A new method for indoor low-cost mobile robot SLAM

Localization is one of many issues in mobile robot study. Localization is an essential ability for mobile robot to determine its location, so that it can plan a movement and go to a desired location. The mutual method for mobile robot localization is using a particle filter. High computation needs in particle filter is one of problem in particle filtering to get accurate location. The paper proposes a low computational mobile robot localization using a particle filter. It uses two methods: local localization using a dead reckoning method and global localization using a landmark-based vision sensor. Simulation results show that the proposed method provides a good estimation on the mobile robot position and orientation.

In this paper, we propose a novel method for mobile robot localization and navigation based on multispectral visual odometry (MVO). The proposed approach consists in combining visible and infrared images to localize the mobile robot under different conditions (day, night, indoor and outdoor). The depth image acquired by the Kinect sensor is very sensitive for IR luminosity, which makes it not very useful for outdoor localization. So, we propose an efficient solution for the aforementioned Kinect limitation based on three navigation modes: indoor localization based on RGB/depth images, night localization based on depth/IR images and outdoor localization using multispectral stereovision RGB/IR. For automatic selection of the appropriate navigation modes, we proposed a fuzzy logic controller based on images’ energies. To overcome the limitation of the multimodal visual navigation (MMVN) especially during navigation mode switching, a smooth variable structure filter (SVSF) is implemented to fuse the MVO pose with the wheel odometry (WO) pose based on the variable structure theory. The proposed approaches are validated with success experimentally for trajectory tracking using the mobile robot (Pioneer P3-AT).

This paper aims to design and implement an indoor localization method for mobile robots based on trilateration technique, Color Code signatures (CCs) as artificial passive beacons, and a depth camera. The artificial passive beacons are designed as three disks positioned one on top of the other’s with different sizes and colors (primary colors only, RGB). The three disks share the same center. The designed beacons are placed on the ceiling to be visible from most locations within the room. The robot's model, controller, and localization method are implemented and evaluated inside the CoppeliaSim environment. The simulation results show that the CCs detecting algorithm enables the robot to discover the designed beacons, achieve an accurate localization and reach the target

Owing to the presence of multiple obstacles or changes in the positions of surroundings objects, the localization of a mobile robot using only natural landmarks is difficult in indoor environments. Consequently, in these environments, the use of artificial landmarks to achieve robust localization is necessary. To this end, we propose a global localization method for mobile robots, using reflectors as indistinguishable artificial landmarks, not the manmade signs have a certain pattern. In previous studies, it has been shown that localization is possible using information about the distance between indistinguishable artificial landmarks. We applied this principle in a real-world situation with many obstacles or in a dynamic environment and confirmed that robust, high-accuracy global localization is possible.

Mobile robot localization based on omnicamera

To promote robotic soccer research, we need a low cost and portable robot with some sensors and a communication device. To date, there is no platform for robotic soccer. Therefore, each research must build his own robots or utilize robots which are commercially available. This paper describes how to construct a robot system which includes a lightweight and low-cost mobile robot with visual, tactile sensors, TCP/IP communication device, and portable PC where Linux is running. An example of the developed soccer robot system and preliminary experimental results are also shown.

This paper proposes a new localization method for indoor mobile robots. Using two cameras and one laser range finder on board a TRC mobile robot, the initial position and pose of the robot can be obtained by multisensor fusion and scene matching based on geometric hashing. No correspondence calculation and special pattern recognition are needed during the scene matching. This localization method can be implemented in five stages: 1) Model the indoor environment. Some selected indoor environment features are firstly modeled off-line into hashing tables. 2) Perform system calibration and information fusion from two cameras and the range finder. 3) Extract the vertical edge points corresponding to the horizontal scanning plane of the 2D laser range finder from the scene images and transform them into geometric invariants. 4) Perform scene matching and matching verification by geometric hashing and model back- projection method respectively. 5) Perform position and pose estimation by a least square fit method. Experimental results show that the accuracy and reliability of this localization method ar quite high.

