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**1 - 5**of**5**### Motion Coordination for . . . WITH VISIBILITY SENSORS

, 2007

"... The subject of this dissertation is motion coordination for mobile robotic networks with visibility sensors. Such networks consist of robotic agents equipped with sensors that can measure distances to the environment boundary and to other agents within line of sight. We look at two fundamental coord ..."

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The subject of this dissertation is motion coordination for mobile robotic networks with visibility sensors. Such networks consist of robotic agents equipped with sensors that can measure distances to the environment boundary and to other agents within line of sight. We look at two fundamental coordination problems: (i) deploying over an unknown nonconvex environment to achieve complete visibility, and (ii) gathering all agents initially scattered over the environment at a single location. As a special case of problem (i), we first address the problem of optimally locating a single robotic agent in a nonconvex environment. The agent is modeled as a point mass with continuous first-order dynamics. We propose a nonsmooth gradient algorithm for the problem of maximizing the area of the region visible to the observer in a non-self-intersecting nonconvex polygon. First, we show that the visible area is almost everywhere a locally Lipschitz function of the observer location. Second, we provide a novel version of the LaSalle Invariance Principle for discontinuous vector fields and for Lyapunov functions with a finite number of discontinuities. Finally, we establish the asymptotic convergence properties of the nonsmooth gradient algorithm and we illustrate numerically its performance. Second, we address problem (i) by proposing a novel algorithm to the deploy a group of robotic

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"... Multirobot rendezvous with visibility sensors in nonconvex environments Abstract—This paper presents a coordination algorithm for mobile autonomous robots. Relying upon distributed sensing, the robots achieve rendezvous, that is, they move to a common location. Each robot is a point mass moving in a ..."

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Multirobot rendezvous with visibility sensors in nonconvex environments Abstract—This paper presents a coordination algorithm for mobile autonomous robots. Relying upon distributed sensing, the robots achieve rendezvous, that is, they move to a common location. Each robot is a point mass moving in a simply connected, nonconvex, unknown environment according to an omnidirectional kinematic model. Each robot is equipped with line-of-sight limited-range sensors, i.e., a robot can measure the relative position of any object (robots or environment boundary) if and only if the object is within a given distance and there are no obstacles in-between. The Perimeter Minimizing Algorithm is designed using the notions of robust visibility, connectivity-preserving constraint sets, and proximity graphs. The algorithm is guaranteed to achieve rendezvous if the interagent sensing graph is connected at any time during the evolution of the group. Simulations illustrate the theoretical results and the performance of the proposed algorithm in asynchronous setups and with measurement errors, control errors and non-zero robot size. Index Terms—Multi-robot coordination, Cooperative control,

### unknown title

"... Multirobot rendezvous with visibility sensors in nonconvex environments Abstract—This paper presents a coordination algorithm for mobile autonomous robots. Relying upon distributed sensing, the robots achieve rendezvous, that is, they move to a common location. Each robot is a point mass moving in a ..."

Abstract
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(Show Context)
Multirobot rendezvous with visibility sensors in nonconvex environments Abstract—This paper presents a coordination algorithm for mobile autonomous robots. Relying upon distributed sensing, the robots achieve rendezvous, that is, they move to a common location. Each robot is a point mass moving in a simply connected, nonconvex, unknown environment according to an omnidirectional kinematic model. Each robot is equipped with line-of-sight limited-range sensors, i.e., a robot can measure the relative position of any object (robots or environment boundary) if and only if the object is within a given distance and there are no obstacles in-between. The Perimeter Minimizing Algorithm is designed using the notions of robust visibility, connectivity-preserving constraint sets, and proximity graphs. The algorithm is guaranteed to achieve rendezvous if the interagent sensing graph is connected at any time during the evolution of the group. Simulations illustrate the theoretical results and the performance of the proposed algorithm in asynchronous setups and with measurement errors, control errors and non-zero robot size. Index Terms—Multi-robot coordination, Cooperative control,