Pivoting based manipulation by a humanoid robot

In this paper we address whole-body manipulation of bulky objects by a humanoid robot. We adopt a “pivoting” manipulation method that allows the humanoid to displace an object without lifting, but by the support of the ground contact. First, the small-time controllability of pivoting is demonstrated. On its basis, an algorithm for collision-free pivoting motion planning is established taking into account the naturalness of motion as nonholonomic constraints. Finally, we present a whole-body motion generation method by a humanoid robot, which is verified by experiments.     

Cubic centimeter robot based on inertial stick–slip driving

In order to achieve the nano-operation in a limited space, a precision motion platform with a cubic centimeter volume based on the principle of inertial stick–slip driving is proposed in this paper. The mechanical structure and the operating principle are discussed. Kinematic models are used to analyze the performance of the prototype. To investigate the working performance of the prototype, a series of experiments are carried out. Experimental results show that the displacement outputs is related to the parameters of the electrical signal. The maximum moving speed of the platform reaches 13.1 mm/s when the driving frequency is 3.1 kHz. The maximum single step displacement reaches 4.8 μm. Through proper driving voltage and frequency, the proposed prototype can produce a satisfactory velocity.

     

Structure-based color learning on a mobile robot under changing illumination

A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomous robots rely on sensory information. Despite the potential richness of visual information from on-board cameras, many mobile robots continue to rely on non-visual sensors such as tactile sensors, sonar, and laser. This preference for relatively low-fidelity sensors can be attributed to, among other things, the characteristic requirement of real-time operation under limited computational resources. Illumination changes pose another big challenge. For true extended autonomy, an agent must be able to recognize for itself when to abandon its current model in favor of learning a new one; and how to learn in its current situation. We describe a self-contained vision system that works on-board a vision-based autonomous robot under varying illumination conditions. First, we present a baseline system capable of color segmentation and object recognition within the computational and memory constraints of the robot. This relies on manually labeled data and operates under constant and reasonably uniform illumination conditions. We then relax these limitations by introducing algorithms for (i) Autonomous planned color learning, where the robot uses the knowledge of its environment (position, size and shape of objects) to automatically generate a suitable motion sequence and learn the desired colors, and (ii) Illumination change detection and adaptation, where the robot recognizes for itself when the illumination conditions have changed sufficiently to warrant revising its knowledge of colors. Our algorithms are fully implemented and tested on the Sony ERS-7 Aibo robots.

Safe human–robot interaction based on dynamic sphere-swept line bounding volumes

This paper presents a geometric representation for human operators and robotic manipulators, which cooperate in the development of flexible tasks. The main goal of this representation is the implementation of real-time proximity queries, which are used by safety strategies for avoiding dangerous collisions between humans and robotic manipulators. This representation is composed of a set of bounding volumes based on swept-sphere line primitives, which encapsulate their links more precisely than previous sphere-based models. The radius of each bounding volume does not only represent the size of the encapsulated link, but it also includes an estimation of its motion. The radii of these dynamic bounding volumes are obtained from an algorithm which computes the linear velocity of each link. This algorithm has been implemented for the development of a safety strategy in a real human–robot interaction task.     

Gesture recognition based human–robot interactive control for robot soccer

Microsystem Technologies - This paper proposes an interaction method in human gestures for controlling robot play soccer. It aims to design a human–robot interactive control scheme let a...     

Optical spatial image processor based on aliasing of?pseudo-periodic sampling

In this paper, we present a new configuration for a real-time spatial image processor that is based upon a spatially incoherent imaging setup in which a grating is attached to the object plane. By proper adjusting of the magnification of the imaging system to the spatial period of the grating and the sampling grid of the camera, the aliasing effect along the non-uniform digital sampling realizes a tunable spectral distribution that is applied over the spectrum of the object. Preliminary numerical demonstration of the operation principle is provided.     

Control of bidirectional physical human–robot interaction based on the human intention

This paper presents a control strategy for human–robot interaction with physical contact, recognizing the human intention to control the movement of a non-holonomic mobile robot. The human intention is modeled by mechanical impedance, sensing the human-desired force intensity and the human-desired force direction to guide the robot through unstructured environments. Robot dynamics is included to improve the interaction performance. Stability analysis of the proposed control system is proved by using Lyapunov theory. Real experiments of the human–robot interaction show the performance of the proposed controllers.     

