Development of a Control Platform for the Mobile Robot Roomba Using ROS and a Kinect Sensor

Ruiz, Elvis; Acuña, Raul; Certad, Novel; Terrones, Angel; Cabrera, María Eugenia

doi:10.1109/lars.2013.57

Cited by 20 publications

(12 citation statements)

References 3 publications

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“…The maximum speed of the robot is 0.5m/s in both forward and reverse directions. [6] The embedded robot controller is capable of controlling basic functions of the robot including travelling at either a desired distant or speed and handle all the sensor signals.…”

Section: Irobot Creatementioning

confidence: 99%

Automatic Docking with Obstacle Avoidance of a Differential Wheel Mobile Robot

Poomarin¹,

Chancharoen²,

Sangveraphunsiri³

2016

IJMERR

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The paper presents a technique and a system that can be used to smoothly dock a differential drive mobile robot. The system consists of only a robot, a RGBD camera, and a notebook computer which are connected via USB cable. The RGBD camera with the proposed processing technique is capable of determining the Cartesian positions of a home base, obstacles, a floor, and a wall. They are then plotted on a 2D grip map where a free trajectory towards the home based can be constructed. This trajectory is then used to guide the robot to dock at the home base. Experimental result is used to demonstrate the applicable of the proposed technique. 

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Section: Irobot Creatementioning

confidence: 99%

Automatic Docking with Obstacle Avoidance of a Differential Wheel Mobile Robot

Poomarin¹,

Chancharoen²,

Sangveraphunsiri³

2016

IJMERR

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“…Their dimension is more than 30 cm x 15 cm, consequently not suitable for academic purpose especially when the testing area is limited [8]- [13]. Therefore, there is a need a small size robot to be designed that uses an embedded Linux single-board computer.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Robot Operating System in Beaglebone Black based Mobile Robot for Obstacle Avoidance Application

Zakaria¹,

Shing²,

Tomari³

2017

International Journal on Advanced Science, Engineering and Information Technology

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Abstract-The Robot Operating System (ROS) is a collection of tools, libraries, and conventions that focus on simplifying the task of creating a complex and advanced robotics system. Its standard framework can be shared with another robotics system that has a similar platform and suitable for being introduced as an educational tool in robotics. However, the problems found out in the current robot platform available in the market are expensive and encapsulated. The development of an open source robot platform is encouraged. Therefore, this research is carried out to design and develop an ROS based obstacle avoidance system for existing differential-wheeled mobile robot. The ROS was installed under Ubuntu 14.04 on a Beaglebone Black embedded computer system. Then, the ROS was implemented together with the obstacle avoidance system to establish the communication between program nodes. The mobile robot was then designed and developed to examine the obstacle avoidance application. The debugging process was carried out to check the obstacle avoidance system application based on the communication between nodes. This process is important in examining the message publishing and subscribing from all nodes. The obstacle avoidance mobile robot has been successfully tested where the communication between nodes was running without any problem.

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“…In on-site investigation, it is found that the places below the fruits are spacious with less sheltering and the background is simple, so the writer proposes that the fruits be identified, positioned, and picked from the bottom parts of the plants. The principle is like this: determine the sequence of fruit identification, feature point extraction and fruit picking by using elliptic Hough conversion; acquire the feature point coordinates of the images with Kinect sensors made by Microsoft Company; obtain the image coordinates of feature points by Kinect sensor referring the foreign research results for Microsoft Kinect sensor in robot navigation [11][12] and feature recognition [13][14][15]; finally, conduct coordinates conversion between the camera and sensors and construct mathematical model of the coordinates conversion to obtain the 3D coordinates of the feature points. In Figure 1, due to the greater scene depth, and complicated background, it can be seen that the images of fruits taken from the side contain not only the leaves of the near-byplant branches, but also distant non-target fruits, and serious mutual occlusion between the target fruits.…”

Section: Introductionmentioning

confidence: 99%

“…Since the spatial position of the Microsoft camera and Kinect sensors remain unchanged, pixel coordinates of feature point A in the imaged captured by Kinect sensor can be derived from the pixel coordinates of the feature point 'A' in the camera image shot by the Microsoft camera. That is (x − 320) + X = b(x ′ − 320)(11) (y − 180) + Y = b(y ′ − 240)(12)From equations(11) and(12), we can get the following formulas:…”

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confidence: 99%

The Acquisition of Kiwifruit Feature Point Coordinates Based on the Spatial Coordinates of Image

Wang

Chen

Gao

et al. 2016

Computer and Computing Technologies in Agriculture IX

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How to obtain the spatial coordinates of kiwi fruit has been one of the key techniques for kiwi fruit harvesting robot. In this paper, the writer proposes a unique way to obtain the spatial coordinates of the features of kiwi fruit from the bottom of the target fruit based on the growth characteristics and scaffolding cultivation pattern characteristicsof kiwi fruit, plus the help of Microsoft camera and Kinect sensor. Also included in this paper is the coordinate conversion between the images come from Microsoft camera and the images of the Kinect sensor, which is followed by an analysis of the precision of the spatial coordinates of Kiwi fruit captured by the Microsoft camera and Kinect sensor. The process is like this: first, capture images of the target fruit from the bottom of the fruit with Microsoft camera, and then extract coordinates of the target fruits' feature points to determine the corresponding target fruit feature point coordinates in the Kinect sensor; second, analyze the correspondence between the Microsoft camera image coordinate system and the Kinect sensor image coordinate system so as to establish amathematical model for the image coordinate conversion; finally,capture target feature points' spatial coordinates with Kinect sensorand conduct tests. The results show that the precision of coordinate conversion mode and Kiwifruit spatial coordinates can meet the requirements of the harvesting robots.

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Development of a Control Platform for the Mobile Robot Roomba Using ROS and a Kinect Sensor

Cited by 20 publications

References 3 publications

Automatic Docking with Obstacle Avoidance of a Differential Wheel Mobile Robot

Automatic Docking with Obstacle Avoidance of a Differential Wheel Mobile Robot

Implementation of Robot Operating System in Beaglebone Black based Mobile Robot for Obstacle Avoidance Application

The Acquisition of Kiwifruit Feature Point Coordinates Based on the Spatial Coordinates of Image

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