Mission Reliability Estimation for Repairable Robot Teams (original) (raw)
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Planning to fail: Mission design for modular repairable robot teams
This paper presents a method using stochastic simulation to evaluate the reliability of robot teams consisting of modular robots. For an example planetary exploration mission we use this method to compare the performance of a repairable robot team with spare modules versus nonrepairable robot teams. Our results show that for this mission a repairable robot team can provide a higher probability of mission completion than a nonrepairable team, even when the nonrepairable robots are built using components with an order of magnitude greater reliability than the repairable robots.
A mission taxonomy-based approach to planetary rover cost-reliability tradeoffs
Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems - PerMIS '09, 2009
Our earlier work on robot mission reliability provides tradeoff analysis between input parameters such as mission success rate, robot team size, and robot component reliability, but only for specific tasks. Here we take a more comprehensive approach in order to draw more general conclusions about robot mission reliability. The approach is based on a mission taxonomy coupled with detailed reliability analysis of each of the resultant mission classes. This paper describes initial work towards that goal. In this paper we present the above-mentioned taxonomy, which divides planetary robotic missions into subgroups with common characteristics with respect to the time proportion of tasks involved in the missions. For a given mission class, we show how a mission designer can obtain the optimum robot configuration in terms of robot team size and component reliability that maximize mission success rate under a budget constraint.
An analysis of cooperative repair capabilities in a team of robots
Proceedings 2002 Ieee International Conference on Robotics and Automation, 2002
the benefits of repairable robots. Robots that can repair themselves and other robots in their team are intuitively a superior design. Intuition, however, is not an acceptable basis for spending millions of dollars in development. In this work, we quantify the gain in productivity of a team of repairable robots compared to a team without repair capabilities. We create a model using an extension of standard reliability theory. It allows the definition of a metric which is used t o compare the two teams. The analysis yields insight into the design of repairable robot teams under a certain set of assumptions. The model also demonstrates scenarios where repair capabilities are not likely to be beneficial.
Lecture Notes in Computer Science, 2013
This paper presents a quantifiable method by which the behaviors of robots, as determined by their performance in a cyber-physical context, can be captured and generalized so that accurate predictions of sequentially coordinated multirobot behaviors can be made. The analysis technique abstracts sequentially coordinated multirobot missions as a frequentist inference problem. Rather than attempt to identify and put into a causal relation all the hidden and unknown cyber-physical influences that can have an impact on mission performance, we model the problem as that of predicting multirobot performance as a conditional probability. This allows us to initially limit the testing and evaluation of robot performance to evaluations of atomistic behaviors, and to experiment mathematically with the combinations of predictive features and elementary performance metrics to derive accurate predictions of higherlevel coordinated performance. Statistical tests on the goodness of the results are reported, as well.
AIAA SPACE 2016, 2016
Space Administration (NASA) continues to evaluate potential approaches for sending humans beyond low Earth orbit (LEO). A key aspect of these missions is the strategy that is employed to maintain and repair the spacecraft systems, ensuring that they continue to function and support the crew. Long duration missions beyond LEO present unique and severe maintainability challenges due to a variety of factors, including: limited to no opportunities for resupply, the distance from Earth, mass and volume constraints of spacecraft, high sensitivity of transportation element designs to variation in mass, the lack of abort opportunities to Earth, limited hardware heritage information, and the operation of human-rated systems in a radiation environment with little to no experience. The current approach to maintainability, as implemented on ISS, which includes a large number of spares pre-positioned on ISS, a larger supply sitting on Earth waiting to be flown to ISS, and an on demand delivery of logistics from Earth, is not feasible for future deep space human missions. For missions beyond LEO, significant modifications to the maintainability approach will be required.
Towards a Predictive Model of Mobile Robot Reliability
2000
Mobile robots are notoriously unreliable. In order to make,significant improvements,in mobile robot reliability, we need quantitative methods and precise language for measuring,and ,discussing ,reliability. Such ,methods ,exist within ,the reliability engineering literature but have seen little use in the design of mobile ,robots. In this report we present ,an overview ,of reliability engineering methods ,which can be used ,to
Planning to fail — Reliability needs to be considered a priori in multirobot task allocation
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
The reliability of individual team members has a substantial and complex influence on the success of multirobot missions. When one robot fails, other robots must be retasked to complete the tasks that were assigned to the failed robot. This in turn increases the likelihood of these other robots failing, since they have more work to do. Existing multirobot task allocation systems consider robot failures only after the fact-by replanning after a failure occurs. We hypothesize that it should be important to consider robot reliabilities when generating an initial plan. In this paper we test this hypothesis in the context of the multirobot exploration problem. We take a simple exhaustive planner and compare the plan it chooses against the optimal plan that takes into account robot failures and the backup plans that occur after failure. Our results show that for this problem domain, making an initial plan without regards to individual robot reliabilities results in choosing a suboptimal plan most of the time, and that the difference in mission performance between the chosen plan and the optimal plan is usually substantial. In brief, in order to successfully plan we must 'plan to fail'.
Planning to fail: using reliability to improve multirobot task allocation
Unattended Ground, Sea, and Air Sensor Technologies and Applications XII, 2010
The reliability of individual robots influences the success of multirobot missions. When one robot fails, others must be retasked to complete the failed robot's tasks. This increases the failure likelihood for these other robots. Existing multirobot task allocation systems consider robot failures only after the fact, via replanning. In this paper we show that mission performance for multirobot missions can be improved by using knowledge of robot failure rates to inform the initial task allocation.
Manned missions to Mars: Minimizing risks of failure
Acta Astronautica, 2014
Some major risks-of-failure issues for the future manned missions to Mars are discussed, with an objective to address criteria for making such missions possible, successful, safe and cost-effective. The following astronautical and instrumentation-and-equipmentreliability related aspects of the missions are considered: redundancies and backup strategies; costs; assessed probability of failure as a suitable reliability criterion for the instrumentation (equipment); probabilistic assessment of the likelihood of the mission success and safety. It is concluded that parametric risk modeling is a must for a risk-driven decision-making process.