Marco Pavone

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This paper presents a decentralized control policy for symmetric formations in multi-agent systems. It is shown that n agents, each one pursuing its leading neighbor along the line of sight rotated by a common offset angle α, eventually converge to a single point, a circle or a logarithmic spiral pattern, depending on the value of α. In the final part of(More)
In this paper we present a novel probabilistic sampling-based motion planning algorithm called the Fast Marching Tree algorithm (FMT*). The algorithm is specifically aimed at solving complex motion planning problems in high-dimensional configuration spaces. This algorithm is proven to be asymptotically optimal and is shown to converge to an optimal solution(More)
A widely applied strategy for workload sharing is to equalize the workload assigned to each resource. In mobile multi-agent systems, this principle directly leads to equitable partitioning policies whereby (i) the environment is equitably divided into subregions of equal measure, (ii) one agent is assigned to each subregion, and (iii) each agent is(More)
Recent years have witnessed great advancements in the science and technology of autonomy, robotics and networking. This paper surveys recent concepts and algorithms for dynamic vehicle routing (DVR), that is, for the automatic planning of optimal multi-vehicle routes to perform tasks that are generated over time by an exogenous process. We consider a rich(More)
In this paper we present distributed and adaptive algorithms for motion coordination of a group of m autonomous vehicles. The vehicles operate in a convex environment with bounded velocity and must service demands whose time of arrival, location and on-site service are stochastic; the objective is to minimize the expected system time (wait plus service) of(More)
In this paper, we study the problem of designing motion strategies for a team of mobile agents, required to fulfill request for on-site service in a given planar region. In our model, each service request is generated by a spatio-temporal stochastic process; once a service request has been generated, it remains active for a certain deterministic amount of(More)
In this paper we present queueing-theoretical methods for the modeling, analysis, and control of autonomous mobilityon-demand (MOD) systems wherein robotic, self-driving vehicles transport customers within an urban environment and rebalance themselves to ensure acceptable quality of service throughout the network. We first cast an autonomous MOD system(More)
The most widely applied resource allocation strategy is to balance, or equalize, the total workload assigned to each resource. In mobile multi-agent systems, this principle directly leads to equitable partitioning policies in which (i) the workspace is divided into subregions of equal measure, (ii) there is a bijective correspondence between agents and(More)
In this paper we develop methods for maximizing the throughput of a mobility-on-demand urban transportation system. We consider a finite group of shared vehicles, located at a set of stations. Users arrive at the stations, pick-up vehicles, and drive (or are driven) to their destination station where they drop-off the vehicle. When some origins and(More)