Publications & Presentations

Safe and Efficient Robotic Space Exploration with Tele-Supervised Autonomous Robots [ AAAI Spring Symposium ] Abstract A successful plan for space exploration requires the commissioning of fleets of robots to prospect, mine, build, inspect and maintain structures, and generally assist astronauts, rendering the overall mission as safe as reasonably achievable for human beings, the most precious resource. The authors are currently developing, under the support of NASA, a Robot Supervision Architecture (RSA) which will allow a small number of human operators to safely and efficiently telesupervise a fleet of autonomous robots. This represents a significant advance over the state of the art, where currently one robot is overseen by a group of skilled professionals. In this paper we describe some aspects of this work, including the architecture itself for coordination of human and robot work, failure and contingency management, high-fidelity telepresence, and operation under limited bandwidth. We also present highlights of our first application: wide area prospecting of minerals and water in support of sustained outposts on the Moon and on Mars.

A Robot Supervision Architecture for Safe and Efficient Space Exploration and Operation [ Earth & Space 2006 Conference ] [ PowerPoint presentation, PDF version ]

A Robot Supervision Architecture for Safe and Efficient Space Exploration and Operation [ Earth & Space 2006 Conference ] [ Proceedings paper ] Abstract Current NASA plans envision human beings returning to the Moon in 2018 and, once there, establishing a permanent outpost from which we may initiate a long-term effort to visit other planetary bodies in the Solar System. This will be a bold, risky, and costly journey, comparable to the Great Navigations of the fifteenth and sixteenth centuries. Therefore, it is important that all possible actions be taken to maximize the astronauts' safety and productivity. This can be achieved by deploying fleets of autonomous robots for mineral prospecting and mining, habitat construction, fuel production, inspection and maintenance, etc.; and by providing the humans with the capability to telesupervise the robots' operation and to teleoperate them whenever necessary or appropriate, all from a safe, "shirtsleeve" environment. This paper describes the authors' work in progress on the development of a Robot Supervision Architecture (RSA) for safe and efficient space exploration and operation. By combining the humans' advanced reasoning capabilities with the robots' suitability for harsh space environments, we will demonstrate significant productivity gains while reducing the amount of weight that must be lifted from Earth - and, therefore, cost.

Human Telesupervision of a Fleet of Autonomous Robots for Safe and Efficient Space Exploration [ 1st Annual Conference on Human-Robot Interaction ] Abstract In January 2004, NASA began a bold enterprise to return to the Moon, and with the technologies and expertise gained, press on to Mars. The underlying Vision for Space Exploration calls for a sustained and affordable human and robotic program to explore the solar system and beyond; to conduct human expeditions to Mars after successfully demonstrating sustained human exploration missions on the Moon. The approach is to "send human and robotic explorers as partners, leveraging the capabilities of each where most useful." Human-robot interfacing technologies for this approach are required at readiness levels above any available today. In this paper, we describe the HRI aspects of a robot supervision architecture we are developing under NASA's auspices, based on the authors' extensive experience with field deployment of ground, underwater, lighter-than-air, and inspection autonomous and semi-autonomous robotic vehicles and systems.

Robotics Institute Technical Reports

Adaptive Sampling for Multi-Robot Wide Area Prospecting [ CMU-RI-TR-05-51 ] Abstract Prospecting for in situ mineral resources is essential for establishing settlements on the Moon and Mars. To reduce human effort and risk, it is desirable to build robotic systems to perform this prospecting. An important issue in designing such systems is the sampling strategy: how do the robots choose where to prospect next? This paper argues that a strategy called Adaptive Cluster Sampling (ACS) has a number of desirable properties: compared to conventional strategies, (1) it reduces the total mission time and energy consumption of a team of robots, and (2) returns a higher mineral yield and more information about the prospected region by directing exploration towards areas of high mineral density, thus providing detailed maps of the boundaries of such areas. Due to the adaptive nature of the sampling scheme, it is not immediately obvious how the resulting sampled data can be used to provide an unbiased, low-variance estimate of the regional mineral density. This paper therefore investigates new mineral density estimators, which have lower error than previously-developed estimators; they are derived from the older estimators via a process called Rao-Blackwellization. Since the efficiency of estimators depends on the type of mineralogical population sampled, the population characteristics that favor ACS estimators are also analyzed. The ACS scheme and our new estimators are evaluated empirically in a detailed simulation of the prospecting task, and the quantitative results show that our approach can yield more minerals with less resources and provide more accurate mineral density estimates than previous methods.