This paper presents two novel control methodologies for the cooperative manipulation of an object by N robotic agents. Firstly, we design an adaptive control protocol which employs quaternion feedback for the object orientation to avoid potential representation singularities. Secondly, we propose a control protocol that guarantees predefined transient and steadystate performance for the object ...

This chapter deals with the problem of persistent observation of a wide area scene through decentralized, cooperative control of an active camera network. We focus on applications where events unfold over a large geographic area and need to be analyzed by multiple cameras. There is no central unit accumulating and analyzing all the data. The overall goal is to observe all objects (i.e., targets...

As networks of video cameras are being installed in many applications, modeling and inference strategies in video networks have captured more and more interest. There are many challenge problems, such as (i) traditional computer vision challenges in tracking and recognition, robustness to pose, illumination, occlusion, clutter; recognition of objects and activities; (ii) aggregating local infor...

This paper addresses the problem of cooperative transportation of an object rigidly grasped by N robotic agents. We propose a Nonlinear Model Predictive Control (NMPC) scheme that guarantees the navigation of the object to a desired pose in a bounded workspace with obstacles, while complying with certain input saturations of the agents. The control scheme is based on inter-agent communication a...

Decentralized control of networked systems has been widely investigated in the literature, with the aim of obtaining coordinated emerging behaviors (e.g. synchronization, swarming, coverage, formation control) by means of local interaction. In this paper we consider the possibility of injecting external inputs into the networked system, in order to obtain more complex cooperative behaviors. Spe...

Limited communication resources have gradually become a critical factor toward efficiency of decentralized large scale multi-agent coordination when both system scales up and tasks become more complex. In current researches, due to the agent's limited communication and observational capability, an agent in a decentralized setting can only choose a part of channels to access, but cannot perceive...

Simultaneous tracking and formation control is addressed for a team of autonomous agents that evolve dynamically in a space containing a measurable vector field. Each agent measures the local value of the field along its trajectory and occasionally shares relevant information with other agents, in order to estimate the spatial average obtained from averaging measurements across all agents. Usin...

Collaborative driving is a growing domain of intelligent transportation systems (ITS) that makes use of communications to autonomously guide cooperative vehicles on an automated highway system (AHS). In this paper, we address this issue by using a platoon of cars considered as more or less autonomous software agents. To achieve this, we propose a hierarchical driving agent architecture based on...

Over the last five years, the AI community has shown considerable interest in decentralized control of multiple decision makers or “agents” under uncertainty. This problem arises in many application domains, such as multi-robot coordination, manufacturing, information gathering, and load balancing. Such problems must be treated as decentralized decision problems because each agent may have diff...

abstractthe present study attempted to investigate the impact of cooperation versus collaboration on college students` reading ability. to fulfill the purpose of the study, 90 participants were chosen from among 140 by means of administering the nelson proficiency test. they were divided into three groups: cooperative group, collaborative group, and control group. a fifty-item multiple-choice r...