Exploring Microsoft Robotics Studio as a Mechanism for Service-Oriented Robotics

Cepeda, Jesús S.; Chaimowicz, Luiz; Soto, Rogelio

doi:10.1109/lars.2010.18

Cited by 16 publications

(20 citation statements)

References 7 publications

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“…"ROS encourages well-defined data flows through ROS-topics and has become popular in recent robot projects due to its open-source BSD (Berkeley Software Distribution) license and good online documentation" (Quigley et al, 2009). Cepeda et al (2010) presented the Microsoft Robotics Developer Studio where they tested speech recognition, vision and sensor-based navigation. The MRDS environment was programmed for robot control and simulation and allows for the achievement of complex behaviours for a wide variety of robot hardware.…”

Section: Software Architecturementioning

confidence: 99%

Mobile sensor platforms: categorisation and research applications in precision farming

Zecha

Link

Claupein

2013

J. Sens. Sens. Syst.

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Abstract. The usage of mobile sensor platforms arose in research a few decades ago. Since the beginning of satellite sensing, measurement principles and analysing methods have become widely implemented for aerial and ground vehicles. Mainly in Europe, the United States and Australia, sensor platforms in precision farming are used for surveying, monitoring and scouting tasks. This review gives an overview of available sensor platforms used in recent agricultural and related research projects. A general categorisation tree for platforms is outlined in this work. Working in manual, automatic or autonomous ways, these ground platforms and unmanned aircraft systems (UAS) with an agricultural scope are presented with their sensor equipment and the possible architectural models. Thanks to advances in highly powerful electronics, smaller devices mounted on platforms have become economically feasible for many applications. Designed to work automatically or autonomously, they will be able to interact in intelligent swarms. Sensor platforms can fulfil the need for developing, testing and optimising new applications in precision farming like weed control or pest management. Furthermore, commercial suppliers of platform hardware used in sensing tasks are listed.

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Section: Software Architecturementioning

confidence: 99%

Mobile sensor platforms: categorisation and research applications in precision farming

Zecha

Link

Claupein

2013

J. Sens. Sens. Syst.

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“…Examples include Webots [3] , Gazebo [4] , CARMEN RNT [5] , Coupled Layer Architecture for Robotic Autonomy (CLARAty) [6], [7] , Microsoft Robotics Developer Studio (MRDS) [8] , Orca [9] , Open Robot Control Software (Orocos) [10] , Player [11] , the Autonomous Mobile Outdoor Robot (AMOR) [12] , and Mobotware [13] . In addition, several efforts have been made toward creating simulation platforms and frameworks that are based on the professional simulators and are customized for agricultural robotics or farm machinery.…”

Section: Simulation Environmentsmentioning

confidence: 99%

“…This is a joint project of UniBots (a university spin-off company based in the UK) and MobotSoft (www.mobotsoft.com) for an academic initiative for easy-to-use by non-programmers to develop a set of designs, tools, and resources to simulate agricultural robots and promote precision agriculture and smart farming [17,18] . The simulation scenes are created in Microsoft Robotics Developer Studio (MRDS) [8] . Sample screenshot from a tractor simulation in SAFAR is shown in Figure 9f.…”

Section: Other Simulators and Virtual Environmentsmentioning

confidence: 99%

“…retrieves the image of a vision sensor as an image array, (3,4): simxReadProximitySensor and simxReadVisionSensor respectively read the state of a proximity and vision sensor (these two functions do not perform detection, but merely reads the result from a previous call to the sensor handles), (5) simxSetJointPosition: sets the intrinsic position of all joints type except the spherical ones (may have no effect depending on the joint mode), (6) simxSetJointTargetPosition, sets the target position of a joint if it is in torque/force mode (joint's motor and position control should be enabled for this function to work), (7) simxSetJointTargetVelocity: sets the intrinsic target velocity of a non-spherical joint (only applicable when the joint is in torque/force mode, and the dynamics functionality and the joint motor have been enabled, and position control is disabled), (8) simxSetVisionSensorImage2: sets the image of a vision sensor and applies any image processing filter if specified in the vision sensor dialog (the image is provided as an image array), and (9) simxStopSimulation: requests a stop of the running simulation. The regular use of simxSetVisionSensorImage2 is to first read the data from a vision sensor with simxSetVisionSensorImage2, then performs custom filtering or image processing, and then writes the modified image to a passive vision sensor.…”

