Visual servo control rules that refer to the control methods of robot motion planning using image data acquired from the camera mounted on the robot have been widely applied to the motion control of robotic arms or mobile robots. The methods are usually classified as image-based visual servo, position-based visual servo, and hybrid visual servo (HVS) control rules. Mobile manipulation enhances the working range and flexibility of robotic arms. However, there is little work on applying visual servo control rules to the motion of the whole mobile manipulation robot. We propose an HVS motion control method for a mobile manipulation robot which combines a six-degree- of-freedom (6-DOF) robotic arm with a nonholonomic mobile base. Based on the kinematic differential equations of the mobile manipulation robot, the global Jacobian matrix of the whole robot is derived, and the HVS control equation is derived using the whole Jacobian matrix combined with position and visual image information. The distance between the gripper and target is calculated through the observation of the marker by a camera mounted on the gripper. The differences between the positions of the markers’ feature points and the expected positions of them in the image coordinate system are also calculated. These differences are substituted into the control equation to obtain the speed control law of each degree of freedom of the mobile manipulation robot. To avoid the position error caused by observation, we also introduce the Kalman filter to correct the positions and orientations of the end of the manipulator. Finally, the proposed algorithm is validated on a mobile manipulation platform consisting of a Bulldog chassis, a UR5 robotic arm, and a ZED camera.
We present a novel indirect adaptive fuzzy-regulated optimal control scheme for continuous-time nonlinear systems with unknown dynamics, mismatches, and disturbances. Initially, the Hamilton-Jacobi-Bellman (HJB) equation associated with its performance function is derived for the original nonlinear systems. Unlike existing adaptive dynamic programming (ADP) approaches, this scheme uses a special non-quadratic variable performance function as the reinforcement medium in the actor-critic architecture. An adaptive fuzzy-regulated critic structure is correspondingly constructed to configure the weighting matrix of the performance function for the purpose of approximating and balancing the HJB equation. A concurrent self-organizing learning technique is designed to adaptively update the critic weights. Based on this particular critic, an adaptive optimal feedback controller is developed as the actor with a new form of augmented Riccati equation to optimize the fuzzy-regulated variable performance function in real time. The result is an online indirect adaptive optimal control mechanism implemented as an actor-critic structure, which involves continuous-time adaptation of both the optimal cost and the optimal control policy. The convergence and closed-loop stability of the proposed system are proved and guaranteed. Simulation examples and comparisons show the effectiveness and advantages of the proposed method.
Tagging is a defining characteristic of Web 2.0. It allows users of social computing systems (e.g., question and answering (Q&A) sites) to use free terms to annotate content. However, is tagging really a free action? Existing work has shown that users can develop implicit consensus about what tags best describe the content in an online community. However, there has been no work studying the regularities in how users order tags during tagging. In this paper, we focus on the natural ordering of tags in domain-specific Q&A sites. We study tag sequences of millions of questions in four Q&A sites, i.e., CodeProject, SegmentFault, Biostars, and CareerCup. Our results show that users of these Q&A sites can develop implicit consensus about in which order they should assign tags to questions. We study the relationships between tags that can explain the emergence of natural ordering of tags. Our study opens the path to improve existing tag recommendation and Q&A site navigation by leveraging the natural ordering of tags.
Service composition is an effective method of combining existing atomic services into a value-added service based on cost and quality of service (QoS). To meet the diverse needs of users and to offer pricing services based on QoS, we propose a service composition auction mechanism based on user preferences, which is strategy-proof and can be beneficial in selecting services based on user preferences and dynamically determining the price of services. We have proven that the proposed auction mechanism achieves desirable properties including truthfulness and individual rationality. Furthermore, we propose an auction algorithm to implement the auction mechanism, and carry out extensive experiments based on real data. The results verify that the proposed auction mechanism not only achieves desirable properties, but also helps users find a satisfactory service composition scheme.
Special curves in the Minkowski space such as Minkowski Pythagorean hodograph curves play an important role in computer-aided geometric design, and their usages are thoroughly studied in recent years. Bizzarri et al. (2016) introduced the class of Rational Envelope (RE) curves, and an interpolation method for G1 Hermite data was presented, where the resulting RE curve yielded a rational boundary for the represented domain. We now propose a new application area for RE curves: skinning of a discrete set of input circles. We show that if we do not choose the Hermite data correctly for interpolation, then the resulting RE curves are not suitable for skinning. We introduce a novel approach so that the obtained envelope curves touch each circle at previously defined points of contact. Thus, we overcome those problematic scenarios in which the location of touching points would not be appropriate for skinning purposes. A significant advantage of our proposed method lies in the efficiency of trimming offsets of boundaries, which is highly beneficial in computer numerical control machining.
We investigate the solution and stability of continuous-time cross-dimensional linear systems (CCDLSs) with dimension bounded by V-addition and V-product. Using the integral iteration method, the solution to CCDLSs can be obtained. Based on the new algebraic expression of the solution and the Jordan decomposition method of matrix, a necessary and sufficient condition is derived for judging whether a CCDLS is asymptotically stable with a given initial state. This condition demonstrates a method for finding the domain of attraction and its relationships. Then, all the initial states that can be stabilized are studied, and a method for designing the corresponding controller is proposed. Two examples are presented to illustrate the validity of the theoretical results.
We investigate the stability of Boolean networks (BNs) with impulses triggered by both states and random factors. A hybrid index model is used to describe impulsive BNs. First, several necessary and sufficient conditions for forward completeness are obtained. Second, based on the stability criterion of probabilistic BNs and the forward completeness criterion, the necessary and sufficient conditions for the finite-time stability with probability one and the asymptotical stability in distribution are presented. The relationship between these two kinds of stability is discussed. Last, examples and time-domain simulations are provided to illustrate the obtained results.
