scholarly journals TelOpTrak: Heuristics-enhanced Indoor Location Tracking for Tele-operated Robots

2012 ◽  
Vol 65 (2) ◽  
pp. 265-279 ◽  
Author(s):  
Johann Borenstein ◽  
Russ Miller ◽  
Adam Borrell
Keyword(s):  
Low Cost ◽  
Dead Reckoning ◽  
Experimental Results ◽  
Location Tracking ◽  
Live Video ◽  
Indoor Location ◽  
Live Demonstration ◽  
Conference Papers ◽  
Gyro Drift

With most tele-operated robots the operator's only feedback is the view from an onboard camera. Live video lets the operator observe the robot's immediate surroundings but does not establish the orientation or whereabouts of the robot in its environment. An additional plot of the robot's trajectory would be helpful for the operator and is sometimes provided, based on GPS. However, indoors where GPS is unavailable, tracking has to rely on dead-reckoning, which is too inaccurate to be useful. Our proposed TelOpTrak method corrects dead-reckoning errors even when only odometry and a low-cost (and thus, high-drift) MEMS-class gyro are available on the robot. TelOpTrak corrects gyro drift by exploiting the structured nature of most buildings, but without having to directly sense building features. This paper explains the TelOpTrak method and provides comprehensive experimental results.Earlier versions of this paper (Borenstein et al., 2010a), (Borenstein et al., 2010b) were presented at two conferences. The main difference between the earlier conference papers and the present manuscript is that the latter is more comprehensive, more up-to-date, and it presents an entirely new set of experimental results, including results of a live demonstration at the 2010 Robotics Rodeo event at Ft. Benning, USA.

A Combined Location Method for Mobile Robots Based on Dead Reckoning and WLAN

2014 ◽  
Vol 631-632 ◽  
pp. 649-653 ◽  
Author(s):  
Fang Jia ◽  
Kui Liu ◽  
De Cheng Xu
Keyword(s):  
Mobile Robots ◽  
Information Fusion ◽  
Low Cost ◽  
Dead Reckoning ◽  
Probability Matching ◽  
Location Method ◽  
Indoor Location ◽  
Location Algorithm ◽  
Location Methods ◽  
Received Signal Strength Indication

To minimize the deficiency of the existing indoor location methods for mobile robots, the RSSI (received signal strength indication) model of WLAN is established. Then a combined location method for mobile robots based on DR (dead reckoning) and WLAN is proposed, which employs PMLA (probability matching location algorithm) and KF (Kalman filter) for information fusion. Simulation results reveal that the combined location approach works well in eliminating the cumulative error of DR and reducing the fluctuation of WLAN location. As a result, the proposed method is capable of enhancing the positioning accuracy of mobile robots to a certain extent, promising a low-cost and reliable location scheme for its development.

scholarly journals Dual-Model Reverse CKF Algorithm in Cooperative Navigation for USV

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Bo Xu ◽  
Yong ping Xiao ◽  
Wei Gao ◽  
Yong gang Zhang ◽  
Ya Long Liu ◽  
...  
Keyword(s):  
Simulation Analysis ◽  
Low Cost ◽  
Dead Reckoning ◽  
Convergence Speed ◽  
Dual Model ◽  
Misalignment Angle ◽  
Cooperative Navigation ◽  
Cubature Kalman Filter ◽  
Short Period ◽  
Gyro Drift

As one of the most promising research directions, cooperative location with high precision and low-cost IMU is becoming an emerging research topic in many positioning fields. Low-cost MEMS/DVL is a preferred solution for dead-reckoning in multi-USV cooperative network. However, large misalignment angles and large gyro drift coexist in low-cost MEMS that leads to the poor observability. Based on cubature Kalman filter (CKF) algorithm that has access to high accuracy and relative small computation, dual-model filtering scheme is proposed. It divides the whole process into two subsections that cut off the coupling relations and improve the observability of MEMS errors: it first estimates large misalignment angle and then estimates the gyro drift. Furthermore, to improve the convergence speed of large misalignment angle estimated in the first subsection, “time reversion” concept is introduced. It uses a short period time to forward and backward several times to improve convergence speed effectively. Finally, simulation analysis and experimental verification is conducted. Simulation and experimental results show that the algorithm can effectively improve the cooperative navigation performance.

