On the trajectory tracking control for an SCARA robot manipulator in a fractional model driven by induction motors with PSO tuning

This paper describes the fractional modeling and control of an industrial selective compliant assembly robot arm (SCARA); the fractional model was obtained by using the Euler–Lagrange and Hamilton formalisms. Each joint of the robot manipulator was driven by an induction motor. In this work, the fractional model of each induction motor was formulated, and the matching of the induction motors with the SCARA robot is shown. For comparison purposes, the SCARA robot control was formulated by conventional PI and PD and by fractional PI ^? and PD ^δ controllers. So each induction motor was controlled by using PI and fractional PI ^? controllers, and for trajectory tracking control, PD and fractional PD ^δ controllers were designed. For tuning the PI, PI ^? , PD, and PD ^δ controllers, the PSO algorithm was used; the same restrictions were used for the PI and PD classical controllers, and ITAE index was used as a cost function to be minimized. For computing the fractional derivatives and to obtain the numerical solution of the system, the Riemann–Liouville and Grünwald–Letnikov approaches were used. The numerical simulations have shown the effectiveness of the use of fractional PI ^? and PD ^δ controllers.     

A Learning Behavior Based Controller for Maintaining Balance in Robotic Locomotion

The Behavior Based Locomotion Controller (BBLC) extends the applicability of the behavior based control (BBC) architecture to redundant systems with multiple task-space motions. A set of control behaviors are attributed to each task-space motion individually and a reinforcement learning algorithm is used to select the combination of behaviors which can achieve the control objective. The resulting behavior combination is an emergent control behavior robust to unknown environments due to the added learning capability. Hence, the BBLC is applicable to complex redundant systems operating in unknown environments, where the emergent control behaviors can satisfy higher level control objectives such as balance in locomotion. The balance control problem of two robotic systems, a bipedal robot walker and a mobile manipulator, are used to study the performance of this controller. Results show that the BBLC strategy can generate emergent balancing strategies capable of adapting to new unknown disturbances from the environment, using only a small fixed library of balancing behaviors.     

Mining mobile application usage pattern for demand prediction by considering spatial and temporal relations

Recently, researches on smart phones have received attentions because the wide potential applications. One of interesting and useful topic is mining and predicting the users’ mobile application (App) usage behaviors. With more and more Apps installed in users’ smart phone, the users may spend much time to find the Apps they want to use by swiping the screen. App prediction systems benefit for reducing search time and launching time since the Apps which may be launched can preload in the memory before they are actually used. Although some previous studies had been proposed on the problem of App usage analysis, they recommend Apps for users only based on the frequencies of App usages. We consider that the relationship between App usage demands and users’ recent spatial and temporal behaviors may be strong. In this paper, we propose Spatial and Temporal App Recommender (STAR), a novel framework to predict and recommend the Apps for mobile users under a smart phone environment. The STAR framework consists of four major modules. We first find the meaningful and semantic location movements from the geographic GPS trajectory data by the Spatial Relation Mining Module and generate the suitable temporal segments by the Temporal Relation Mining Module. Then, we design Spatial and Temporal App Usage Pattern Mine (STAUP-Mine) algorithm to efficiently discover mobile users’ Spatial and Temporal App Usage Patterns (STAUPs). Furthermore, an App Usage Demand Prediction Module is presented to predict the following App usage demands according to the discovered STAUPs and spatial/temporal relations. To our knowledge, this is the first study to simultaneously consider the spatial movements, temporal properties and App usage behavior for mining App usage pattern and demand prediction. Through rigorous experimental analysis from two real mobile App datasets, STAR framework delivers an excellent prediction performance.     

An Improved Extended Active Observer for Adaptive Control of A <Emphasis Type="Italic">n</Emphasis><Emphasis Type="Italic">−</Emphasis>DOF Robot Manipulator

A novel algorithm for simultaneous force estimation and friction compensation of constrained motion of robot manipulators is presented. This represents an extension of the improved extended active observer (IEAOB) algorithm reported earlier and proposes a higher order IEAOB or N?th order IEAOB (IEAOB ?N) for a n?DOF robot manipulator. Central to this observer is the use of extra system states modeled as a Gauss-Markov (GM) formulation to estimate the force and disturbances including robot inertial parameters and friction. The stability of IEAOB ?N is verified through stability analysis. The IEAOB-1 is validated by applying it to a Phantom Omni haptic device against a Nicosia observer, disturbance observer (DOB)/reaction torque observer (RTOB), and nonlinear disturbance observer (NDO), respectively. The results show that the proposed IEAOB-1 is superior to the compared observers in terms of force estimation. Then, the performance of the IEAOB ? N is experimentally studied and compared to the IEAOB-1. Results demonstrate that the IEAOB ? N has an improved capability in tracking nonlinear external forces.     

