From virtual world to reality: designing an autonomous underwater robot

AAAI Conferences

Design of autonomous underwater robots is particularly difficult due to the physical and sensor challenges of the underwater environment. Inaccessibility during operation and low probability of failure recovery makes robot stability and reliability paramount. Building an accurate and complete virtual world simulation is proposed as a necessary prerequisite for design of an autonomous underwater robot. A virtual world can include actual robot components and models for all other aspects of the world. Robot design can be fully tested using a virtual world and then verified using the real world. Additional testing can be performed in the virtual world that is not feasible in the real world. Visualization of robot interactions within a virtual world permits sophisticated analysis of robot performance that is otherwise unavailable. All aspects of world modeling and robot design must be mastered and coordinated in order to build an authentic virtual world and capable autonomous robot.


Experiences Looking into Niches

AAAI Conferences

I've worked on over a dozen different robot systems whose software control architecture ranged from nonexistent [4] to ponderous [2]. For the past many years, I along with several others, have been developing a layered architecture that joins reactive control with more traditional symbolic reasoning [6]. I believe that this architecture is the right way to go to create physical agents that can carry out a large variety of complex tasks in realistic environments. However, despite numerous publications with titles like An Implemented Architecture..., many of them coauthored by myself, the actual experience with robots using these layered architectures where the full system has been implemented on a physical robot has been extremely limited. Therefore the conclusions that can be gained for these experiences are, at this time, limited. Several of the other attendees are talking about these systems, and will cover them in detail.


Robot Planning in the Real World: Research Challenges and Opportunities

AI Magazine

Recent years have seen significant technical progress on robot planning, enabling robots to compute actions and motions to accomplish challenging tasks involving driving, flying, walking, or manipulating objects. However, robots that have been commercially deployed in the real world typically have no or minimal planning capability. These robots are often manually programmed, teleoperated, or programmed to follow simple rules. Although these robots are highly successful in their respective niches, a lack of planning capabilities limits the range of tasks for which currently deployed robots can be used. In this article, we highlight key conclusions from a workshop sponsored by the National Science Foundation in October 2013 that summarize opportunities and key challenges in robot planning and include challenge problems identified in the workshop that can help guide future research toward making robot planning more deployable in the real world.


Robot Planning in the Real World: Research Challenges and Opportunities

AI Magazine

Recent years have seen significant technical progress on robot planning, enabling robots to compute actions and motions to accomplish challenging tasks involving driving, flying, walking, or manipulating objects. However, robots that have been commercially deployed in the real world typically have no or minimal planning capability. These robots are often manually programmed, teleoperated, or programmed to follow simple rules. Although these robots are highly successful in their respective niches, a lack of planning capabilities limits the range of tasks for which currently deployed robots can be used. In this article, we highlight key conclusions from a workshop sponsored by the National Science Foundation in October 2013 that summarize opportunities and key challenges in robot planning and include challenge problems identified in the workshop that can help guide future research towards making robot planning more deployable in the real world.


MICE and the Science of Vacuuming

AAAI Conferences

Artificial intelligence and robotics are fields notorious for developing many different systems that are never compared with each other in a quantitative way. This paper suggests that the task of vacuum-cleaning could be used as a benchmark for comparing different robot systems. Such a comparison should take place within a simulation environment, which is outlined in the paper. This paper also suggests a possible standard robot and some benchmark environments, as well as a set of quantitative evaluation metrics that could be used to compare robot systems. Introduction In general, research in robotics and artificial intelligence has been notoriously bereft of the type of rigorous scientific analysis and testing that lead to well-understood advances in a field.