This paper presents a global localization method for mobile robots based on the geometric information of structured indoor environments. With a global/local point cloud and projection map, lines are extracted from the projection maps using Hough transform. According to the directions of the obtained lines, the orientations of projection maps and point clouds are normalized. Next, the template matching algorithm is applied to the normalized global and local projection maps. Once coarse localization is completed, final accurate localization is achieved using the Iterative Closest Points (ICP) algorithm. Experimental results on several point clouds show that the proposed method can achieve high localization accuracy in real-time. The proposed method can be used for other global localization applications in structured environments.

With increasing attention to urban temperature and outdoor thermal comfort, monitoring urban microenvironments at a lower cost is an effective method to supplement the spatiotemporal deficiencies of traditional monitoring networks. But widespread use of low-cost sensors has been hampered by uncertainty about their data quality. The calibration of low-cost sensors is key to promoting their large-scale application and increasing people's confidence in related research. The purpose of this study is to calibrate low-cost integrated environmental sensors and effectively improve their hourly data quality based on an IoT case study in Wuhan, China.Based on the standards of 24 traditional weather stations in different locations of the meteorological regulatory authorities, this study applied a total of eight machine learning (ML) algorithms to calibrate low-cost sensors and compared their performance. The eight ML algorithms are: (a) Multiple Linear Regression (MLR); (b) Random Forest (RF); (c) K-Nearest Neighbors (KNN); (d) Gradient Boosting Regression Tree (GBRT); (e) Decision Tree (DT); (f) AdaBoost; (g) Bagging; (h) Extremely randomized Trees (Extra-Trees). Hourly raw data collected by 34 low-cost sensors deployed near traditional weather stations were calibrated, and the model was tested using ten-fold cross-validation. The two farthest locations are 121km apart in a straight line, and the maximum data collected from a single sensor is 12,406 hours. In addition, the model migration effects in different field scenarios were also considered, including six typical land surface types, namely built area, scrub, water, artificial surfaces, woodland, and cultivated land.The results show that the random forest model shows better performance than other models on multiple low-cost sensors at different locations. By applying our method, it shows an average improvement with its R-squared value from 0.682 to 0.980, Root Mean Square Error (RMSE) from 5.989 to 1.355, and Mean Absolute Error (MAE) from 4.250 to 0.932. The random forest model has a better migration effect in similar scenarios. Using a model with a surface type that is more similar to the sensor to be calibrated, the average R-squared obtained by calibrating 34 sensors is 0.946, and the average MAE is 1.584. At the same time, the distance between the sensor to be calibrated and the best-performing migration model was also considered, with the farthest straight-line distance being 94km and the nearest being 7km.This study introduces a calibration method for low-cost meteorological integrated sensors for long-term complex field environment monitoring. Moreover, we compared the migration effect of the random forest model in different typical scenes in the field. Similar surface types are more beneficial to model migration. Even in locations far apart, our model still has stable performance. The results show that this method can significantly improve data quality and increase user confidence in low-cost environmental sensor applications.

The recent research advancements in the field of chemical sensors, distributed sensing and wireless networking have led to development of several low-cost optical aerosol sensors. These sensors are based on the principle of particle light scattering, and are dependent on several parameters - temperature, relative humidity, particle size, and particle concentration. However, the linearity of the response of these sensors over a wide concentration range has not been well studied. We evaluated a low-cost particulate matter measuring sensor (BlueSky Air Monitor Model 8143 TSI Inc) in different environments. The particulate matter concentration of PM10, PM4, PM2.5 and PM1 were compared with reference measurements using a Dust Trak Model 8534 TSI Inc- a widely used light scattering instrument. Several methodologies were developed to generate wide concentration of aerosols. The concentration ranges for the lower end were created in indoor environmental conditions (0.003-0.004 mg/m3) and for the higher end were created in a chamber with e-cigarette vaping (0.006- 30 mg/m3). The intermediate concentrations (0.003- 2 mg/m3) were obtained using a Concentrated Air Particulate System (CAPS) consisting of a virtual impactor setup that magnifies ambient concentration by an adjustable enrichment factor between 5-20. Results of the present study indicate that the BlueSky low cost sensor compares well with the reference instrument (R2 = 0.92; Intercept ~0; Slope = 0.75). The novel design of the CAPS including maintaining an uniform temperature and humidity makes it an ideal design for characterizing low cost sensors over a wide range of concentrations. The findings of the present study can be used to design more robust methodologies for laboratory testing for low cost air quality sensors at different concentrations.