Planning non-holonomic stable trajectories on uneven terrain through non-linear time scaling

In this paper, we present a framework for generating smooth and stable trajectories for wheeled mobile robots moving on uneven terrains. Instead of relying on static stability measures, the paper incorporates velocity and acceleration based constraints like no-slip and permanent wheel ground contact conditions in the planning framework. The paper solves this complicated problem in a computationally efficient manner with full 3D dynamics of the robot. The two major aspects of the proposed work are: Firstly, closed form functional relationships are derived which describes the 6 dof evolution of the robot’s state on an arbitrary 2.5D uneven terrain. This enables us to have a fast evaluation of robot’s dynamics along any candidate trajectory. Secondly, a novel concept of non-linear time scaling is introduced through which simple algebraic relations defining the bounds on velocities and accelerations are obtained. Moreover, non-linear time scaling also provides a new approach for manipulating velocities and accelerations along given geometric paths. It is thus exploited to obtain stable velocity and acceleration profiles. Extensive simulation results are presented to demonstrate the efficacy of the proposed methodology.     

<Emphasis Type="Italic">κ</Emphasis>-<Emphasis Type="Italic">PMP</Emphasis>: Enhancing Physics-based Motion Planners with Knowledge-Based Reasoning

Physics-based motion planning is a challenging task, since it requires the computation of the robot motions while allowing possible interactions with (some of) the obstacles in the environment. Kinodynamic motion planners equipped with a dynamic engine acting as state propagator are usually used for that purpose. The difficulties arise in the setting of the adequate forces for the interactions and because these interactions may change the pose of the manipulatable obstacles, thus either facilitating or preventing the finding of a solution path. The use of knowledge can alleviate the stated difficulties. This paper proposes the use of an enhanced state propagator composed of a dynamic engine and a low-level geometric reasoning process that is used to determine how to interact with the objects, i.e. from where and with which forces. The proposal, called κ-PMP can be used with any kinodynamic planner, thus giving rise to e.g. κ-RRT. The approach also includes a preprocessing step that infers from a semantic abstract knowledge described in terms of an ontology the manipulation knowledge required by the reasoning process. The proposed approach has been validated with several examples involving an holonomic mobile robot, a robot with differential constraints and a serial manipulator, and benchmarked using several state-of-the art kinodynamic planners. The results showed a significant difference in the power consumption with respect to simple physics-based planning, an improvement in the success rate and in the quality of the solution paths.     

Study on microchannel flows with a sudden contraction–expansion at a wide range of Knudsen number using lattice Boltzmann method

Numerical simulations have been performed on the pressure-driven rarefied flow through channels with a sudden contraction–expansion of 2:1:2 using isothermal two and three-dimensional lattice Boltzmann method (LBM). In the LBM, a Bosanquet-type effective viscosity and a modified second-order slip boundary condition are used to account for the rarefaction effect on gas viscosity to cover the slip and transition flow regimes, that is, a wider range of Knudsen number. Firstly, the in-house LBM code is verified by comparing the computed pressure distribution and flow pattern with experimental ones measured by others. The verified code is then used to study the effects of the outlet Knudsen number Kn _o , driving pressure ratio P _i /P _o , and Reynolds number Re, respectively, varied in the ranges of 0.001–1.0, 1.15–5.0, and 0.02–120, on the pressure distributions and flow patterns as well as to document the differences between continuum and rarefied flows. Results are discussed in terms of the distributions of local pressure, Knudsen number, centerline velocity, and Mach number. The variations of flow patterns and vortex length with Kn _o and Re are also documented. Moreover, a critical Knudsen number is identified to be Kn _oc  = 0.1 below and above which the behaviors of nonlinear pressure profile and velocity distribution and the variations of vortex length with Re upstream and downstream of constriction are different from those of continuum flows.     

