Autonomous Outdoor Navigation

  • Robotic tasks for real-world applications typically involve temporal sequences and representations of data not available directly from sensors, which suggests that representations and deliberative components are essential for a robot’s control architecture. The majority of real-world robot tasks require not only the reliable real-time characteristics of reactive behavior, but also guided transitions from state-to-state, and the ability to make decisions based on abstract data acquired a-priori, from sources such as maps. This poses significant challenges for the development of controllers for robots that interact directly with the physical environment. A principal challenge is in dealing with the uncertainty introduced by noisy sensors. Pure deliberation falters in that even seemingly simple environments cannot be entirely represented by models accurately or quickly enough to guide a robot reliably in real-time. Reactive architectures are able to deal with uncertainties, but are limited to relatively simple tasks.
  • The goal of this project is to develop an architecture that addresses the above challenges and demonstrates a flexible method for building robot controllers, while allowing for both reactive and deliberative components. Our solution is to consider a controller as a composition of agents, with similar representations and inter-agent communication mechanisms, similar to behaviors in the behavior-based design paradigm. The agents can be composed of other agents in a nested fashion and use the implementation (reactive or deliberative) that is most appropriate for their task. Thus, the contribution of our work is a control architecture that has the following main features: 1) it enables modular, flexible, incremental design of controllers to execute complex, sequential tasks, which can be easily extended or improved and 2) it integrates reaction and deliberation within the same representational framework, using deliberation only as necessary. This approach is used to develop a controller on a custom robot, and was validated in an outdoor navigation and retrieval task.
  • This work was supported by the National Science Foundation EPSCoR Ring True III Award EPS0447416 and by NASA under Awards NSHE-07-34, NSHE-07-35, and NSHE-07-56.