Several different architectures has been suggested for agricultural robotic vehicles like Agriture, The Hortibot and AgroBot linux shared memory based architecture, or the FroboMind.This work present the implementation of the latter conceptual architecture FroboMind utilising the open-source cross language robotic framework ROS.Secondly a rugged hardware platform FroboBox is presented

Bøgild, Anders

Jensen, Kjeld

Jørgensen, Rasmus Nyholm

Kjærhus Bertelsen, Keld

Nielsen, Søren Hundevadt

English

Bertelsen, Keld Kjærhus

Organic Eprints

Conference: http://www.njf.nu/site/seminarRedirect.asp?intSeminarID=441&p=1004 Implementations of FroboMind  using the Robot Operating System framework  Søren Hundevadt Nielsen1, Anders Bøgild2, Kjeld Jensen1, Keld Kjærhus Bertelsen1, Rasmus N. Jørgensen1 1Institute of Chemical Engineering, Biotechnology and Environmental Technology 2The Maersk Mc-Kinney Moller Institute University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark  Corresponding author: shn[a]kbm.sdu.dk   Introduction Several  different  architectures  has  been  suggested  for  agricultural  robotic  vehicles  like Agriture  (Nebot  et  al.  2011),  The  Hortibot  and  AgroBot  linux  shared  memory  based architecture (Jørgensen et al. 2007), or the FroboMind (Jensen et al. 2011). Implementing the different architectures across universities and platforms is complicated. Science of robotics suffers because it can be difficult to replicate the results of other researchers. Barriers to evaluating each other's work include incompatible hardware platforms, closed or proprietary software, and intellectual property concerns that lead to secrecy. Willow Garage claims to have an approach that overcomes these barriers (Oyama et al. 2009). ROS (Robot Operating System)  is  an open source  robotics framework  designed  to  take advantage of networked computing  infrastructures.  It  can  manage  many  different  process  written  in  different languages across many computers, which enables large, diverse robotics systems that fully take  advantage  of  the  available  computing  resources  (Oyama  et  al.  2009).  According  to Oyama  (2009)  ROS  has  dual  design  goals:  take  advantage  of  networked  computing infrastructures and encourage sharing of software. Hence in the future ROS may lead to a Robot App Store similar to the iPhone App Store (Orca 2010). As an example Libby & Kantor (2011) used ROS on a perception-based GPS-free approach for localizing a mobile robot  demonstrated  in  over  20km  of  online  operation  in  a  variety  of  real  orchard environments.    Jensen et al. (2011) proposed a flexible system architecture Field Robot Cognitive System Architecture  (FroboMind)  which  provides  the  base  for  further  research  and  development within  cognition  based  navigation  of  plant  nursing  robots.  This  work  present  the implementation  of  the  latter  conceptual  architecture  FroboMind  utilising  the  open-source cross language robotic framework ROS. Secondly a rugged hardware platform FroboBox is presented. FroboBox will have the most common interfaces often involved when working with sensors and actuators used on agricultural plant and animal nursing robots.   Vehicle mechanical platform The existing  agricultural  research  vehicle ASuBot  was  chosen for  the implementation of FroboMind. ASuBot is a modified AGCO Massey Ferguson garden tractor and is a joint project  between  the  University  of  Southern  Denmark  and  Aarhus  University.  This modifications includes a Topcon AES25 electrical steering system, which makes the ASubot able to steer by sending steering commands, Sick LMS111 Lidars, which is  the primary navigation sensors and a ADIS16345 inertial measurement unit from Analog devices which may be used as a pose information source.   Conference: http://www.njf.nu/site/seminarRedirect.asp?intSeminarID=441&p=1004     Figure 1: Left: Illustration of domain in which the FroboBox system is used the control the ASuBot equipped with a prototype natural gas burner from EnvoDan ApS (www.envodan.dk) for weeding with orchards. Right: The FroboBox prototype.  Hardware architecture The FroboBox has been developed to handle the low level processes listed in the conceptual architecture of FroboMind (Jensen  et  al.  2011). The Frobobox provides  a wide  range of  interfaces  which  is  often  used  when  communicating  between  sensors,  implements  and actuators. Hence, FroboBox will be suitable for other vehicle-platforms than the ASuBot as it may easily be adapted to different sensor/implement/actuator configurations.  Furthermore the FroboBox provides a wired/wireless network which may be connected to the Internet using a 3G uplink as well serve as a link to an Autonomous Task Computer which handles the high level processes also proposed in the conceptual architecture of FroboMind (Jensen et al. 2011) .  Software architecture  The FroboMind software architecture is implemented on the FroboBox hardware platform, running  a Debian Linux with the ROS framework on-top. By utilising the ROS method of structuring a project, each level of abstraction listed in the conceptual architecture of FroboMind is created as a ROS-package which is the main unit for organising software in ROS. Each package contains ROS processes (nodes) as well as source-code and other ROS specific files.   - fmSystemEnvironment - package  - fmSensorFeedback - package  - fmPredefinedKnowledge - package  - fmKnowledgeProcessingPlanning - package  - fmNavigationActuation - package  Besides  the  packages  defined  by  the  architecture,  listed  above,  two  packages  containing ROS-core functionalities and one package containing interface drivers (CANbus and serial communication) is implemented.    - fmCore - package  - fmMsgs - package  - fmInterfaces - package  Conference: http://www.njf.nu/site/seminarRedirect.asp?intSeminarID=441&p=1004 The above listed packages is collected in a ROS-stack called FroboMind. ROS-stacks are collections of packages that provide aggregate functionality, in this case the abstraction levels of the FroboMind architecture as well as low-level interface drivers.  Data exchange between the nodes in the FroboMind stack is accomplished by publishing messages  to  ROS-topics.  ROS-messages  is  data-structures,  much  like  C-structs,  standard primitive types such as integer, floating point and boolean are supported and may contain data corresponding to a given abstraction level.    Figure  2:  A  ROS-rxgraph  plot  of  nodes  from  an  early  version  of  the  implementation  of FromoMind. Black: fmInterfaces, Blue: fmSensorFeedback, Yellow: fmNavigationActuation.  As an example the imu_parser node (blue) shown in figure 2 is receiving raw data from the  COM1  serial  interface  node (black)  which  is  handeling the  interface driver. Raw data  is parsed and measured accelerations is convertet to m/s2 and angular velocities to rad/sec. The parsed and converted imu-data is published to a new topic, and made available to other nodes for further processing.   Conclusion The work provides a highly domain specific architecture in form of the field robotic vehicle conceptual architecture FroboMind (Jensen et al. 2011). This architecture is currently, as a work in progress, being implemented in ROS to evaluate how well FroboMind maps into ROS.  A prominent feature in both ROS and the conceptual architecture FroboMind is the well defined  interfaces/relations  between  components  (topics  and  nodes  in  ROS).  As  ROS encourages well defined dataflows through ROS-topics, one of the major tasks has indeed been to define these interfaces.  Since  ROS  imposes  no  architectural  constraints  ROS  has  shown  well  suited  for implementation of the proposed FroboMind architecture, which as a conceptual architecture provides  a  logical  functional-decomposition  and  serves  to  identify  and  modularize  key functionality and the relation between these modules.    Acknowledgement  This  research  is  linked  to  and  partially  funded  from  the  Danish  Ministry  for  Food, Agriculture and Fisheries project: FruitGrowth (Journal No. 3405-10-OP-00146). Further we we  would  like  to  acknowledge  The  Department  of  BioSystems  Engineering  Aarhus University;  Egon  Sørensen,  AGCO  Denmark  for  cooperation  with  regards  to  the  tractor; Torben Thorsen, Thorsen Teknik for skillful support implementing and adapting the Topcon Conference: http://www.njf.nu/site/seminarRedirect.asp?intSeminarID=441&p=1004 AES25  electrical  steering  system;  TopCon  Precision  Agriculture  Europe  for  the  Topcon AES25 electrical steering system and granting access to its CANbus protocol; and finally Sick Denmark for the four Sick LMS111 Lidars.   References Aslund S., Jensen K, Jørgensen R.N.. 2011. Complete coverage path planning of a random polygon - A FroboMind component. NJF seminar 441, Automation and System Technology in Plant Production CIGR section V & NJF section VII conference, 30 June - 2 July 2011 Denmark (Publication within this conference).   Christiansen M.P., Jensen K., Jørgensen R.N., Ellekilde L-P. 2011. Localization in orchards using Extended Kalman Filter for sensor-fusion - A FroboMind component. NJF seminar 441, Automation and System Technology in Plant Production CIGR section V & NJF section VII conference, 30 June - 2 July 2011 Denmark (Publication within this conference). Jensen K., Bøgild A., Nielsen S.H., Christiansen M.P., Jørgensen R.N. 2011. FroboMind, a conceptual architecture for agricultural field robot navigation. NJF seminar 441, Automation and System Technology in Plant Production CIGR section V & NJF section VII conference, 30 June - 2 July 2011 Denmark (Publication within this conference). Jørgensen, R.N., Sørensen, C.G.,  Pedersen, J.M., Havn, I., Jensen, K., Søgaard, H.T., Sørensen L.B.. 2007. Hortibot: A system design of a robotic tool carrier for high-tech plant nursing. CIGR Journal of AE Scientific Research and Development, Volume IX, 13 pp Libby J. and Kantor G.A. 2011. Deployment of a Point and Line Feature Localization System for an Outdoor Agriculture Vehicle. 2011 IEEE International Conference on Robotics & Automation (ICRA 2011), May, 2011. 6 p. Nebot, P., Torres-Sospedra, J., Martinez, R. J. 2011. A New HLA-Based Distributed Control Architecture for Agricultural Teams of Robots in Hybrid Applications with Real and Simulated Devices or Environments. Sensors 2011, 11, 4385-4400; doi:10.3390/s110404385 Oyama, A.; Konolige, K.; Cousins, S.; Chitta, S.; Conley, K. & Bradski, G. 2009 Come on in, our community is wide open for Robotics research! RSJ.  Orca. S. 2010. One Step Closer to the Robot App Store: ROS 1.0 and DIY Robotics. h+ Magazine, February 17, 2010. Internetlink: http://hplusmagazine.com/2010/02/17/one-step-closer-robot-app-store-ros-10-and-diy-robotics (seen May 6th 2011)     

Implementations of FroboMind using the Robot Operating System framework

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