Planning to Fail - Reliability as a Design Parameter for Planetary Rover Missions

operating on Mars for more than three years. The extremely high reliability demonstrated by these rovers is a great success story in robotic design. This reliability comes at a high cost, however, both in the initial cost of developing the rovers and in the ongoing operational costs for their mission extensions. If it were possible to design rovers with reliability more in line with their mission requirements (in the case of MER, 90 days), considerable cost reductions could be achieved. This will be even more important for future planetary robotic missions due to greatly increased mission durations. In this paper we present an overview of our ongoing research in the area of predicting robot mission reliability, and we show how a mission designer can trade off reliability against costs in order to find an optimal reliability target for a given robotic mission. Our results show that for a given mission there is an optimal reliability range with respect to cost and that having rovers with reliability that is too low or too high is suboptimal from an economic standpoint. This suggests that a better cost-reliability tradeoff can be obtained by "planning to fail " by designing rovers which have lower reliability than current legacy designs

Mission reliability estimation for multi-robot team design

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

Planning to Fail - Reliability as a Design Parameter for Planetary Rover Missions

The Mars Exploration Rovers (MER) have been operating on Mars for more than three years. The extremely high reliability demonstrated by these rovers is a great success story in robotic design. This reliability comes at a high cost, however, both in the initial cost of developing the rovers and in the ongoing operational costs for their mission extensions. If it were possible to design rovers with reliability more in line with their mission requirements (in the case of MER, 90 days), considerable cost reductions could be achieved. This will be even more important for future planetary robotic missions due to greatly increased mission durations. In this paper we present an overview of our ongoing research in the area of predicting robot mission reliability, and we show how a mission designer can trade off reliability against costs in order to find an optimal reliability target for a given robotic mission. Our results show that for a given mission there is an optimal reliability range with respect to cost and that having rovers with reliability that is too low or too high is suboptimal from an economic standpoint. This suggests that a better cost-reliability tradeoff can be obtained by "planning to fail" by designing rovers which have lower reliability than current legacy designs

Mission Reliability Estimation for Multirobot Team Design

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

called the Telesupervised Adaptive Ocean Sensor Fleet that uses a

Abstract – We are developing a Sensor Web-relevant syste