This paper proposed a new approach for the joint friction estimation of non-slipping walking biped robots. The proposed approach is based on the combination of a measurement-based strategy and a model-based method. The former is used to estimate the joint friction online when the foot is in contact with the ground, while the latter adopts a friction model to represent the joint friction when the leg is swinging. The measurement-based strategy utilizes the measured ground reaction forces (GRF) and the readings of an inertial measurement unit (IMU) located at the robot body. Based on these measurements, the joint angular accelerations and the body attitude and velocity are estimated. The aforementioned measurements and estimates are used in a reduced dynamical model of the biped. However, when the leg is swinging, this strategy is inapplicable. Therefore, a friction model is adopted. Its parameters are identified adaptively using the estimated online friction whenever the foot is in contact. The estimated joint friction is used in the feedback torque control signal. The proposed approach is validated using the full-dynamics of 12-DOF biped model. By using this approach, the robot center of mass (CoM) position error is reduced by 10% which demonstrates the effectiveness of this approach.

This paper introduces a novel approach to motion planning for a rapid mobile manipulator using inverted pendulum models. Our aim was to realize an actual rapid mobile manipulator with high acceleration and speed performance for an object's delivery. In our research, we developed an actual rapid mobile manipulator called KDMR-1. We proposed simple motion planning methods using a single inverted pendulum model (SIPM) and a double inverted pendulum model (DIPM), which are easily adaptable to a real-time system with only a small computational burden. The SIPM was useful for basic movement but did not provide object carrying capability. For that, a DIPM was proposed. In both models, we designed linear quadratic optimal controllers to stabilize the Zero Moment Point (ZMP). Two kinds of ZMP stabilization strategies were proposed, fixed ZMP and relaxed ZMP. Using these strategies, we realized optimal ZMP stabilizations for a real-time rapid mobile manipulator. For decoupled forward and rotational linear DIPM, we designed a centrifugal acceleration compensation model in the manner of feedback linearization. The experimental results showed high acceleration and speed performances during rapid object delivery.

One way to study certain classes of polynomials is by considering examples that are attached to combinatorial objects. Any graph $G$ has an associated reciprocal polynomial $R_{G}$ , and with two particular classes of reciprocal polynomials in mind one can ask the questions: (a) when is $R_{G}$ a product of cyclotomic polynomials (giving the cyclotomic graphs)? (b) when does $R_{G}$ have the minimal polynomial of a Salem number as its only non-cyclotomic factor (the non-trivial Salem graphs)? Cyclotomic graphs were classified by Smith (Combinatorial structures and their applications, Proceedings of Calgary International Conference, Calgary, AB, 1969 (eds R. Guy, H. Hanani, H. Saver and J. Schönheim; Gordon and Breach, New York, 1970) 403–406); the maximal connected ones are known as Smith graphs. Salem graphs are ‘spectrally close’ to being cyclotomic, in that nearly all their eigenvalues are in the critical interval $[-2,2]$ . On the other hand, Salem graphs do not need to be ‘combinatorially close’ to being cyclotomic: the largest cyclotomic induced subgraph might be comparatively tiny.

We define an $m$ -Salem graph to be a connected Salem graph $G$ for which $m$ is minimal such that there exists an induced cyclotomic subgraph of $G$ that has $m$ fewer vertices than $G$ . The $1$ -Salem subgraphs are both spectrally close and combinatorially close to being cyclotomic. Moreover, every Salem graph contains a $1$ -Salem graph as an induced subgraph, so these $1$ -Salem graphs provide some necessary substructure of all Salem graphs. The main result of this paper is a complete combinatorial description of all $1$ -Salem graphs: in the non-bipartite case there are $25$ infinite families and $383$ sporadic examples.

Writing in language tests is regarded as an important indicator for assessing language skills of test takers. As Chinese language tests become popular, scoring a large number of essays becomes a heavy and expensive task for the organizers of these tests. In the past several years, some efforts have been made to develop automated simplified Chinese essay scoring systems, reducing both costs and evaluation time. In this paper, we introduce a system called SCESS (automated Simplified Chinese Essay Scoring System) based on Weighted Finite State Automata (WFSA) and using Incremental Latent Semantic Analysis (ILSA) to deal with a large number of essays. First, SCESS uses an n-gram language model to construct a WFSA to perform text pre-processing. At this stage, the system integrates a Confusing-Character Table, a Part-Of-Speech Table, beam search and heuristic search to perform automated word segmentation and correction of essays. Experimental results show that this pre-processing procedure is effective, with a Recall Rate of 88.50%, a Detection Precision of 92.31% and a Correction Precision of 88.46%. After text pre-processing, SCESS uses ILSA to perform automated essay scoring. We have carried out experiments to compare the ILSA method with the traditional LSA method on the corpora of essays from the MHK test (the Chinese proficiency test for minorities). Experimental results indicate that ILSA has a significant advantage over LSA, in terms of both running time and memory usage. Furthermore, experimental results also show that SCESS is quite effective with a scoring performance of 89.50%.

