Francesco Bullo
University of California, Santa Barbara
520 Papers
6K Citations
Francesco Bullo is an academic researcher from University of California, Santa Barbara. The author has contributed to research in topics: Computer science & Distributed algorithm. The author has an hindex of 81, co-authored 484 publications. Previous affiliations of Francesco Bullo include California Institute of Technology & University of California.
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Papers
On Discrete-Time Pursuit-Evasion Games With Sensing Limitations
TL;DR: This paper proposes a sweep-pursuit-capture pursuer strategy to capture the evader and applies it to two variants of the game, one involving a single pursuer and an evader in a bounded convex environment and the other in a boundaryless environment.
Quantized average consensus via dynamic coding/decoding schemes
Ruggero Carli,Francesco Bullo,Sandro Zampieri +2 more
- 01 Dec 2008
TL;DR: A consensus strategy in which the systems can exchange information among themselves according to a fixed connected digital communication network and two different encoding/decoding strategies are presented with theoretical and simulation results on their performance.
Distributed Algorithms for Environment Partitioning in Mobile Robotic Networks
TL;DR: This paper designs provably correct and spatially distributed algorithms that allow a team of agents to compute a convex and equitable partition of a conveX environment and illustrates a systematic approach to devise spatially distributing control policies for a large variety of multiagent coordination problems.
Discrete Partitioning and Coverage Control for Gossiping Robots
TL;DR: It is proved that territory ownership converges to a pairwise-optimal partition in finite time and represents improved performance over common Lloyd-type algorithms.
On frame and orientation localization for relative sensing networks
G. Piova,Iman Shames,Baris Fidan,Francesco Bullo,Brian D. O. Anderson +4 more
- 09 Dec 2008
TL;DR: A novel localization theory for planar networks of nodes that measure each other?s relative position is developed, i.e., they assume that nodes do not have the ability to perform measurements expressed in a common reference frame.