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

Gyro Drift Calibration in Low Cost Inertial System

1999 ◽  
Author(s):  
Zhong Zhao ◽  
Rong Ma ◽  
Weiguo Zhang
Keyword(s):  
Low Cost ◽  
Fuzzy Reasoning ◽  
Calibration Method ◽  
Inertial System ◽  
Time Varying ◽  
Dynamic Estimation ◽  
Gyro Drift

Abstract An intelligent gyro drift calibration method for low-cost inertial system is presented in this paper. This method based on fuzzy reasoning and dynamic estimation can calibrate time-varying gyro drift in the motion of vehicle. Experiments have been done on three strapdown inertial all-attitude systems constituted of piezoelectric rate gyros. The result shows that this method is effective by which the residual of piezoelectric gyro drift can be reduced to about one percent of its original drift value.

scholarly journals Feedforward ins aiding: an investigation of maneuvers for in-flight alignment

2007 ◽  
Vol 18 (4) ◽  
pp. 459-470 ◽  
Author(s):  
Jacques Waldmann
Keyword(s):  
Autonomous Vehicles ◽  
Inertial Sensors ◽  
Low Cost ◽  
Measurement Unit ◽  
Model Mismatch ◽  
External Data ◽  
Rate Gyro ◽  
External Position ◽  
The Impact ◽  
Gyro Drift

Navigation in autonomous vehicles involves integrating measurements from on-board inertial sensors and external data collected by various sensors. In this paper, the computer-frame velocity error model is augmented with a random constant model of accelerometer bias and rate-gyro drift for use in a Kalman filter-based fusion of a low-cost rotating inertial navigation system (INS) with external position and velocity measurements. The impact of model mismatch and maneuvers on the estimation of misalignment and inertial measurement unit (IMU) error is investigated. Previously, the literature focused on analyzing the stripped observability matrix that results from applying piece-wise constant acceleration segments to a stabilized, gimbaled INS to determine the accuracy of misalignment, accelerometer bias, and rate-gyro drift estimation. However, its validation via covariance analysis neglected model mismatch. Here, a vertically undamped, three channel INS with a rotating IMU with respect to the host vehicle is simulated. Such IMU rotation does not require the accurate mechanism of a gimbaled INS (GINS) and obviates the need to maneuver away from the desired trajectory during in-flight alignment (IFA) with a strapdown IMU. In comparison with a stationary GINS at a known location, IMU rotation enhances estimation of accelerometer bias, and partially improves estimation of rate-gyro drift and misalignment. Finally, combining IMU rotation with distinct acceleration segments yields full observability, thus significantly enhancing estimation of rate-gyro drift and misalignment.

A self-developed indoor three-dimensional pedestrian localization platform based on MEMS sensors

Sensor Review ◽  
2015 ◽  
Vol 35 (2) ◽  
pp. 157-167 ◽  
Author(s):  
Shengbo Sang ◽  
Ruiyong Zhai ◽  
Wendong Zhang ◽  
Qirui Sun ◽  
Zhaoying Zhou
Keyword(s):  
Low Cost ◽  
Angular Rate ◽  
Three Dimensional ◽  
Dead Reckoning ◽  
Rate Data ◽  
Mems Sensors ◽  
Micro Electro Mechanical Systems ◽  
Content Type ◽  
Position Errors ◽  
Low Performance

Purpose – This study aims to design a new low-cost localization platform for estimating the location and orientation of a pedestrian in a building. The micro-electro-mechanical systems (MEMS) sensor error compensation and the algorithm were improved to realize the localization and altitude accuracy. Design/methodology/approach – The platform hardware was designed with common low-performance and inexpensive MEMS sensors, and with a barometric altimeter employed to augment altitude measurement. The inertial navigation system (INS) – extended Kalman filter (EKF) – zero-velocity updating (ZUPT) (INS-EKF-ZUPT [IEZ])-extended methods and pedestrian dead reckoning (PDR) (IEZ + PDR) algorithm were modified and improved with altitude determined by acceleration integration height and pressure altitude. The “AND” logic with acceleration and angular rate data were presented to update the stance phases. Findings – The new platform was tested in real three-dimensional (3D) in-building scenarios, achieved with position errors below 0.5 m for 50-m-long route in corridor and below 0.1 m on stairs. The algorithm is robust enough for both the walking motion and the fast dynamic motion. Originality/value – The paper presents a new self-developed, integrated platform. The IEZ-extended methods, the modified PDR (IEZ + PDR) algorithm and “AND” logic with acceleration and angular rate data can improve the high localization and altitude accuracy. It is a great support for the increasing 3D location demand in indoor cases for universal application with ordinary sensors.

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