This paper presents what is termed as the supervoxel normal distributions transform (SV-NDT), a novel three-dimensional (3-D) registration algorithm which improves the performance of the three-dimensional normal distributions transform (3-D NDT) significantly. The 3-D NDT partitions a model scan using a 3-D regular grid. Generating normal distributions using the 3-D regular grid causes considerable information loss because the 3-D regular grid does not use any information pertaining to the local surface structures of the model scan. The best type of surface (the constituent unit of each scan) for modeling with one normal distribution is known to be the plane. The SV-NDT reduces the loss of information using a supervoxel-generating algorithm at the partitioning stage. In addition, it uses the information of the local surface structures from the data scan by replacing the Euclidean distance with a function that uses local geometries as well as the Euclidean distance when each point in the data scan is matched to the corresponding normal distribution. Experiments demonstrate that the use of the supervoxel-generating algorithm increases the modeling accuracy of the normal distributions and that the proposed 3-D registration algorithm outperforms the 3-D NDT and other widely used 3-D registration algorithms in terms of robustness and speed on both synthetic and real-world datasets. Additionally, the effect of changing the function to create correspondences is also verified.

With its presence in data integration, chemistry, biological, and geographic systems, eXtensible Markup Language (XML) has become an important standard not only in computer science. A common problem among the mentioned applications involves structural clustering of XML documents—an issue that has been thoroughly studied and led to the creation of a myriad of approaches. In this paper, we present a comprehensive review of structural XML clustering. First, we provide a basic introduction to the problem and highlight the main challenges in this research area. Subsequently, we divide the problem into three subtasks and discuss the most common document representations, structural similarity measures, and clustering algorithms. In addition, we present the most popular evaluation measures, which can be used to estimate clustering quality. Finally, we analyze and compare 23 state-of-the-art approaches and arrange them in an original taxonomy. By providing an up-to-date analysis of existing structural XML clustering algorithms, we hope to showcase methods suitable for current applications and draw lines of future research.

Hajnal and Szemerédi proved that every graph G with |G| = ks and δ(G)⩾ k(s − 1) contains k disjoint s-cliques; moreover this degree bound is optimal. We extend their theorem to directed graphs by showing that every directed graph $\vv G$ with | $\vv G$ | = ks and δ( $\vv G$ ) ⩾ 2k(s − 1) − 1 contains k disjoint transitive tournaments on s vertices, where δ( $\vv G$ )= minv∈V ( $\vv G$ )d −(v)+d +(v). Our result implies the Hajnal–Szemerédi theorem, and its degree bound is optimal. We also make some conjectures regarding even more general results for multigraphs and partitioning into other tournaments. One of these conjectures is supported by an asymptotic result.

In this paper we study the following problem.

Discrete partitioning problem (DPP). Let $\mathbb{F}_q$ Pn denote the n-dimensional finite projective space over $\mathbb{F}_q$ . For positive integer k ⩽ n, let {Ai }i = 1 N be a partition of ( $\mathbb{F}_q$ Pn )k such that:

1. (1) for all i ⩽ N, Ai = ∏ j=1 k Aj i (partition into product sets),

2. (2) for all i ⩽ N, there is a (k − 1)-dimensional subspace Li ⊆ $\mathbb{F}_q$ Pn such that Ai ⊆ (Li) k.

DPP arises in an approach that we propose for proving lower bounds for the query complexity of generating random points from convex bodies. It is also related to other partitioning problems in combinatorics and complexity theory. We conjecture an asymptotically optimal partition for DPP and show that it is optimal in two cases: when the dimension is low (k = n = 2) and when the factors of the parts are structured, namely factors of a part are close to being a subspace. These structured partitions arise naturally as partitions induced by query algorithms. Our problem does not seem to be directly amenable to previous techniques for partitioning lower bounds such as rank arguments, although rank arguments do lie at the core of our techniques.

Robots running on water have attracted the attention of researchers in the last decades as an alternative to conventional aquatic propulsion mechanisms. Up to now, a large scale robot capable of running on water has not been realized. Bouncing on water is a prerequisite for running on water. For this reason, the development of a water bouncing robot represents a necessary first step. The paper presents the model of a 2-degree-of-freedom water bouncing robot inspired by the pogo-stick, a device for jumping off the ground in a standing position. An analytical model of the impact force between “robot's foot” and water is provided for both water-entry and water-exit phases. Such a model has been integrated in a dynamic simulation of whole robot. The model represents a useful and general framework to gain an insight into the parameters that characterize the efficiency of robot.

