Coordinating Agile Systems through the Model-based Execution of Temporal Plans

SM thesisAgile autonomous systems are emerging, such as unmanned aerial vehicles (UAVs), that must robustly perform tightly coordinated time-critical missions; for example, military surveillance or search-and-rescue scenarios. In the space domain, execution of temporally flexible plans has provided an enabler for achieving the desired coordination and robustness, in the context of space probes and planetary rovers, modeled as discrete systems. We address the challenge of extending plan execution to systems with continuous dynamics, such as air vehicles and robot manipulators, and that are controlled indirectly through the setting of continuous state variables.Systems with continuous dynamics are more challenging than discrete systems, because they require continuous, low-level control, and cannot be controlled by issuing simple sequences of discrete commands. Hence, manually controlling these systems (or plants) at a low level can become very costly, in terms of the number of human operators necessary to operate the plant. For example, in the case of a fleet of UAVs performing a search-and-rescue scenario, the traditional approach to controlling the UAVs involves providing series of close waypoints for each aircraft, which incurs a high workload for the human operators, when the fleet consists of a large number of vehicles.Our solution is a novel, model-based executive, called Sulu, that takes as input a qualitative state plan, specifying the desired evolution of the state of the system. This approach elevates the interaction between the human operator and the plant, to a more abstract level where the operator is able to Âcoach the plant by qualitatively specifying the tasks, or activities, the plant must perform. These activities are described in a qualitative manner, because they specify regions in the plantÂs state space in which the plant must be at a certain point in time. Time constraints are also described qualitatively, in the form of flexible temporal constraints between activities in the state plan. The design of low-level control inputs in order to meet this abstract goal specification is then delegated to the autonomous controller, hence decreasing the workload per human operator. This approach also provides robustness to the executive, by giving it room to adapt to disturbances and unforeseen events, while satisfying the qualitative constraints on the plant state, specified in the qualitative state plan.Sulu reasons on a model of the plant in order to dynamically generate near-optimal control sequences to fulfill the qualitative state plan. To achieve optimality and safety, Sulu plans into the future, framing the problem as a disjunctive linear programming problem. To achieve robustness to disturbances and maintain tractability, planning is folded within a receding horizon, continuous planning and execution framework. The key to performance is a problem reduction method based on constraint pruning. We benchmark performance using multi-UAV firefighting scenarios on a real-time, hardware-in-the-loop testbed

Method to allocate inter-dependent resources by a set of participants

The object of the present invention is a method that allows a group of independent participants to coordinate decisions with respect to the allocation of interdependent resources, while maintaining certain privacy guarantees. The present invention proposes a method to allocate inter-dependent resources by a set of at least three participants, this method comprising the steps of : a. receiving by a first participant a request for a first resource by a third participant, and agreeing between the first participant and the third participant on at least one of a pair of allocation/non-allocation keys for the first resource, the allocation key being related to the allocation of the resource and the non-allocation key being related to the non-allocation of the resource, b. receiving by a second participant a request for a second resource by the third participant, and agreeing between the second participant and the third participant on at least one of a pair of allocation/non-allocation keys for the second resource, the allocation key being related to the allocation of the resource and the non-allocation key being related to the non-allocation of the resource, c. the third participant defining at least a first preference value defining his interest in a first combination of allocation or non-allocation of the first and second resources, d. the third participant obfuscating said first preference value using the two keys corresponding to the first combination of allocation and non-allocation of the first and second resources, e. transmitting the first obfuscated value directly or indirectly to the second participant, f. de-obfuscating by the second participant the received preference value using the corresponding allocation/non-allocation keys

Clinical, Etiologic, and Histopathologic Features of Stevens-Johnson Syndrome During an 8-Year Period at Mayo Clinic

OBJECTIVE: To examine clinical, etiologic, and histologic features of Stevens-Johnson syndrome and to identify possible correlates of clinical disease severity related to etiologic and histopathologic findings