No abstract

No abstract

No abstract

In this paper, we address a class of distributed optimization problems in the presence of inter-agent communication delays based on passivity. We first focus on unconstrained distributed optimization and provide a passivity-based perspective for distributed optimization algorithms. This perspective allows us to handle communication delays while using scattering transformation. Moreover, we extend the results to constrained distributed optimization, where it is shown that the problem is solved by just adding one more feedback loop of a passive system to the solution of the unconstrained ones. We also show that delays can be incorporated in the same way as the unconstrained problems. Finally, the algorithm is applied to a visual human localization problem using a pedestrian detection algorithm.

In this paper the coverage control for mobile sensor networks is studied. The novelty is to consider an anisotropic sensor model where the performance of the sensor depends not only on the distance but also on the orientation from the sensor to the target. Moreover we consider sensors with limited-range sensing defined by a probabilistic model and we assume that each robot is equipped with omni-directional communication capability. A gradient-based distributed algorithm is designed to maximize the joint detection probabilities of the events in the region of interest by the sensors. Simulations illustrate the results.

In this paper the coverage control problem for mobile sensor networks is studied. The novelty is to consider an anisotropic sensor model where the performance of the sensor depends not only on the distance but also on the orientation to the target. By adapting the Lloyd algorithm and assuming a fixed and equal sensor orientation, a distributed control law is derived. Aside from coverage, the control law also guarantees collision avoidance between the agents. A simulation is provided to illustrate the results obtained in this paper. Furthermore, a numerical performance analysis to compare the anisotropic sensors modelling to isotropic approximations is performed.

This paper investigates bilateral human-swarminteractions wherein the objective is to guarantee human operator enabled synchronization of positions/velocities of an ensemble of kinematic robots to desired reference inputs. We first present a feedback loop configuration, where every robot implements a cooperative controller and the human visually feedbacks the average positions/velocities of the accessible robots depending on the selected (position or velocity) control modes. Asymptotic synchronization is demonstrated by assuming passivity of an appropriately defined human operator decision process. The aforementioned passivity assumption and learning ability of the operator are studied through experiments on a human-in-the-loop simulator. It is observed that learning has a positive effect on passivity, but passivity of the decision process may nevertheless be violated in the high frequency domain depending on the network connection. Hence, passivation scheme is presented for the operator's decision process and it is demonstrated for three different interconnection structures among the kinematic robots and operator.

No abstract