The CLAPPER: A Dual-Drive Mobile Robot with Internal Correction of Dead-Reckoning Errors

2005 ◽  
Author(s):  
J. Borenstein
Keyword(s):  
Mobile Robot ◽  
Dead Reckoning

Path-tracking controller design and implementation of a vision-based wheeled mobile robot

2009 ◽  
Vol 223 (6) ◽  
pp. 847-862 ◽  
Author(s):  
J-L Yang ◽  
D-T Su ◽  
Y-S Shiao ◽  
K-Y Chang
Keyword(s):  
Mobile Robot ◽  
Tracking Control ◽  
Intelligent System ◽  
Vision System ◽  
Dead Reckoning ◽  
Path Tracking ◽  
Wheeled Mobile Robot ◽  
Detection Methods ◽  
Control Laws ◽  
The Dead

This paper presents techniques for building system configuration, control architecture, and implementation of a vision-based wheeled mobile robot (WMR). The completed WMR has been built with the dead-reckoning method so as to determine the vehicle's velocity and posture by the numerical differentiation/integration over short travelling. The developed proportional-integral-derivative (PID) controllers show good transient performances; that is, the velocity of right and left wheels can track the commands quickly and correctly. Moreover, the path-tracking control laws have also been executed within the digital signal processor (DSP)-based controller in the WMR. The image-recognized system can obtain motion information at 15 frames/s by using the hybrid intelligent system (HIS) model, which is one of the well-known colour detection methods. The better performance a vision system has, the more successful the control laws design. The WMR obtains its posture from the dead-reckoning device together with the vision system. These subsystems are integrated, and the operators of the whole system are completed. This WMR system can be thought of as a platform for testing various tracking control laws and a signal-filtering method. To solve the problem of position/orientation tracking control of the WMR, two kinematical optimal non-linear predictive control laws are developed to manipulate the vehicle to follow the desired trajectories asymptotically. A Kalman filter scheme is used to reduce the bad effect of the imagine nose; thereby the accuracy of pose estimation can be improved. The experimental system is composed of a wireless RS232 modem, a DSP-based controller for the WMR, and a vision system with a host computer. A computation-effective and high-performance DSP-based controller is constructed for executing the developed sophisticated path-tracking laws. Finally, the simulation and experimental results show the feasibility and effectiveness of the proposed control laws.

Autonomous Navigation of a Mobile Robot Based on GNSS/DR Integration in Outdoor Environments

2014 ◽  
Vol 26 (2) ◽  
pp. 214-224 ◽  
Author(s):  
Taro Suzuki ◽  
◽  
Mitsunori Kitamura ◽  
Yoshiharu Amano ◽  
Nobuaki Kubo ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Dead Reckoning ◽  
Satellite System ◽  
Mobile Robot Navigation ◽  
Observation Data ◽  
Multipath Mitigation ◽  
Ir Camera ◽  
Outdoor Environments ◽  
Global Navigation Satellite

This paper describes the development of a mobile robot system and an outdoor navigationmethod based on global navigation satellite system (GNSS) in an autonomous mobile robot navigation challenge, called the Tsukuba Challenge, held in Tsukuba, Japan, in 2011 and 2012. The Tsukuba Challenge promotes practical technologies for autonomous mobile robots working in ordinary pedestrian environments. Many teams taking part in the Tsukuba Challenge used laser scanners to determine robot positions. GNSS was not used in localization because its positioning has multipath errors and problems in availability. We propose a technique for realizing multipath mitigation that uses an omnidirectional IR camera to exclude “invisible” satellites, i.e., those entirely obstructed by a building and whose direct waves therefore are not received. We applied GPS / dead reckoning (DR) integrated based on observation data from visible satellites determined by the IR camera. Positioning was evaluated during Tsukuba Challenge 2011 and 2012. Our robot ran the 1.4 km course autonomously and evaluation results confirmed the effectiveness of our proposed technique and the feasibility of its highly accurate positioning.

scholarly journals Indoor Dead Reckoning Localization Using Ultrasonic Anemometer with IMU

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Woojin Seo ◽  
Kwang-Ryul Baek
Keyword(s):  
Mobile Robot ◽  
Dead Reckoning ◽  
Measurement Unit ◽  
Velocity Data ◽  
Short Period ◽  
Instantaneous Position ◽  
Ultrasonic Anemometer ◽  
Robot Positioning ◽  
Positioning Method ◽  
Angular Velocities

Dead reckoning is an important aspect of estimating the instantaneous position of a mobile robot. An inertial measurement unit (IMU) is generally used for dead reckoning because it measures triaxis acceleration and triaxis angular velocities in order to estimate the position of the mobile robot. Positioning with inertial data is reasonable for a short period of time. However, the velocity, position, and attitude errors increase over time. Much research has been conducted in ways to reduce these errors. To position a mobile robot, an absolute positioning method can be combined with dead reckoning. The performance of a combined positioning method can be improved based on improvement in dead reckoning. In this paper, an ultrasonic anemometer is used to improve the performance of dead reckoning when indoors. A new approach to the equation of an ultrasonic anemometer is proposed. The ultrasonic anemometer prevents divergence of the mobile robot’s velocity. To position a mobile robot indoors, the ultrasonic anemometer measures the relative movement of air while the robot moves through static air. Velocity data from the ultrasonic anemometer and the acceleration and angular velocity data from the IMU are combined via Kalman filter. Finally we show that the proposed method has the performance with a positioning method using encoders on a good floor condition.

scholarly journals State Estimation for Mobile Robot using Partially Observable Markov Decision Process

1996 ◽  
Vol 8 (3) ◽  
pp. 272-277
Author(s):  
Daehee Kang ◽  
◽  
Hideki Hashimoto ◽  
Fumio Harashima
Keyword(s):  
Mobile Robot ◽  
Markov Decision Process ◽  
Decision Process ◽  
Dead Reckoning ◽  
Position Estimation ◽  
Estimation Errors ◽  
Markov Decision ◽  
Partially Observable Markov ◽  
Partially Observable ◽  
Robot Position

Dead Reckoning has been commonly used for position estimation. However, this method has inherent problems, one of the biggest being it always cumulates estimation errors. In this paper, we propose a new method to estimate a current mobile robot state using Partially Observable Markov Decision Process (POMDP). POMDP generalizes the Markov Decision Process (MDP) framework to the case where the agent must make its decisions in partial ignorance of its current situation. Here, the robot state means the robot position or current subgoal at which the mobile robot is located. It is shown that we will be able to estimate the mobile robot state precisely and robustly, even if the environment is changed slightly, through a case study.

Position Uncertainty Reduction of Mobile Robot Based on DINDs in Intelligent Space

2008 ◽  
Vol 12 (6) ◽  
pp. 488-493
Author(s):  
TaeSeok Jin ◽  
◽  
Hideki Hashimoto ◽  
Keyword(s):  
Mobile Robot ◽  
A Priori ◽  
Dead Reckoning ◽  
Constraint Equation ◽  
Image Plane ◽  
Moving Object ◽  
Camera Model ◽  
Intelligent Space ◽  
Point Object ◽  
Position Data

This paper proposes a localization of mobile robot using the images by distributed intelligent networked devices (DINDs) in intelligent space (ISpace). This scheme combines data from the observed position using dead-reckoning sensors and the estimated position using images of moving object, such as those of a walking human, used to determine the moving location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Using the a-priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates of a moving object and the estimated position of the robot are derived. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in the determining of the location of the mobile robot.

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