Planning to fail: Mission design for modular repairable robot teams (original) (raw)
Related papers
Mission Reliability Estimation for Repairable Robot Teams
International Journal of Advanced Robotic Systems, 2006
NASA has expressed interest in using modular self-repairable robotic teams for the exploration and colonization of Mars. One of the reasons often given for using repairable robots is increased reliability. Analytical tools are needed for estimating the reliability of robotic missions in order to determine if this reasoning is correct, and for what types of missions. In this paper we present the first method for analytically predicting the probability of mission completion for teams of repairable mobile robots. We then apply this method to compare the reliability of repairable and nonrepairable robot teams for an example mission scenario. Our results show that for this simple mission, with reasonable assumptions regarding costs, teams of repairable robots with spare components are superior to teams with spare nonrepairable 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.
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.
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.
Towards a team of robots with reconfiguration and repair capabilities
Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2000
In the future, we propose that there will be largely self-sufficient robot colonies operating on distant planets and in harsh environments here on earth. A highly desirable quality of such a colony would he the capability of the robots to repair each other. Towards the goal of autonomous repair, we have designed a robot that can replace the modules composing a similar robot. The final system was teleoperated and module removal and replacement was performed on a test bed. We discuss some of the design trade-offs for such a system and discuss some of the steps required in order to develop a selfsufficient robot colony.
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.
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.
Resilience by Reconfiguration: Exploiting Heterogeneity in Robot Teams
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019
We propose a method to maintain high resource availability in a networked heterogeneous multi-robot system subject to resource failures. In our model, resources such as sensing and computation are available on robots. The robots are engaged in a joint task using these pooled resources. When a resource on a particular robot becomes unavailable (e.g., a sensor ceases to function), the system automatically reconfigures so that the robot continues to have access to this resource by communicating with other robots. Specifically, we consider the problem of selecting edges to be modified in the system's communication graph after a resource failure has occurred. We define a metric that allows us to characterize the quality of the resource distribution in the network represented by the communication graph. Upon a resource becoming unavailable due to failure, we reconfigure the network so that the resource distribution is brought as close to the maximal resource distribution as possible without a large change in the number of active inter-robot communication links. Our approach uses mixed integer semi-definite programming to achieve this goal. We employ a simulated annealing method to compute a spatial formation that satisfies the inter-robot distances imposed by the topology, along with other constraints. Our method can compute a communication topology, spatial formation, and formation change motion planning in a few seconds. We validate our method in simulation and real-robot experiments with a team of seven quadrotors.