Low Cost Sensor Data Fusion in Omnidirectional Mobile Robot Feedback System to Improve the Navigation Accuracy

2014 ◽  
Vol 607 ◽  
pp. 791-794 ◽  
Author(s):  
Wei Kang Tey ◽  
Che Fai Yeong ◽  
Yip Loon Seow ◽  
Eileen Lee Ming Su ◽  
Swee Ho Tang
Keyword(s):  
Mobile Robot ◽  
Sensor Fusion ◽  
Low Cost ◽  
Feedback System ◽  
Sensor Data ◽  
Research Setting ◽  
Fusion Technique ◽  
Omnidirectional Mobile Robot ◽  
The Cost ◽  
Navigation Accuracy

Omnidirectional mobile robot has gained popularity among researchers. However, omnidirectional mobile robot is rarely been applied in industry field especially in the factory which is relatively more dynamic than normal research setting condition. Hence, it is very important to have a stable yet reliable feedback system to allow a more efficient and better performance controller on the robot. In order to ensure the reliability of the robot, many of the researchers use high cost solution in the feedback of the robot. For example, there are researchers use global camera as feedback. This solution has increases the cost of the robot setup fee to a relatively high amount. The setup system is also hard to modify and lack of flexibility. In this paper, a novel sensor fusion technique is proposed and the result is discussed.

scholarly journals NanoSen-AQM: From Sensors to Users

2020 ◽  
Vol 16 (04) ◽  
pp. 51
Author(s):  
Pedro Lucas ◽  
Jorge Silva ◽  
Filipe Araujo ◽  
Catarina Silva ◽  
Paulo Gil ◽  
...  
Keyword(s):  
Air Quality ◽  
Low Cost ◽  
Sensor Data ◽  
Quality Data ◽  
Easy Access ◽  
The Public ◽  
Nano Sensors ◽  
The Cost ◽  
Air Quality Data ◽  
Monitoring Platform

With the raising of environmental concerns regarding pollution, interest in monitoring air quality is increasing. However, air pollution data is mostly originated from a limited number of government-owned sensors, which can only capture a small fraction of reality. Improving air quality coverage in-volves reducing the cost of sensors and making data widely available to the public. To this end, the NanoSen-AQM project proposes the usage of low-cost nano-sensors as the basis for an air quality monitoring platform, capa-ble of collecting, aggregating, processing, storing, and displaying air quality data. Being an end-to-end system, the platform allows sensor owners to manage their sensors, as well as define calibration functions, that can im-prove data reliability. The public can visualize sensor data in a map, define specific clusters (groups of sensors) as favorites and set alerts in the event of bad air quality in certain sensors. The NanoSen-AQM platform provides easy access to air quality data, with the aim of improving public health.

A new approach using sensor data fusion for mobile robot navigation

Robotica ◽  
2004 ◽  
Vol 22 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Tae-Seok Jin ◽  
Jang Myung Lee ◽  
S. K. Tso
Keyword(s):  
Mobile Robot ◽  
Sensor Fusion ◽  
Current Data ◽  
Sensor Data ◽  
Mobile Robot Navigation ◽  
Service Robots ◽  
Mobile Service ◽  
Data Sets ◽  
Sensing System ◽  
Visual Sensing

To fully utilize the information from the sensors, this paper proposes a new sensor-fusion technique where the data sets for the previous moments are properly transformed and fused into the current data sets to enable an accurate measurement. Exploration of an unknown environment is an important task for the new generation of mobile service robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. Note that in the conventional fusion schemes, the measurement is dependent on the current data sets only. Therefore, more of sensors are required to measure a certain physical parameter or to improve the accuracy of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequence of the data sets are stored and utilized for the accurate measurement. The theoretical basis is illustrated by examples and the effectiveness is proved through the simulations and experiments. The newly proposed, STSF (Space and Time Sensor Fusion) scheme is applied to the navigation of a mobile robot in an unstructured environment, as well as in structured environment, and the experimental results show the performance of the system.

scholarly journals Network-Oriented Real-Time Embedded System Considering Synchronous Joint Space Motion for an Omnidirectional Mobile Robot

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 317 ◽  
Author(s):  
Raimarius Delgado ◽  
Byoung Choi
Keyword(s):  
Mobile Robot ◽  
Embedded System ◽  
Real Time ◽  
Low Cost ◽  
Joint Space ◽  
Geometric Constraints ◽  
Real Time Control ◽  
Synchronization Mechanism ◽  
Omnidirectional Mobile Robot ◽  
Time Control

