Abstract
The aim of this paper is to describe a novel representation framework for high level robot and multi-robot programming, called Petri Net Plans (PNP), that allows for representing all the action features that are needed for describing complex plans in dynamic environments. We provide a sound and complete execution algorithm for PNPs based on the semantics of Petri nets. Moreover, we show that multi-robot PNPs allow for a sound and complete distributed execution algorithm, given that a reliable communication channel is provided. PNPs have been used for describing effective plans for actual robotic agents which inhabit dynamic, partially observable and unpredictable environments, and experimented in different application scenarios. Copyright

Abstract
This paper introduces Petri net (PN) based models of cooperative robotic tasks, namely those involving the coordination of two or more robots, thus requiring the exchange of synchronisation messages, either using explicit (e.g., wireless) or implicit (e.g., vision-based observation of teammates) communication. In the models, PN places represent primitive actions, subtasks and predicates set by sensor readings and communicated messages. Events are associated to PN transitions. The PN models can be used for task planning, plan execution and plan analysis. Different PN views enable the analysis of different properties. In this work we focus on plan analysis, namely on properties such as boundedness and liveness, corresponding to checking if resources usage is stable and plans have no deadlocks, as well as on stochastic performance, concerning the plan success probability. One novel feature of our work is that the analysis consists of composing several small action PN models with environment PN models, leading to a closed loop robot team/environment analysis methodology. Examples of application to simulated robotic soccer scenarios are presented. Copyright

Abstract

Abstract

Abstract
This paper proposes a new algorithm which promotes well distributed non-dominated fronts in the parameters space when a single-objective function is optimized. This algorithm is based on e-dominance concept and maxmin sorting scheme. Besides that, the paper also presents the results of the algorithm when it is used in the automated synthesis of optimum performance CMOS radio-frequency and microwave binary-weighted differential switched capacitor arrays (RFDSCAs). The genetic synthesis tool optimizes a fitness function which is based on the performance parameter of the RFDSCAs. To validate the proposed design methodology, a CMOS RFDSCA is synthesized, using a 0.25 µm BiCMOS technology.

Abstract
The automotive suspension plays a crucial role in vehicle safety and driving comfort. One of the most important components in vehicle suspensions is the damper (or shock absorber). Because there is no precise method to perform shock absorber test within the vehicle, an embedded autonomous system, powered by the energy harvested from the shock absorber itself, capable of monitoring shock absorber parameters and transmitting these values throughout a wireless interface to the vehicle central diagnostic unit, is presented. Such a device will permit the shock absorber condition assessment under vehicle operation, which to our best knowledge is considered a breakthrough in vehicle safety. © 2008 IEEE.