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Robot calibration to provide an accurate kinematic model is widely adopted in the advanced controller development of articulated serial robot performing complicated tasks. Conventional calibration methods mainly focus on the complete, continuous, and minimal error modeling. The generation and accumulation of errors have not been explicitly explained. In addition, the error identification and compensation sometimes are not practical for controller establishment. This article presents a robot calibration method using finite and instantaneous screw theory. From the differentiation of finite screw, the errors are defined by the deviations of instantaneous screws at initial pose. The error modeling is explicit. We also propose an advanced optimization algorithm based identification method and regard the geometry of redundant errors as constraints. The identified instantaneous screw errors are then converted to the joint actuation errors. Without modifying existing motion controller, errors are compensated by modified inputs. A UR3 robot is taken as an example to illustrate the calibration method. Simulation and experiment are implemented for verification. Comparing with the accuracy before calibration, the position and orientation accuracy of UR3 robot after calibration has improved by 94.75% and 89.29%. The results also show that modified inputs can be conveniently connected to controller development. [ABSTRACT FROM AUTHOR]

In current robot calibration approaches, the error propagation and identification of serial and parallel robots fail to be solved intuitively and generically, resulting in an inefficient calibration implementation and a low accuracy improvement. In this article, we present a generic error modeling method of serial robots and extend to parallel robots by finite and instantaneous screw (FIS) theory. The differential map and the explicit description of FIS on the robot motions enable a concise error modeling of the serial robot. The identifiability of errors in serial robot is discussed. The maximum independent errors are proved to be 4r + 2p + 6, where r and p are the numbers of revolute and prismatic joints, respectively. Based on the error mapping of serial limbs, reciprocal twist and wrench are introduced to consider the interaction among limbs and reveal the error propagation of the parallel robot. Then, the identification algorithms with high robustness and efficiency are investigated for the serial and parallel robots. Specifically, the conventional ill-conditioning problems of parallel robots are addressed. Finally, the proposed kinematic calibration framework for both types of robots are compared with the existing methods, and verified by simulations and experiments. The results show that our calibration approach improves the robot accuracy in a robust and efficient manner. [ABSTRACT FROM AUTHOR]

High-speed robots are being applied more and more widely in the scenarios of aviation manufacturing, electronic packaging, and three-dimensional printing, etc. To achieve high speed, the robots are typically designed to be lightweight, hence suffer from undesired vibration, so that the dynamic performance would deteriorate. In light of this, this paper considers the dynamic modeling and active control of an emerging redundant parallel robot. First, the recursively dynamic model is modularly established by means of Lagrangian multipliers method. For completeness, the model of permanent magnet synchronous motor is further integrated with the model of mechanical system to formulate the electromechanically coupled dynamic model (ECDM). To facilitate dynamic control, the ECDM is cleverly projected into the null space of constraint Jacobian matrix eliminating the need to compute Lagrangian multipliers explicitly. Based on singular perturbation approach and Tikhonov theorem, the ECDM is decomposed into two subsystems in different timescales. On this basis, a nonlinear hybrid control scheme is proposed for both trajectory tracking and vibration suppression. Numerical simulations suggest that the nonlinear hybrid control exhibits overwhelming performance than the conventional joint-based proportional and differential feedback control. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of “evil twin” attacks in wireless local area networks (WLANs). An evil twin is essentially a rogue (phishing) Wi-Fi access point (AP) that looks like a legitimate one (with the same SSID). It is set up by an adversary, who can eavesdrop on wireless communications of users' Internet access. Existing evil twin detection solutions are mostly for wireless network administrators to verify whether a given AP is in an authorized list or not, instead of for a wireless client to detect whether a given AP is authentic or evil. Such administrator-side solutions are limited, expensive, and not available for many scenarios. Thus, a lightweight, effective, and user-side solution is highly desired. In this work, we propose a novel user-side evil twin detection technique that outperforms traditional administrator-side detection methods in several aspects. Unlike previous approaches, our technique does not need a known authorized AP/host list, thus it is suitable for users to identify and avoid evil twins. Our technique does not strictly rely on training data of target wireless networks, nor depend on the types of wireless networks. We propose to exploit fundamental communication structures and properties of such evil twin attacks in wireless networks and to design new active, statistical and anomaly detection algorithms. Our preliminary evaluation in real-world widely deployed 802.11b and 802.11 g wireless networks shows very promising results. We can identify evil twins with a very high detection rate while maintaining a very low false positive rate. [ABSTRACT FROM PUBLISHER]