This paper proposes a real-time embedded system for joint space control of omnidirectional mobile robots. Actuators driving an omnidirectional mobile robot are connected in a line topology which requires synchronization to move simultaneously in translation and rotation. We employ EtherCAT, a real-time Ethernet network, to control servo controllers for the mobile robot. The first part of this study focuses on the design of a low-cost embedded system utilizing an open-source EtherCAT master. Although satisfying real-time constraints is critical, a desired trajectory on the center of the mobile robot should be decomposed into the joint space to drive the servo controllers. For the center of the robot, a convolution-based path planner and a corresponding joint space control algorithm are presented considering its physical limits. To avoid obstacles that introduce geometric constraints on the curved path, a trajectory generation algorithm considering high curvature turning points is adapted for an omnidirectional mobile robot. Tracking a high curvature path increases mathematical complexity, which requires precise synchronization between the actuators of the mobile robot. An improvement of the distributed clock—the synchronization mechanism of EtherCAT for slaves—is presented and applied to the joint controllers of the mobile robot. The local time of the EtherCAT master is dynamically adjusted according to the drift of the reference slave, which minimizes the synchronization error between each joint. Experiments are conducted on our own developed four-wheeled omnidirectional mobile robot. The experiment results confirm that the proposed system is very effective in real-time control applications for precise motion control of the robot even for tracking high curvature paths.

Dynamic Estimation of Water Hyacinth Area by Fusing Data from Satellite and GPS Sensors

2014 ◽  
Vol 511-512 ◽  
pp. 134-137
Author(s):  
Ling Sun ◽  
Ze Sheng Zhu
Keyword(s):  
Sensor Fusion ◽  
Growth Model ◽  
Water Hyacinth ◽  
Goodness Of Fit ◽  
Model Development ◽  
Sensor Data ◽  
Complete Control ◽  
Fusion Technique ◽  
Area Growth ◽  
Dynamic Estimation

The interaction of water hyacinth area with growth is known to be strongly influenced by area size, but little is known about the interdependent role that size and time have on dynamic estimation of water hyacinth area. We report on the fusion of specially designed, satellite and GPS sensor data into area growth model as a function of area and time. We employ a multi-sensor fusion technique that is able to generate uniform data of fitting area growth model with complete control of area and time. Evidence of an overall Goodness of Fit Index of 0.9753 was obtained by using conventional statistic analysis. These findings suggest that the multi-sensor fusion technique readily supports area growth model development with highly resolution. Moreover, it was found that area growth model enjoy an appreciable advantage when it comes to harvesting water hyacinth.

A SENSOR DATA FUSION ALGORITHM FOR INDOOR SLAM USING A LOW-COST MOBILE ROBOT

2012 ◽  
pp. 762-769
Author(s):  
LUCIANO BUONOCORE ◽  
AEROLINO DE ALMEIDA NETO ◽  
CAIRO LÚCIO NASCIMENTO JÚNIOR
Keyword(s):  
Data Fusion ◽  
Mobile Robot ◽  
Low Cost ◽  
Sensor Data ◽  
Fusion Algorithm ◽  
Sensor Data Fusion

scholarly journals LoRaWAN Geo-Tracking Using Map Matching and Compass Sensor Fusion

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5815
Author(s):  
Nico Podevijn ◽  
Jens Trogh ◽  
Michiel Aernouts ◽  
Rafael Berkvens ◽  
Luc Martens ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Energy Efficient ◽  
Low Cost ◽  
Map Matching ◽  
Directional Information ◽  
Matching Algorithm ◽  
Additional Information ◽  
Energy Impact ◽  
Node Location ◽  
The Cost

In contrast to accurate GPS-based localization, approaches to localize within LoRaWAN networks offer the advantages of being low power and low cost. This targets a very different set of use cases and applications on the market where accuracy is not the main considered metric. The localization is performed by the Time Difference of Arrival (TDoA) method and provides discrete position estimates on a map. An accurate “tracking-on-demand” mode for retrieving lost and stolen assets is important. To enable this mode, we propose deploying an e-compass in the mobile LoRa node, which frequently communicates directional information via the payload of the LoRaWAN uplink messages. Fusing this additional information with raw TDoA estimates in a map matching algorithm enables us to estimate the node location with a much increased accuracy. It is shown that this sensor fusion technique outperforms raw TDoA at the cost of only embedding a low-cost e-compass. For driving, cycling, and walking trajectories, we obtained minimal improvements of 65, 76, and 82% on the median errors which were reduced from 206 to 68 m, 197 to 47 m, and 175 to 31 m, respectively. The energy impact of adding an e-compass is limited: energy consumption increases by only 10% compared to traditional LoRa localization, resulting in a solution that is still 14 times more energy-efficient than a GPS-over-LoRa solution.

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