Comment on “Balance recovery control for biped robot based on reaction null space method”

We hereby acknowledge that the published paper on our journal, “Balance recovery control for biped robot based on reaction null space method” by Baoping Wang, Renxi Hu, Jinming Zhang and Chuangfeng Huai, is a plagiarism of “Balance control of a humanoid robot based on the reaction null space method” by Akinori Nishio, Kentaro Takahashi and Dragomir N. Nenchev. We withdrew the plagiarized paper from the Springer website, and sent a formal notification letter to each author’s affiliation. Any submission from Baoping Wang, Renxi Hu, Jinming Zhang or Chuangfeng Huai will not be accepted in three years from now on. The above comment and this notification are published not only in this printed version, but also on the Springer website and our journal website. We have used plagiarism scanning software and started the online detection of plagiarism in the received papers in September 2010 for screening the plagiarized submission.     

Recursive formulations for multibody systems with frictional joints based on the interaction between bodies

In practice, the clearances of joints in a great number of mechanical systems are well under control. In these cases, some of the existing methods become unpractical because of the little differences in the order of magnitude between relative movements and computational errors. Assuming that the effects of impacts are negligible, we proved that both locations and forces of contacts in joints can be fully determined by parts of joint reaction forces. Based on this fact, a method particularly suited for multibody systems possessing frictional joints with tiny clearances is presented. In order to improve the efficiency of computation, recursive formulations are proposed based on the interactions between bodies. The proposed recursive formulations can improve the computation of joint reaction forces. With the methodology presented in this paper, not only the motion of bodies in a multibody system but also the details about the contacts in joints, such as forces of contacts and locations of contact points, can be obtained. Even with the assumption of impact free, the instants of possible impacts can be detected without relying upon any ambiguous parameters, as indicated by numerical examples in this paper.     

Spectral–spatial co-clustering of hyperspectral image data based on bipartite graph

The high dimensionality of hyperspectral images are usually coupled with limited data available, which degenerates the performances of clustering techniques based only on pixel spectral. To improve the performances of clustering, incorporation of spectral and spatial is needed. As an attempt in this direction, in this paper, we propose an unsupervised co-clustering framework to address both the pixel spectral and spatial constraints, in which the relationship among pixels is formulated using an undirected bipartite graph. The optimal partitions are obtained by spectral clustering on the bipartite graph. Experiments on four hyperspectral data sets are performed to evaluate the effectiveness of the proposed framework. Results also show our method achieves similar or better performance when compared to the other clustering methods.     

A geometrically exact beam element based on the absolute nodal coordinate formulation

In this study, Reissner’s classical nonlinear rod formulation, as implemented by Simo and Vu-Quoc by means of the large rotation vector approach, is implemented into the framework of the absolute nodal coordinate formulation. The implementation is accomplished in the planar case accounting for coupled axial, bending, and shear deformation. By employing the virtual work of elastic forces similarly to Simo and Vu-Quoc in the absolute nodal coordinate formulation, the numerical results of the formulation are identical to those of the large rotation vector formulation. It is noteworthy, however, that the material definition in the absolute nodal coordinate formulation can differ from the material definition used in Reissner’s beam formulation. Based on an analytical eigenvalue analysis, it turns out that the high frequencies of cross section deformation modes in the absolute nodal coordinate formulation are only slightly higher than frequencies of common shear modes, which are present in the classical large rotation vector formulation of Simo and Vu-Quoc, as well. Thus, previous claims that the absolute nodal coordinate formulation is inefficient or would lead to ill-conditioned finite element matrices, as compared to classical approaches, could be refuted. In the introduced beam element, locking is prevented by means of reduced integration of certain parts of the elastic forces. Several classical large deformation static and dynamic examples as well as an eigenvalue analysis document the equivalence of classical nonlinear rod theories and the absolute nodal coordinate formulation for the case of appropriate material definitions. The results also agree highly with those computed in commercial finite element codes.     

