This paper describes the use of task primitives in robot learning from observation. A framework has been developed that uses observed data to initially learn a task and then the agent goes on to increase its performance through repeated task performance (learning from practice). Data that is collected while a human performs a task is parsed into small parts of the task called primitives. Modules are created for each primitive that encode the movements required during the performance of the primitive, and when and where the primitives are performed. The feasibility of this method is currently being tested with agents that learn to play a virtual and an actual air hockey game. 1

We present a terrain mapping system for walking robots that constructs quantitative models of surface geometry.

This thesis presents methods for implementing robust hexapod locomotion and fault tolerance capabilities on an autonomous robot with many sensors and actuators. The controller is based on the Subsumption Architecture and is fully distributed over approximately 1500 simple, concurrent processes. The robot, Hannibal, weighs approximately 6 pounds and is equipped with over 100 physical sensors, 19 degres of freedom, and $ on board computers.

markj @ oregon.uoregon.edu and rohrer @ cogsci.ucsd.edu © 2003-2007 by the authors, pre-press final draft 4/7/07 citation information:

Abstract ⎯ One reason given for the use of multirobot systems is that many cheap robots are more reliable than one expensive robot. To date, however, there has been no quantitative analysis to support this assertion. This paper presents the first quantitative support for the argument that larger teams of less-reliable robots can perform certain missions more reliably than smaller teams of more-reliable robots. Our results show that for short missions, in fact, a team of four robots can provide greater mission reliability than a team of two robots, even when the individual robots in the team of four have reliability that is an order of magnitude lower. These results suggest that considerable cost reductions can be achieved for some missions by choosing larger teams of less-reliable robots over smaller teams of more-reliable robots. Index Terms ⎯ Mobile robots, multirobot systems, mission design, reliability. I.

Abstract — In swarm robotic systems emergent swarm properties are particularly difficult to analyse and model. This paper describes a simple but effective algorithm for emergent swarm taxis (swarm motion toward a beacon) in a 2D or 3D wireless connected swarm of minimalist mobile robots. The paper then undertakes a deep analysis of the swarm taxis by identifying both first and second order micro-level robot interactions and quantifying the contribution of each such interaction to the macro-level swarm behaviour. From the analysis we develop a simple quantitative model that is able to predict swarm velocity with reasonable accuracy. Although the analysis is specific to the swarm algorithm in question, we believe that the methodology presented has generic value to swarm modellers. I. BACKGROUND. The fields of robotics and artificial intelligence have seen

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The problem of landmine detection has been studied for decades. Mine detection systems have typically been developed by first identifying a sensor technology, then testing on particular manmade testbeds, then deploying the sensor on a vehicle or man-portable device. Despite much effort, current systems still exhibit gaps between existing and desired capability, e.g., in terms of rate of advance, detection rate, and false alarm rate within demonstration testbeds. In this paper, we propose a new system-level approach to landmine detection. We argue that "the landmine detection problem" cannot be attacked in a piecewise fashion: system-level solutions must simultaneously consider functional requirements, sensor technologies, models of sensors, the method of sensor application, and the platforms from which sensors are applied. This perspective allows us to shift our focus from the previous emphasis on novel sensor technology, and to go somewhat beyond traditional doctrines governing stand...

The launch of the Deep Space One (DS1) probe heralded the beginning of a new phase for NASA, which will be embarking on a series of missions to test and deploy low cost, demonstration technologies. In an attempt to cut mission costs from billions to under 100 million, NASA is looking towards autonomous spacecraft and robots to establish a virtual presence in space. This paper describes mobile agents and discusses their uses in tackling the problems of adjustable autonomy and long distance interaction. The concepts of autonomy and emergence are then briefly discussed, before combining them with a mobile agent based framework within which the properties of adjustable autonomy and interaction at a distance are inherent. Finally, mobile agents are examined within several plausible contexts to demonstrate their applicability. Introduction and Motivation It is the stated intention of NASA to establish a virtual presence in space through the use of a plethora of robotic probe...

Complex adaptive systems research adds to the theory of how to design systems that are resilient to change in turbulent environments. This paper reports a case story about using complex adaptive systems theory for designing a quality management system in a politically turbulent organization. The story explains how the quality management system evolved rapidly, exploiting the turbulence of the organization, but collapsed after six years. Through an analysis and discussion of what went wrong, three key issues are identified and explained; (1) topology of quality management systems, (2) controlling the controllers, and (3) projects perspective vs. systems perspective. Implications for a revised design strategy are discussed.