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In this paper we consider a team of mobile nodes that are in charge of cooperative target tracking. We propose communication-aware navigation functions that allow the nodes to perform their task while maintaining their connectivity to a fixed base station and avoiding obstacles. More specifically, we show how to incorporate measures of link qualities in the navigation functions. We consider both centralized...
In this paper we consider a team of robots that are tasked with tracking a moving target cooperatively, while maintaining their connectivity to a base station and avoiding collision. We propose a novel extension of the classical navigation function framework in order to ensure task completion. More specifically, we modify the classical definition of the navigation functions to (1) incorporate measures...
In this paper, we propose a decentralized control scheme for combined motion/force control of nonredundant multi-manipulator robotic systems, cooperatively grasping a rigid body in a prespecified position/force trajectory. The proposed control scheme uses the impedance method for modeling the internal force exerted by the end effectors to the object. The precise mathematical analysis of the overall...
Fractional order PID controllers are suitable for almost all types of dynamic models. In this paper, a new adaptive fractional order PID controller using neural networks is introduced.The overall performance using the proposed adaptive fractional order PID controller is demonstrated through some examples. It is shown that the new controller scheme can give excellent performance and more robustness...
In this paper, we propose two fully decentralized adaptive and robust control schemes for combined motion/force control of nonredundant multi-manipulator robotic systems, cooperatively grasping a rigid body in a prespecified position/force trajectory. The precise mathematical analysis of the overall dynamical system and the two proposed control schemes are presented. The controllers are tested and...
In this paper, we propose a new state estimation filter called POLYFILTER, which is based on polynomial approximation of the nonlinear transformation obtained using particular multidimensional extension of Stirling's Interpolation Formula (SIF). In contrast to the Extended Kalman Filtering, no derivatives are needed in the interpolation formula; only function evaluations are needed during interpolation...
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