Filtration of aerosol particles by cylindrical fibers within a parallel and staggered array

The World Health Organization (WHO) in 2013 reported that more than seven million unexpected losses every year are credited to air contamination. Because of incredible adaptability and expense viability of fibrous filters, they are broadly used for removing particulates from gasses. The influence of appropriate parameters, e.g., the fiber arrangement, solid volume fraction (SVF or α), fluid flow face velocity (mean inlet velocity), and filter thickness (I _x ), on pressure drop and deposition efficiency are researched. Furthermore, to study the effects of variation of the laminar flow regime and fiber’s cross-sectional shape on the deposition of particles, only a single square fiber has been placed in a channel. By means of finite volume method (FVM), the 2-D motion of 100–1000 nm particles was investigated numerically. The Lagrangian method has been employed and the Saffman’s lift, Drag, and Brownian forces have been considered to affect this motion. Contribution of increasing the Reynolds number to filtration performance increased with smaller fine aerosols to a level of 59.72 %. However, for over 500 nm, the Re = 100 has more efficient results up to 26.97 %. Remarkably, the single square fiber in Re = 200 regime performs similarly to the optimum choice of multi-fibrous filters. It was portrayed the parallel circular multi-fibrous filter with a ratio of horizontal-to-vertical distances between fibers, l/h = 1.143; α = 0.687, I _x  = 116.572, and h/d _f  = 1.0 is the most efficient filter’s structure. The increase in the ratio of vertical distances between fibers-to-fiber’s diameter (h/d _f ) and decrease in SVF or α, results in a drastically decrement of the filtration performance of both parallel and staggered structures. The obtained results have been validated with previous research findings.     

Planar collision-type dependence on incident angle and on friction coefficient

This work addresses the ‘hard collision’ approach to the solution of planar, simple non-holonomic systems undergoing a one-point collision-with-friction problem, showing that (i) there are no coherent types of collision whereby forward sliding follows sticking, unless the initial relative tangential velocity of the colliding points vanishes; and (ii) the type of collision can be determined directly, given the collision angle of incidence \(\alpha\) and Coulomb’s coefficient of friction \(\mu\) between the colliding points. The classic hitting rod problem is used to illustrate the \(\alpha \)–\(\mu\) collision-type dependence. Finally, the relation between collision with friction and tangential impact problems in multibody systems is briefly discussed.     

Interactive transmission processing for large images in a resource-constraint mobile wireless network

In the state-of-the-art methods for (large) image transmission, no user interaction behaviors (e.g., user tapping) can be actively involved to affect the transmission performance (e.g., higher image transmission efficiency with relatively poor image quality). So, to effectively and efficiently reduce the large image transmission costs in resource-constraint mobile wireless networks (MWN), we design a content-based and bandwidth-aware Interactive large Image Transmission method in MWN, called the I it. To the best of our knowledge, this is the first study on the interactive image transmission. The whole transmission processing of the I it works as follows: before transmission, a preprocessing step computes the optimal and initial image block (IB) replicas based on the image content and the current network bandwidth at the sender node. During transmission, in case of unsatisfied transmission efficiency, the user’s anxiety to preview the image can be implicitly indicated by the frequency of tapping the screen. In response, the transmission resolutions of the candidate IB replicas can be dynamically adjusted based on the user anxiety degree (UAD). Finally, the candidate IB replicas are transmitted with different priorities to the receiver for reconstruction and display. The experimental results show that the performance of our approach is both efficient and effective, minimizing the response time by decreasing the network transmission cost while improving user experiences.     

The pursuit-evasion game on the 1-skeleton graph of a regular polyhedron. I

We consider a game between a group of n pursuers and one evader moving with the same maximum velocity along the 1-skeleton graph of a regular polyhedron. The goal of the paper is finding, for each regular polyhedron M, a number N(M) with the following properties: if n ≥ N(M), the group of pursuers wins, while if n < N(M), the evader wins. Part I of the paper is devoted to the case of polyhedra in ?³; Part II will be devoted to the case of ? ^d , d ≥ 5; and Part III, to the case of ?⁴.     

<Emphasis Type="Italic">D</Emphasis>-decomposition technique state-of-the-art

It is a survey of recent extensions and new applications for the classical D-decomposition technique. We investigate the structure of the parameter space decomposition into root invariant regions for single-input single-output systems linear depending on the parameters. The D-decomposition for uncertain polynomials is considered as well as the problem of describing all stabilizing controllers of the certain structure (for instance, PID-controllers) that satisfy given H _∞-criterion. It is shown that the D-decomposition technique can be naturally linked with M-Δ framework (a general scheme for analysis of uncertain systems) and it is applicable for describing feasible sets for linear matrix inequalities. The problem of robust synthesis for linear systems can be also treated via D-decomposition technique.     

