A robot system has been developed to search for signs of life on Mars. The system consists of a rover equipped with an open-path spectrometer, and is to designed look for potential biogenic gas emissions from the ground. The paper discusses preliminary field studies with the system. The findings indicate that for this type of application, the spectrometer should be located as close to the ground as is feasible. Also, because wind quickly disperses concentrated gases, frequent measurements are needed in order to determine the location of the source.

Robots are being called upon to perform increasingly complex tasks in ever more complex environments. One popular strategy for designing robot control systems is to imitate creatures in the natural world. Since living organisms are usually adapted to the environment they exist in, the question becomes how can robots be designed to be adapted to their surroundings? To answer this, we must know how complex an environment is, or how well a robot can perform a given task in it. This paper examines a complexity measure that was previously proposed [36] for a robot searching task and shows the measure can predict the average number of steps a robot needs to complete a task to within 10%.

This paper examines various theories of innovation and sees how they apply to a system of systems framework. Systems of systems present an unusual challenge for innovation theory because some of the basic rules of the theory are broken by the system of systems paradigm. In particular, systems of systems are often deployed to solve complex problems that have a pressing need. However, pressing problems that require top system performance typically require an integrated solution - a solution where one entity controls all the components. By definition, a system of systems administrator does not control all the components and, indeed, may have control of none of them. This paper reviews various theories of innovation and applies them to an example that has previously been proposed for a system of systems.

This paper proposes a quantitative method to describe how complex an environment looks to an individual robot. The assumption is that robots are designed to perform a task in a specific setting or group of settings. The structure of the environment and knowledge the robot has about the environment determine how sophisticated the robot hardware and control algorithms need to be to perform a given task Information about the environment can be 1) obtained from a robot sensors; 2) downloaded or programmed into a robot; or 3) placed in the environment for a robot to read, as needed. Extensive simulations of a search task indicate that a combination of two factors can describe environmental complexity: a measure of entropy and the compressibility of the environment as seen by a robot's sensors. These combined measures can be used as a yardstick by engineers in determining how to design a robot-environment system. They allow the designer to determine how to divide his/her resources between robot hardware/software capabilities and information/structure in an environment. The complexity measure also allows the designer to determine quantitatively what information is most important for improving a robot's performance.

The field of robotics is on a growth curve, with most of the growth expected in the areas of personal and service robots. As robots become more prevalent in chaotic home and industrial settings, they will be required to make increasingly independent decisions about how to accomplish their tasks. A key to accomplishing this is the development of techniques to allow robots to handle severe uncertainty. This paper introduces the use of information gap theory as a way to enable robots to make robust decisions in the face of uncertainty, and illustrates this with an example problem.

The search for signs of past or present life on planetary surfaces such as Mars is a high priority objective of international space agencies. At present and in the near future, the most promising means to conduct such searches employ robotic systems that operate from planetary orbits or on planetary surfaces. This paper presents a robotic system concept for mobile search and surveying on planetary surfaces. It employs an open-path absorption spectrometer with components distributed on a rover and terrain to measure biogenic gases in the near-surface atmosphere. Rover motion control algorithms are presented and demonstrated in simulation for surveying wide areas autonomously using the distributed spectrometer for in situ remote sensing.

In recent years there has been growing evidence that Mars once had a warm, wet environment that was capable of supporting life. This leads to questions as to whether life ever arose on the planet. Space agencies are actively supporting projects to answer this question. As part of that effort, this paper proposes a robotic system to rapidly scan large areas of the Martian surface for specific biogenic gases in the atmosphere. The long-term goal of the project is to develop a system that can locate local emissions of water vapor and biogases on Mars. The paper presents preliminary proof of concept experiments for a practical robotic measurement system to search for biogenic gases on Mars. In this work, an open path spectrometer to measure the biogenic gas ammonia was developed and deployed on a rover. Initial tests in an outdoor setting indicate that the system is effective in measuring ammonia. Difficulties in taking measurements outdoors include compensating for wind gusts and changes in ambient lighting. The paper proposes improvements in the current system that will compensate for current limitations and allow measurements to be taken over longer distances.

This paper presents an agent-based robot control (ARC) architecture. ARC features a flexible real-time control system, which is suitable for multi-robot cooperative tasks. It also provides an efficient platform for building up a multi-robot system consisting of heterogeneous robots. In this paper, an experimental study of this architecture is investigated. A cooperative exploration using two mobile robots will be demonstrated. In this experiment, one robot explores the environment by looking for a color-coded target and the other is responsible for task execution at the target position. While exploring in an unknown environment, the first robot, which is equipped with ultrasonic sensors for exploration, records its position as it sees deployed checkpoints. In a later phase, the second robot plans a path to the target directly using information passed from the first robot and get to the target position in an efficient way.

This paper presents a systematic approach to designing a coupled oscillator controller, a control mechanism used successfully in nature. With this approach, a less conservative behavior-based robot controller with guaranteed performance can be automatically developed. This makes it possible to design a controller with good performance automatically, without the tuning of parameters. More importantly, it provides for a flexible and safe way of learning. Experimental and simulation results illustrate the validity of the method.