Currently, mobile robots are developing rapidly and are finding numerous applications in the industry. However, several problems remain related to their practical use, such as the need for expensive hardware and high power consumption levels. In this study, we build a low-cost indoor mobile robot platform that does not include a LiDAR or a GPU. Then, we design an autonomous navigation architecture that guarantees real-time performance on our platform with an RGB-D camera and a low-end off-the-shelf single board computer. The overall system includes SLAM, global path planning, ground segmentation, and motion planning. The proposed ground segmentation approach extracts a traversability map from raw depth images for the safe driving of low-body mobile robots. We apply both rule-based and learning-based navigation policies using the traversability map. Running sensor data processing and other autonomous driving components simultaneously, our navigation policies perform rapidly at a refresh rate of 18 Hz for control command, whereas other systems have slower refresh rates. Our methods show better performances than current state-of-the-art navigation approaches within limited computation resources as shown in 3D simulation tests. In addition, we demonstrate the applicability of our mobile robot system through successful autonomous driving in an indoor environment.

With the increasing demand for indoor navigation applications, indoor navigation has become a research hotspot in many technical fields. High-precision sensors are expensive, and they are often used in industrial and aerospace applications. Low-cost sensors can cause severe drift and noise. This paper uses a simple, low-cost Inertial measurement unit (IMU) and effectively evaluates the precise position of pedestrians. This paper designs a pedestrian position estimation based on low-cost inertial sensors. To solve the problem of inertial sensing noise and accumulated errors during the movement, based on the EKF algorithm, a multi-condition threshold detection method is proposed, and then a zero-speed update, an angular speed update, and a yaw angle update are designed. In the measurement state, the proposed measurement error vector effectively eliminates the cumulative error during walking. Finally, using this algorithm to perform straight and rectangular walking routes, corresponding experiments were performed on the effectiveness of the method used. The proposed method for estimating the inertial navigation of pedestrians has an error within 3.8%. This basic research is of great significance in rehabilitation training and somatosensory play.

Researches on mobile robots have been mainly focused on the autonomous navigation and a lot of interesting results have been published so far. Most of applications are, however, fancy, unpractical, and very expensive to be used for un-expensive purpose. Well-known soccer robot may be an example of unpractical application. Un-autonomous mobile robot has, however, potential for a lot of practical applications. Especially, tele-operation of the un-autonomous mobile robot may the central hot issue of the related researches. Major research topics for the tele-operated un-autonomous mobile include development of force reflecting joystick for tele-operation and development of sophisticated algorithm for smooth tele-operation. HILS system for a low-cost un-autonomous tele-operated mobile robot is developed in this research. Main contribution of this paper is the development of new fuzzy command smoothing concept for smooth tele-operation of un-autonomous mobile robot with many obstacles around.