Motion of spin-half particles in the axially symmetric field of naked singularities of the static <Emphasis Type="Italic">q</Emphasis>-metric

Quantum-mechanical motion of a spin-half particle is examined in the axially symmetric fields of static naked singularities formed by a mass distribution with a quadrupole moment (q-metric). The analysis is performed by means of the method of effective potentials of the Dirac equation generalized to the case where radial and angular variables are not separated. If ?1 < q < qlim, |qlim| ? 1, where q is the quadrupolemoment in proper units, the naked singularities do not exclude the existence of stationary bound states of Dirac particles for a prolate mass distribution in the q-metric along the axial axis. For an oblate mass distribution, the naked singularities of the q-metric are separated from a Dirac particle by infinitely large repulsive barriers followed by a potential well which deepens while moving apart from the equator (from θ = θ _min or θ = π ? θ _min) toward the poles. The poles make an exception, and at 0 < q < q*, there are some points θ _i for particle states with j ≥ 3/2.     

Sleeping on the Job: Energy-Efficient and Robust Broadcast for Radio Networks

We address the problem of minimizing power consumption when broadcasting a message from one node to all the other nodes in a radio network. To enable power savings for such a problem, we introduce a compelling new data streaming problem which we call the Bad Santa problem. Our results on this problem apply for any situation where: (1) a node can listen to a set of n nodes, out of which at least half are non-faulty and know the correct message; and (2) each of these n nodes sends according to some predetermined schedule which assigns each of them its own unique time slot. In this situation, we show that in order to receive the correct message with probability 1, it is necessary and sufficient for the listening node to listen to a \(\Theta(\sqrt{n})\) expected number of time slots. Moreover, if we allow for repetitions of transmissions so that each sending node sends the message O(log?^? n) times (i.e. in O(log?^? n) rounds each consisting of the n time slots), then listening to O(log?^? n) expected number of time slots suffices. We show that this is near optimal.We describe an application of our result to the popular grid model for a radio network. Each node in the network is located on a point in a two dimensional grid, and whenever a node sends a message m, all awake nodes within L _∞ distance r receive m. In this model, up to \(t<\frac{r}{2}(2r+1)\) nodes within any 2r+1 by 2r+1 square in the grid can suffer Byzantine faults. Moreover, we assume that the nodes that suffer Byzantine faults are chosen and controlled by an adversary that knows everything except for the random bits of each non-faulty node. This type of adversary models worst-case behavior due to malicious attacks on the network; mobile nodes moving around in the network; or static nodes losing power or ceasing to function. Let n=r(2r+1). We show how to solve the broadcast problem in this model with each node sending and receiving an expected \(O(n\log^{2}{|m|}+\sqrt{n}|m|)\) bits where |m| is the number of bits in m, and, after broadcasting a fingerprint of m, each node is awake only an expected \(O(\sqrt{n})\) time slots. Moreover, for t≤(1?ε)(r/2)(2r+1), for any constant ε>0, we can achieve an even better energy savings. In particular, if we allow each node to send O(log?^? n) times, we achieve reliable broadcast with each node sending O(nlog?²|m|+(log?^? n)|m|) bits and receiving an expected O(nlog?²|m|+(log?^? n)|m|) bits and, after broadcasting a fingerprint of m, each node is awake for only an expected O(log?^? n) time slots. Our results compare favorably with previous protocols that required each node to send Θ(|m|) bits, receive Θ(n|m|) bits and be awake for Θ(n) time slots.     

Unprovable Security of Perfect NIZK and Non-interactive Non-malleable Commitments

We present barriers to provable security of two important cryptographic primitives, perfect non-interactive zero knowledge (NIZK) and non-interactive non-alleable commitments:

1. ○
   Black-box reductions cannot be used to demonstrate adaptive soundness (i.e., that soundness holds even if the statement to be proven is chosen as a function of the common reference string) of any statistical NIZK for NP based on any “standard” intractability assumptions.
    