While the Nyquist rate serves as a lower bound to sample a general bandlimited signal with no information loss, the sub-Nyquist rate may also be sufficient for sampling and recovering signals under certain circumstances. Previous works on sub-Nyquist sampling achieved dimensionality reduction mainly by transforming the signal in certain ways. However, the underlying structure of the sub-Nyquist sampled signal has not yet been fully exploited. In this paper, we study the fundamental limit and the method for recovering data from the sub-Nyquist sample sequence of a linearly modulated baseband signal. In this context, the signal is not eligible for dimension reduction, which makes the information loss in sub-Nyquist sampling inevitable and turns the recovery into an under-determined linear problem. The performance limits and data recovery algorithms of two different sub-Nyquist sampling schemes are studied. First, the minimum normalized Euclidean distances for the two sampling schemes are calculated which indicate the performance upper bounds of each sampling scheme. Then, with the constraint of a finite alphabet set of the transmitted symbols, a modified time-variant Viterbi algorithm is presented for efficient data recovery from the sub-Nyquist samples. The simulated bit error rates (BERs) with different sub-Nyquist sampling schemes are compared with both their theoretical limits and their Nyquist sampling counterparts, which validates the excellent performance of the proposed data recovery algorithm.
With the rapid development of electronic information technology, digital signature has become an indispensable part of our lives. Traditional public key certificate cryptosystems cannot overcome the limitations of certificate management. Identity-based cryptosystems can avoid the certificate management issues. The development of quantum computers has brought serious challenges to traditional cryptography. Post-quantum cryptography research is imperative. At present, almost all post-quantum identity-based signature (IBS) schemes are constructed using Gaussian sampling or trapdoor technologies. However, these two technologies have a great impact on computational efficiency. To overcome this problem, we construct an IBS scheme on lattices by employing Lyubashevsky’s signature scheme. Based on the shortest vector problem on lattices, our scheme does not use Gaussian sampling or trapdoor technologies. In the random oracle model, it is proved that our scheme is strongly unforgeable against adaptive chosen messages and identity attacks. The security level of our scheme is strongly unforgeable, which is a higher level than the existential unforgeability of other schemes. Compared with other efficient schemes, our scheme has advantages in computation complexity and security.
A 0.20–2.43 GHz fractional-N frequency synthesizer is presented for multi-band wireless communication systems, in which the scheme adopts low phase noise voltage-controlled oscillators (VCOs) and a charge pump (CP) with reduced current mismatch. VCOs that determine the out-band phase noise of a phase-locked loop (PLL) based frequency synthesizer are optimized using an automatic amplitude control technique and a high-quality factor figure-8-shaped inductor. A CP with a mismatch suppression architecture is proposed to improve the current match of the CP and reduce the PLL phase errors. Theoretical analysis is presented to investigate the influence of the current mismatch on the output performance of PLLs. Fabricated in a TSMC 0.18-μm CMOS process, the prototype operates from 0.20 to 2.43 GHz. The PLL synthesizer achieves an in-band phase noise of−96.8 dBc/Hz and an out-band phase noise of −122.8 dBc/Hz at the 2.43-GHz carrier. The root-mean-square jitter is 1.2 ps under the worst case, and the measured reference spurs are less than −65.3 dBc. The current consumption is 15.2 mA and the die occupies 850 μm×920 μm.
Infrared Earth sensors are widely used in attitude-determination and control systems of satellites. The main deficiency of static infrared Earth sensors is the requirement of a small field of view (FOV). A typical FOV for a static infrared Earth sensor is about 20◦ to 30◦, which may not be sufficient for low-Earth-orbiting microsatellites. A novel compact infrared Earth sensor with an FOV of nearly 180◦ is developed here. The Earth sensor comprises a panoramic annular lens (PAL) and an off-the-shelf camera with an uncooled complementary-metaloxide- semiconductor (CMOS) infrared sensor. PAL is used to augment FOV so as to obtain a complete infrared image of the Earth from low-Earth-orbit. An algorithm is developed to compensate for the distortion caused by PAL and to calculate the vector of the Earth. The new infrared Earth sensor is compact with low power consumption and high precision. Simulated images and on-orbit infrared images obtained via the micro-satellite ZDPS-2 are used to assess the performance of the new infrared Earth sensor. Experiments show that the accuracy of the Earth sensor is about 0.032◦.
As an increasingly popular flow metering technology, Coriolis mass flowmeter exhibits high measurement accuracy under single-phase flow condition and is widely used in the industry. However, under complex flow conditions, such as two-phase flow, the measurement accuracy is greatly decreased due to various factors including improper signal processing methods. In this study, three digital signal processing methods—the quadrature demodulation (QD) method, Hilbert method, and sliding discrete time Fourier transform method—are analyzed for their applications in processing sensor signals and providing measurement results under gas-liquid two-phase flow condition. Based on the analysis, specific improvements are applied to each method to deal with the signals under two-phase flow condition. For simulation, sensor signals under single- and two-phase flow conditions are established using a random walk model. The phase difference tracking performances of these three methods are evaluated in the simulation. Based on the digital signal processor, a converter program is implemented on its evaluation board. The converter program is tested under single- and two-phase flow conditions. The improved signal processing methods are evaluated in terms of the measurement accuracy and complexity. The QD algorithm has the best performance under the single-phase flow condition. Under the two-phase flow condition, the QD algorithm performs a little better in terms of the indication error and repeatability than the improved Hilbert algorithm at 160, 250, and 420 kg/h flow points, whereas the Hilbert algorithm outperforms the QD algorithm at the 600 kg/h flow point.