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Jan
04
2011
Methodologies for the Design of Robotic and Multi-Agent SystemsObject oriented analysis and design (OOAD) methodologies are well established, offering a plethora of methodologies depending on the needs of the project and the skills of the development team; e.g., eXtreme Programming, Domain Driven Design, Agile Modeling, and Crystal Clear. (Scrum is omitted as it lacks adequate direction for OOAD; albeit, it’s a terrific project management methodology.) Indeed, a pivotal element of any successful software development endeavor is the careful selection of a methodology for defining project requirements and designing the solution. A challenge with applying traditional OOAD methodology to robot and multi-agent control systems is the traditional methodologies’ bias towards defining the structure and properties of objects and applying behaviors to those objects as a secondary concern. But in the world of robotics, the emphasis needs to be squarely placed on behavior as the centerpiece of design. This does not imply that the methodology will result in a behavior-based, subsumption architecture, but instead that the robot’s goal-driven and event-driven behavior is at the very core of what is being modeled. Accordingly, a number of agent-oriented analysis and design (AOAD) methodologies have emerged over the years in response to this disconnect between traditional OOAD methodologies and the needs of agent-oriented systems. What follows is a brief listing of a few notable AOAD methodologies representing a wide cross-section of approaches:
If you’d like to learn more about other agent-oriented methodologies, an almost comprehensive survey of options, with a good introduction to each, has been put together by the University of British Columbia in Analysis and Design of Agent-Oriented Information Systems (AOIS); or, if you’re willing to shell out some cash, see Federico Bergenti’s Methodologies and Software Engineering for Agent Systems. In the next post, we’ll examine some of the architectural constraints of our project and determine which AOAD methodology will be right. Enjoy! This post is one in a series for the commercial development of a multi-agent, robotic, bell pepper picking team with scalable planning, supporting unstructured, outdoor horticulture. If you’d like to follow along, be sure to subscribe to SharpRobotica.com. In addition to commenting on posts, feel free to contact me anytime if you would like to discuss collaboration or funding prospects. |
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