect basic data for fault detection of the system.

scholarly journals Self-diagnosis System of an Autonomous Mobile Robot using Internal Sensory Information.

2001 ◽  
Vol 19 (4) ◽  
pp. 535-541 ◽  
Author(s):  
Shinnosuke Okina ◽  
Kuniaki Kawabata ◽  
Teruo Fujii ◽  
Yasuharu Kunii ◽  
Hajime Asama ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Sensory Information ◽  
Autonomous Mobile Robot ◽  
Diagnosis System

Practical Education Curriculum for Autonomous Mobile Robot (Project Learning Program for School Based on Subsumption Architecture)

2011 ◽  
Vol 23 (5) ◽  
pp. 684-700 ◽  
Author(s):  
Yoshihiko Kawazoe ◽  
◽  
Masaki Mitsuoka ◽  
Sho Masada
Keyword(s):  
Mobile Robot ◽  
Real World ◽  
Strong Nonlinearity ◽  
Autonomous Mobile Robot ◽  
Learning Program ◽  
Subsumption Architecture ◽  
The Real ◽  
Emotional Appeal ◽  
School Based ◽  
Autonomous Machine

There are presently no robots around us in our society if we define a robot as an autonomous machine working in the arena of offices, homes, disaster sites, etc., not in factories. Mechatronics, dynamics, and robotics involving humans are a world of strong nonlinearity. This paper investigates the approach to the emergence of the target behavior of an autonomous mobile robot by learning with Subsumption Architecture (SA) to break through the problems of the conventional robotics with the SMPA (Sense-Model-Plan-Act) framework in the real world. It has showed the way things are learned in the real world with SA and has been developed into a practical curriculum for education as an introduction to robotics that has an intellectual and emotional appeal.

Development of Autonomous Mobile Robot for Obstacle Avoidance

1993 ◽  
Vol 5 (5) ◽  
pp. 481-486 ◽  
Author(s):  
Masafumi Uchida ◽  
◽  
Syuichi Yokoyama ◽  
Hideto Ide ◽  
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Potential Method ◽  
Working Environment ◽  
Planning Problem ◽  
Autonomous Mobile Robot ◽  
The Real

The potential method is superior for solving the problem of motion planning; however, it must address the problem of the real-time generation of potential field. Obstacle avoidance is a motion planning problem. In a previous study, we investigated the real-time generation of potential field. Based on parallel processing with element group, we proposed the system by Sensory Point Moving (SPM) method. As a result of computer simulation, it was confirmed that the SPM method is effective for generating an obstacle avoidance path in 2-D and a more complex working environment like a 3-D one. In this paper, we discuss the development of autonomous mobile robot for obstacle avoidance based on the SPM method.

Development of Autonomous Mobile Robot that Can Navigate in Rainy Situations

2016 ◽  
Vol 28 (4) ◽  
pp. 441-450 ◽  
Author(s):  
Naoki Akai ◽  
◽  
Yasunari Kakigi ◽  
Shogo Yoneyama ◽  
Koichi Ozaki ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Real World ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Navigation Systems ◽  
Autonomous Mobile Robot ◽  
Technical Challenge ◽  
The Real ◽  
Mobile Navigation ◽  
Unexpected Behavior

[abstFig src='/00280004/02.jpg' width='300' text='Navigation under strong rainy condition' ] The Real World Robot Challenge (RWRC), a technical challenge for mobile outdoor robots, has robots automatically navigate a predetermined path over 1 km with the objective of detecting specific persons. RWRC 2015 was conducted in the rain and every robot could not complete the mission. This was because sensors on the robots detected raindrops and the robots then generated unexpected behavior, indicating the need to study the influence of rain on mobile navigation systems – a study clearly not yet sufficient. We begin by describing our robot’s waterproofing function, followed by investigating the influence of rain on the external sensors commonly used in mobile robot navigation and discuss how the robot navigates autonomous in the rain. We conducted navigation experiments in artificial and actual rainy environments and those results showed that the robot navigates stably in the rain.

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