In 2013 the Editor of Journal of Vibration and Control and SAGE became aware of a peer review ring involving assumed and fabricated identities that appeared to centre around Peter Chen at National Pingtung University of Education, Taiwan (NPUE). SAGE and the Editor then began a complex investigation into the case during the rest of 2013 and 2014. Following an unsatisfactory response from Peter Chen, NPUE was notified. NPUE were serious in addressing the Journal and SAGE’s concerns. NPUE confirmed that the institution was investigating Peter Chen. SAGE subsequently uncovered a citation ring involving the above mentioned author and others. We regret that individual authors have compromised the academic record by perverting the peer review process and apologise to readers. On uncovering problems with peer review and citation SAGE immediately put steps in place to avoid similar vulnerability of the Journal to exploitation in the future. More information may be found at www.sagepub.co.uk/JVC_Statement_2014 . The Journal and SAGE understand from NPUE that Peter Chen has resigned his post at NPUE. The following articles are retracted because after thorough investigation evidence points towards them having at least one author or being reviewed by at least one reviewer who has been implicated in the peer review ring and/or citation ring. All authors have had an opportunity to respond to the allegations and proposed actions. OnlineFirst articles (these articles will not be published in an issue) Chen CY, Chen T-H, Chen Y-H, Yu S-E and Chung P-Y (2013) Information technology system modeling an integrated C-TAM-TPB model to the validation of ocean tidal analyses Journal of Vibration and Control Epub ahead of print 7 May 2013. doi: 10.1177/1077546312472924 Chang R-F, Chen CY, Su F-P and Lin H-C (2013) A two-step approach for broadband digital signal processing technique Journal of Vibration and Control Epub ahead of print 26 April 2013. doi: 10.1177/1077546312472925 Chen TH, Chang CJ, Yu SE, Chung PY and Liu C-K (2013) Nonlinear information analysis and system management technique: the influence of design experience and control complexity Journal of Vibration and Control Epub ahead of print 12 April 2013. doi: 10.1177/1077546312473321 Chen CY, Shih BY, Chen YH, Yu SE and Liu YC (2013) The exploration of a 3T flow model using vibrating NXT: II. Model validation Journal of Vibration and Control Epub ahead of print 10 April 2013. doi: 10.1177/1077546312470481 Chen CY, Shih BY, Chen YH, Yu SE and Liu YC (2013) The exploration of 3T flow model using vibrating NXT: I. model formulation Journal of Vibration and Control Epub ahead of print 6 February 2013. doi: 10.1177/1077546312467360 Lin M-L and Chen C-W (2013) Stability analysis of fuzzy-based NN modeling for ecosystems using fuzzy Lyapunov methods Journal of Vibration and Control Epub ahead of print 6 February 2013. doi: 10.1177/1077546312466687 Chen CY, Chen TH, Chen YH and Chiu J (2012) A multi-stage method for deterministic-statistical analysis: a mathematical case and measurement studies Journal of Vibration and Control Epub ahead of print 20 December 2012. doi: 10.1177/1077546312466579 Shih BY, Lin MC and Chen CY (2012) Autonomous navigation system for radiofrequency identification mobile robot e-book reader Journal of Vibration and Control Epub ahead of print 13 December 2012. doi: 10.1177/1077546312466578 Chang RF, Chen CY, Su FP, Lin HC and Lu C-K (2012) Multiphase SUMO robot based on an agile modeling-driven process for a small mobile robot Journal of Vibration and Control Epub ahead of print 13 December 2012. doi: 10.1177/1077546312464993 Shih B-Y, Lin Y-K, Cheng M-H, Chen C-Y and Chiu C-P (2012) The development of an application program interactive game-based information system Journal of Vibration and Control Epub ahead of print 12 December 2012. doi: 10.1177/1077546312464682 Chen C-Y, Chang C-J and Lin C-H (2012) On dynamic access control in web 2.0 and cloud interactive information hub: technologies Journal of Vibration and Control Epub ahead of print 12 December 2012. doi: 10.1177/1077546312464992 Shin BY, Chen CY and Hsu KH (2012) Robot cross platform system using innovative interactive theory and selection algorithms for Android application Journal of Vibration and Control Epub ahead of print 13 November 2012. doi: 10.1177/1077546312463757 Articles published in an issue Chen C-W (2014) Applications of neural-network-based fuzzy logic control to a nonlinear time-delay chaotic system Journal of Vibration and Control 20 (4): 589-605. Epub ahead of print 5 November 2012. doi: 10.1177/1077546312461370 Chen C-W (2014) A review of intelligent algorithm