2. ○
   Black-box reductions cannot be used to demonstrate non-malleability of non-interactive, or even 2-message, commitment schemes based on any “standard” intractability assumptions.
    

We emphasize that the above separations apply even if the construction of the considered primitives makes a non-black-box use of the underlying assumption.

As an independent contribution, we suggest a taxonomy of game-based intractability assumptions.     

Guaranteed strategies for escaping encirclement

This paper considers a conflict situation on the plane as follows. A fast evader E has to break out the encirclement of slow pursuers P _{j1,...,j n} = {P _j1,..., P _jn }, n ≥ 3, with a miss distance not smaller than r ≥ 0. First, we estimate the minimum guaranteed miss distance from E to a pursuer P _a , a ∈ {j ₁,..., j _n }, when the former moves along a given straight line. Then the obtained results are used to calculate the guaranteed estimates to a group of two pursuers P _b,c = {P _b , P _c }, b, c ∈ {j ₁,..., j _n }, b ≠ c, when E maneuvers by crossing the rectilinear segment P _b P _c , and the state passes to the domain of the game space where E applies a strategy under which the miss distance to any of the pursuers is not decreased. In addition, we describe an approach to the games with a group of pursuers P _{j1,... jn} , n ≥ 3, in which E seeks to break out the encirclement by passing between two pursuers P _b and P _c , entering the domain of the game space where E can increase the miss distance to all pursuers by straight motion. By comparing the guaranteed miss distances with r for all alternatives b, c ∈ {j ₁,..., j _n }, b ≠ c, and a ? {b, c}, it is possible to choose the best alternative and also to extract the histories of the game in which the designed evasion strategies guarantee a safe break out from the encirclement.     

Experience Learning From Basic Patterns for Efficient Robot Navigation in Indoor Environments

In this paper we propose a machine learning technique for real-time robot path planning for an autonomous robot in a planar environment with obstacles where the robot possess no a priori map of its environment. Our main insight in this paper is that a robot’s path planning times can be significantly reduced if it can refer to previous maneuvers it used to avoid obstacles during earlier missions, and adapt that information to avoid obstacles during its current navigation. We propose an online path planning algorithm called LearnerRRT that utilizes a pattern matching technique called Sample Consensus Initial Alignment (SAC-IA) in combination with an experience-based learning technique to adapt obstacle boundary patterns encountered in previous environments to the current scenario followed by corresponding adaptations in the obstacle-avoidance paths. Our proposed algorithm LearnerRRT works as a learning-based reactive path planning technique which enables robots to improve their overall path planning performance by locally improving maneuvers around commonly encountered obstacle patterns by accessing previously accumulated environmental information. We have conducted several experiments in simulations and hardware to verify the performance of the LearnerRRT algorithm and compared it with a state-of-the-art sampling-based planner. LearnerRRT on average takes approximately 10% of the planning time and 14% of the total time taken by the sampling-based planner to solve the same navigation task based on simulation results and takes only 33% of the planning time, 46% of total time and 95% of total distance compared to the sampling-based planner based on our hardware results.     

An effective contrast sequential pattern mining approach to taxpayer behavior analysis

Data mining for client behavior analysis has become increasingly important in business, however further analysis on transactions and sequential behaviors would be of even greater value, especially in the financial service industry, such as banking and insurance, government and so on. In a real-world business application of taxation debt collection, in order to understand the internal relationship between taxpayers’ sequential behaviors (payment, lodgment and actions) and compliance to their debt, we need to find the contrast sequential behavior patterns between compliant and non-compliant taxpayers. Contrast Patterns (CP) are defined as the itemsets showing the difference/discrimination between two classes/datasets (Dong and Li, 1999). However, the existing CP mining methods which can only mine itemset patterns, are not suitable for mining sequential patterns, such as time-ordered transactions in taxpayer sequential behaviors. Little work has been conducted on Contrast Sequential Pattern (CSP) mining so far. Therefore, to address this issue, we develop a CSP mining approach, e C S P, by using an effective CSP-tree structure, which improves the PrefixSpan tree (Pei et al., 2001) for mining contrast patterns. We propose some heuristics and interestingness filtering criteria, and integrate them into the CSP-tree seamlessly to reduce the search space and to find business-interesting patterns as well. The performance of the proposed approach is evaluated on three real-world datasets. In addition, we use a case study to show how to implement the approach to analyse taxpayer behaviour. The results show a very promising performance and convincing business value.