This paper proposes a modular caterpillar climbing robot using spines as the attaching tools. To improve the reliability of the spines' engagement and disengagement, this paper discusses the reasonable trajectory of the spine and designs a driving mechanism of the spine based on the compliant mechanism theory. Then some compliant modules are designed and realized to build the caterpillar climbing robot. A climbing gait is designed to avoid collisions between the spines and the wall, and allows the robot to climb on a stucco-like wall with a 72○ incline. The real tests reveal that the deformation of the compliant toes reduces the sliding forces between the spines and the wall, and improve the climbing action obviously.

Exoskeleton robots, which can be worn on human limbs to improve or to rehabilitate their function, are currently of great importance. When these robots are used in rehabilitation, one aspect that must be fulfilled is their capacity to adapt to different patients without significantly varying their performance. This paper describes the application of a relatively new control technique called virtual decomposition control (VDC) to a seven degrees-of-freedom (DOF) exoskeleton robot arm, named ETS-MARSE. The VDC approach mainly involves decomposing complex systems into subsystems, and using the resulting simpler dynamics to conduct control computation, while strictly ensuring global stability and having the subsystem dynamics interactions rigorously managed and maintained by means of virtual power flow. This approach is used to deal with different masses, joint stiffness and biomechanical variations of diverse subjects, allowing the control technique to naturally adapt to the variances involved and to maintain a successful control task. The results obtained in real time on a 7DOF exoskeleton robot arm show the effectiveness of the approach.

Given a graph G, let Q(G) denote the collection of all independent (edge-free) sets of vertices in G. We consider the problem of determining the size of a largest antichain in Q(G). When G is the edgeless graph, this problem is resolved by Sperner's theorem. In this paper, we focus on the case where G is the path of length n − 1, proving that the size of a maximal antichain is of the same order as the size of a largest layer of Q(G).

A continuum manipulator, such as a multisection trunk/tentacle robot, performs manipulation tasks by continuously deforming into different concave shapes. While such a robot is promising for manipulating a wide range of objects in less-structured and cluttered environments, it poses a greater challenge to collision detection than conventional, articulated manipulators. Existing collision detection algorithms are built upon intersection checking between convex primitives, such as between two convex polygons or polyhedra, with the assumption that both the manipulator and the objects in the environment are modeled in terms of those primitives, for example, as polygonal meshes. However, to approximate a continuum manipulator with a polygonal mesh requires a fine mesh because of its concavity, and each time the manipulator changes its configuration by deforming its shape, the mesh has to be updated for the new configuration. This makes mesh-based collision detection involving such a robot much more computationally expensive than that involving an articulated manipulator with rigid links.

Hence, we introduce an efficient algorithm for Collision Detection between a Continuum Manipulator (CD-CoM) and its environment based on analytical intersection checking with nonconvex primitives. Our algorithm applies to the exact model of any continuum manipulator consisting of multiple uniform-curvature sections of toroidal and (sometimes) cylindrical shapes as well as more general continuum manipulators whose sections can be approximated by toroidal and cylindrical primitives. Our test results show that using this algorithm is both more accurate and efficient in time and space to detect collisions than approximating a continuum manipulator as a polygonal mesh. Moreover, the CD-CoM algorithm also provides the minimum distance information between the continuum manipulator and objects when there is no collision. Such an efficient algorithm is essential for path/trajectory planning of continuum manipulators in real-time.

We address the problem of unsupervised and semi-supervised SMS (Short Message Service) text message SPAM detection. We develop a content-based Bayesian classification approach which is a modest extension of the technique discussed by Resnik and Hardisty in 2010. The approach assumes that the bodies of the SMS messages arise from a probabilistic generative model and estimates the model parameters by Gibbs sampling using an unlabeled, or partially labeled, SMS training message corpus. The approach classifies new SMS messages as SPAM or HAM (non-SPAM) by zero-thresholding their logit estimates. We tested the approach on a publicly available SMS corpora collected from the UK. Used in semi-supervised fashion, the approach clearly outperformed a competing algorithm, Semi-Boost. Used in unsupervised fashion, the approach outperformed a fully supervised classifier, an SVM (Support Vector Machine), when the number of training messages used by the SVM was small and performed comparably otherwise. We believe the approach works well and is a useful tool for SMS SPAM detection.