Section: External Programming Of V-rep (Matlab and Ros)mentioning

confidence: 99%

See 1 more Smart Citation

Simulation software and virtual environments for acceleration of agricultural robotics: Features highlights and performance comparison

Shamshiri

Hameed

Pitonakova

et al. 2018

International Journal of Agricultural and Biological Engineering

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Abstract:Research efforts for development of agricultural robots that can effectively perform tedious field tasks have grown significantly in the past decade. Agricultural robots are complex systems that require interdisciplinary collaborations between different research groups for effective task delivery in unstructured crops and plants environments. With the exception of milking robots, the extensive research works that have been carried out in the past two decades for adaptation of robotics in agriculture have not yielded a commercial product to date. To accelerate this pace, simulation approach and evaluation methods in virtual environments can provide an affordable and reliable framework for experimenting with different sensing and acting mechanisms in order to verify the performance functionality of the robot in dynamic scenarios. This paper reviews several professional simulators and custom-built virtual environments that have been used for agricultural robotic applications. The key features and performance efficiency of three selected simulators were also compared. A simulation case study was demonstrated to highlight some of the powerful functionalities of the Virtual Robot Experimentation Platform. Details of the objects and scenes were presented as the proof-of-concept for using a completely simulated robotic platform and sensing systems in a virtual citrus orchard. It was shown that the simulated workspace can provide a configurable and modular prototype robotic system that is capable of adapting to several field conditions and tasks through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment. This review suggests that an open-source software platform for agricultural robotics will significantly accelerate effective collaborations between different research groups for sharing existing workspaces, algorithms, and reusing the materials.

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“…Similarly, Ha et al [19] designed a SOA to support integration among robots and remote sensors in an aware house. With the advent of the first environment focused on the development of SORS, the commercial MRDS, several other systems emerged in literature [7,8]. Currently, ROS development environment is being used as a basis for building a second generation of SORS [25,41].…”

Section: Software Reuse: From Libraries To Servicesmentioning

confidence: 99%

RoboSeT: A Tool to Support Cataloging and Discovery of Services for Service-Oriented Robotic Systems

Oliveira

Amaral

Martins

et al. 2015

Communications in Computer and Information Science

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Abstract. Robotics has played an increasingly important role in several sectors of the society. Nowadays, robots are not only used to support activities in factories, but also to assist house cleaning, border surveillance, and even surgeries. The variety of application domains and the rising complexity are challenging the design of robotic systems that control such robots. In this perspective, Service-Oriented Architecture (SOA) has been adopted as a promising architectural style to design large, complex robotic systems in a flexible and reusable manner. Several Service-Oriented Robotic Systems (SORS) have been developed in the recent years and a large number of services are available for reuse. Nevertheless, none of the environments dedicated to the development of SORS provide an efficient mechanism for publishing and discovering services. As a consequence, services for SORS have to be manually searched, reducing significantly the potential of reuse and productivity provided by SOA. This paper presents RoboSeT, a mechanism that supports cataloging and discovery of services for robotic systems. RoboSeT is based on semantic search and classifies the services using a taxonomy of the robotics domain. Results of our case study indicate that RoboSeT facilitates the development of robotic systems, since it presents the potential to widely promote reusability of services for SORS.

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Exploring Microsoft Robotics Studio as a Mechanism for Service-Oriented Robotics

Cited by 16 publications

References 7 publications

Mobile sensor platforms: categorisation and research applications in precision farming

Mobile sensor platforms: categorisation and research applications in precision farming

Simulation software and virtual environments for acceleration of agricultural robotics: Features highlights and performance comparison

RoboSeT: A Tool to Support Cataloging and Discovery of Services for Service-Oriented Robotic Systems

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