A mission reliability estimation method has been designed to translate mission requirements into choices of robot modules in order to configure a multi-robot team to have high reliability at minimal cost. In order to build cost- effective robot teams for long-term missions, one must be able to compare alternative design paradigms in a principled way by comparing the reliability of different robot models and robot team configurations. Core modules have been created including: a probabilistic module with reliability-cost characteristics, a method for combining the characteristics of multiple modules to determine an overall reliability-cost characteristic, and a method for the generation of legitimate module combinations based on mission specifications and the selection of the best of the resulting combinations from a cost-reliability standpoint.
The developed methodology can be used to predict the probability of a mission being completed, given information about the components used to build the robots, as well as information about the mission tasks. In the research for this innovation, sample robot missions were examined and compared to the performance of robot teams with different numbers of robots and different numbers of spare components.
Data that a mission designer would need was factored in, such as whether it would be better to have a spare robot versus an equivalent number of spare parts, or if mission cost can be reduced while maintaining reliability using spares.
This analytical model was applied to an example robot mission, examining the cost-reliability tradeoffs among different team configurations. Particularly scrutinized were teams using either redundancy (spare robots) or repairability (spare components). Using conservative estimates of the cost-reliability relationship, results show that it is possible to significantly reduce the cost of a robotic mission by using cheaper, lower-reliability components and providing spares. This suggests that the current design paradigm of building a minimal number of highly robust robots may not be the best way to design robots for extended missions.
This work was done by Ashitey Trebi-Ollennu of Caltech and John Dolan and Stephen Stancliff of Carnegie Mellon University for NASA’s Jet Propulsion Laboratory. For more information, download the Technical Support Package (free white paper) at www.techbriefs.com/tsp under the Information Sciences category.
The software used in this innovation is available for commercial licensing. Please contact Karina Edmonds of the California Institute of Technology at (626) 395-2322. Refer to NPO-44825.
This Brief includes a Technical Support Package (TSP).
Mission Reliability Estimation for Repairable Robot Teams
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Overview
The document titled "Mission Reliability Estimation for Repairable Robot Teams" (NPO-44825) presents a novel analytical model developed by NASA's Jet Propulsion Laboratory aimed at optimizing the reliability and cost-effectiveness of multi-robot teams for long-term missions. The primary objective is to translate mission requirements into the selection of appropriate robot modules, thereby enhancing mission reliability while minimizing costs.
The methodology introduced in this document is the first principled quantitative approach for estimating mission reliability in mobile robot teams. It addresses the need for systematic evaluation of reliability and cost, which has been lacking in prior ad hoc methods. The core components of the developed model include:
- Probabilistic Module Reliability-Cost Characteristic: This module assesses the reliability and cost associated with individual robot components.
- Combination Methodology: A method for integrating the characteristics of multiple modules to derive an overall reliability-cost profile for the robot team.
- Legitimate Module Combinations Generation: This involves creating valid combinations of robot modules based on specific mission specifications.
- Selection Process: The model includes a mechanism for selecting the optimal combination of modules that balances cost and reliability.
The document emphasizes the importance of considering alternative design paradigms for robot teams, particularly in the context of extended missions. It explores critical questions that mission designers face, such as whether it is more beneficial to have spare robots or an equivalent number of spare parts, and how to reduce mission costs while maintaining reliability through the use of spare components.
Through practical application, the methodology was tested on a sample robot mission, analyzing various configurations of robot teams with differing numbers of robots and spare components. The findings suggest that significant cost reductions can be achieved by utilizing less expensive, lower-reliability components while providing spares, challenging the traditional design paradigm of creating a minimal number of highly robust robots.
In conclusion, this document outlines a comprehensive framework for mission reliability estimation that can significantly enhance the design and deployment of robotic teams in various applications, ultimately leading to more efficient and cost-effective robotic missions.