approaches and neural-fuzzy stability criteria for time-delay tension leg platform systems Journal of Vibration and Control 20 (4): 561-575. Epub ahead of print 5 November 2012. doi: 10.1177/1077546312463759 Chen C-Y, Chang C-J and Lin C-H (2014) On dynamic access control in web 2.0 and cloud interactive information hub: trends and theories Journal of Vibration and Control 20 (4): 548-560. Epub ahead of print 5 November 2012. doi: 10.1177/1077546312463762 Lin M-L and Chen C-W (2014) Stability conditions for ecosystem modeling using the fuzzy Lyapunov method Journal of Vibration and Control 20 (2): 290-302. Epub ahead of print 23 October 2012. doi: 10.1177/1077546312451301 Chen C-H, Kuo C-M, Hsieh S-H and Chen C-Y (2014) Highly efficient very-large-scale integration (VLSI) implementation of probabilistic neural network image interpolator Journal of Vibration and Control 20 (2): 218-224. Epub ahead of print 22 October 2012. doi: 10.1177/1077546312458822 Chen C-Y (2014) Wave vibration and simulation in dissipative media described by irregular boundary surfaces: a mathematical formulation Journal of Vibration and Control 20 (2): 191-203. Epub ahead of print 22 October 2012. doi: 10.1177/1077546312464258 Chen C-H, Yao T-K, Dai J-H and Chen C-Y (2014) A pipelined multiprocessor system- on-a-chip (SoC) design methodology for streaming signal processing Journal of Vibration and Control 20 (2): 163-178. Epub ahead of print 16 October 2012. doi: 10.1177/1077546312458821 Lin M-L and Chen C-W (2014) Fuzzy neural modeling for n-degree ecosystems using the linear matrix inequality approach Journal of Vibration and Control 20 (1): 82-93. Epub ahead of print 8 October 2012. doi: 10.1177/1077546312458533 Chen C-H, Wu W-X and Chen C-Y (2013) Ant-inspired collective problem-solving systems Journal of Vibration and Control 19 (16): 2481-2490. Epub ahead of print 18 September 2012. doi: 10.1177/1077546312456231 Chen C-H, Yao T-K, Kuo C-M and Chen C-Y (2013) Evolutionary design of constructive multilayer feedforward neural network Journal of Vibration and Control 19 (16): 2413-2420. Epub ahead of print 12 September 2012. doi: 10.1177/1077546312456726 Chen C-W (2013) Applications of the fuzzy-neural Lyapunov criterion to multiple time-delay systems Journal of Vibration and Control 19 (13): 2054-2067. Epub ahead of print 16 August 2012. doi: 10.1177/1077546312451034 Chung P-Y, Chen Y-H, Walter L and Chen C-Y (2013) Influence and dynamics of a mobile robot control on mechanical components Journal of Vibration and Control 19 (13): 1923-1935. Epub ahead of print 20 July 2012. doi: 10.1177/1077546312452184 Chen C-W (2013) Neural network-based fuzzy logic parallel distributed compensation controller for structural system Journal of Vibration and Control 19 (11): 1709-1727. Epub ahead of print 22 June 2012. doi: 10.1177/1077546312442233 Chen C-W, Yeh K, Yang H-C, Liu KFR and Liu C-C (2013) A critical review of structural system control by the large-scaled neural network linear-deferential-inclusion-based criterion Journal of Vibration and Control 19 (11): 1658-1673. Epub ahead of print 18 June 2012. doi: 10.1177/1077546312443377 Chen C-H, Kuo C-M, Chen C-Y and Dai J-H (2013) The design and synthesis using hierarchical robotic discrete-event modeling Journal of Vibration and Control 19 (11): 1603-1613. Epub ahead of print 27 June 2012. doi: 10.1177/1077546312449645 Chang CJ, Chen CY and Chou I-T (2013) The design of information and communication technologies: telecom MOD strength machines Journal of Vibration and Control 19 (10): 1499-1513. Epub ahead of print 27 June 2012. doi: 10.1177/1077546312449644 Shih B-Y, Chen C-Y, Li K-H, Wu T-Y, Chen G-Y (2013) A novel NXT control method for implementing force sensing and recycling in a training robot Journal of Vibration and Control 19 (10): 1443-1459. Epub ahead of print 1 June 2012. doi: 10.1177/1077546312446361 Chen C-W, Chen P-C and Chiang W-L (2013) Modified intelligent genetic algorithm-based adaptive neural network control for uncertain structural systems Journal of Vibration and Control 19 (9): 1333-1347. Epub ahead of print 31 May 2012. doi: 10.1177/1077546312442232 Chen C-Y, Shih B-Y, Shih C-H and Wang L-H (2013) Enhancing robust and stability control of a humanoid biped robot: system identification approach. Journal of Vibration and Control 19 (8): 1199-1207. Epub ahead of print 26 April 2012. doi: 10.1177/1077546312442947 Chang C-J, Chen C-Y and Huang C-W (2013) Applications for medical recovery using wireless control of a bluetooth ball with a hybrid G-sensor and human-computer interface technology Journal of Vi

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