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Due to the lack of efficient control methods for a fleet of vehicles throughout a road network, the large-scale application of cybercars, which are fully automatic road vehicles providing on-demand and door-to-door transportation service, is still hindered. Although the fleet control problem for cybercars can be straightforwardly addressed in a centralized control setting, for reasons of scalability and fast computation, a centralized control method will not be tractable for the large-scale use of cybercars in the future. In this paper, we focus on the dynamic routing of a fleet of cybercars considering minimization of the combined system cost including the total time spent and the total energy consumption by all cybercars. We first propose a model of the dynamics and the energy consumption of a fleet of cybercars based on a description of the dynamics of every single cybercar and the states of the road network. After that, we propose several tractable and scalable multi-agent control methods including multi-agent model predictive control and parameterized control for the dynamic routing of cybercars. Finally, experiments by means of numerical simulations illustrate the performance of the proposed control methods. [ABSTRACT FROM PUBLISHER]

We present a gait generation framework for multilegged robots based on max-plus algebra that is endowed with intrinsically safe gait transitions. The time schedule of each foot liftoff and touchdown is modeled by sets of max-plus linear equations. The resulting discrete-event system is translated to continuous time via piecewise constant leg phase velocities; thus, it is compatible with traditional central pattern generator approaches. Different gaits and gait parameters are interleaved by utilizing different max-plus system matrices. We present various gait transition schemes and show that optimal transitions, in the sense of minimizing the stance time variation, allow for constant acceleration and deceleration on legged platforms. The framework presented in this paper relies on a compact representation of the gait space, provides guarantees regarding the transient and steady-state behavior, and results in simple implementations on legged robotic platforms. [ABSTRACT FROM PUBLISHER]