A two-step method for kinematic parameters calibration based on complete pose measurement—Verification on a heavy-duty robot

The poor pose accuracy of industrial robots restricts their further application in aviation manufacturing. Kinematic calibration based on position errors is a traditional method to improve robot accuracy. However, due to the difference between length errors and angle errors in the order of magnitude, it is difficult to accurately calibrate these geometric parameters together. In this paper, a two-step method for robot kinematic parameters calibration and a novel method for position and orientation measurement are proposed and combined to identify these two kinds of errors respectively. The redundant parameter errors that affect the identification are also analyzed and eliminated to further improve the accuracy of this two-step method. Taking the Levenberg-Marquardt algorithm as the underlying algorithm, simulation results indicate that the proposed two-step calibration method has faster iteration speed and higher identification accuracy than the traditional one. On this basis, the calibration and measurement methods proposed in this paper are verified on a heavy-duty robot used for fiber placement. Experimental results show that the mean absolute position error decreases from 0.9906 mm to 0.3703 mm after calibration by the proposed two-step calibration method with redundancy elimination. The absolute position accuracy has increased by 41.81% compared with the traditional method based on position errors only and 14.97% compared with the two-step calibration method without redundancy elimination. At the same time, the orientation errors after calibration are not more than 0.1485°, and the average of absolute errors is 0.0447.     

One step at a time: animating virtual characters based on foot placement

Especially in a constrained virtual environment, precise control of foot placement during character locomotion is crucial to avoid collisions and to ensure a natural locomotion. In this paper, we present an extension of the step space: a novel technique for generating animations of a character walking over a set of desired foot steps in real time. We use an efficient greedy nearest-neighbor approach and warp the resulting animation so that it adheres to both spatial and temporal constraints. We will show that our technique can generate realistic locomotion animations over an input path very efficiently even though we impose many constraints on the animation. We also present a simple footstep planning technique that automatically plans regular stepping and sidestepping based on an input path with clearance information generated by a path planner.     

Dynamic slicing of lazy functional programs based on redex trails

Tracing computations is a widely used methodology for program debugging. Lazy languages, however, pose new demands on tracing techniques because following the actual trace of a computation is generally useless. Typically, tracers for lazy languages rely on the construction of a redex trail, a graph that stores the reductions performed in a computation. While tracing provides a significant help for locating bugs, the task still remains complex. A well-known debugging technique for imperative programs is based on dynamic slicing, a method for finding the program statements that influence the computation of a value for a specific program input. In this work, we introduce a novel technique for dynamic slicing in first-order lazy functional languages. Rather than starting from scratch, our technique relies on (a slight extension of) redex trails. We provide a notion of dynamic slice and introduce a method to compute it from the redex trail of a computation. We also sketch the extension of our technique to deal with a functional logic language. A clear advantage of our proposal is that one can enhance existing tracers with slicing capabilities with a modest implementation effort, since the same data structure (the redex trail) can be used for both tracing and slicing.     

High-speed and energy-efficient biped locomotion based on Virtual Slope Walking

In our previous work, we have presented results on Virtual Slope Walking, that is when a robot walks on level ground down a virtual slope by leg length modulation, based on the potential energy restoration in Passive Dynamic Walking. In this paper, we introduce the model of Virtual Slope Walking with Trajectory Leg Extension (TLE) and equivalent Instantaneous Leg Extension (ILE) under the Equivalent Definition. The analytic solution of the model’s fixed point is obtained to analyze the essence of Virtual Slope Walking. We systematically investigate the characteristics and illustrate the effect of model parameters: the length-shortening ratio β, the equivalent extension angle q^*_II\theta^{*}_{\mathrm{II}}, and the inter-leg angle ϕ ₀. We examine the energy efficiency and walking speed to demonstrate that Virtual Slope Walking is effective in generating high speed and energy-efficient walking. The high energy efficiency of the proposed model is theoretically confirmed. And the fast walking is validated by the experiments of a planar biped robot Stepper-2D, which achieves a sufficiently fast relative speed of 4.48 leg/s.     

Parallelism of iterative CT reconstruction based on local reconstruction algorithm

An iterative algorithm is suited to reconstruct CT images from noisy or truncated projection data. However, as a disadvantage, the algorithm requires significant computational time. Although a parallel technique can be used to reduce the computational time, a large amount of communication overhead becomes an obstacle to its performance (Li et al. in J. X-Ray Sci. Technol. 13:1–10, 2005). To overcome this problem, we proposed an innovative parallel method based on the local iterative CT reconstruction algorithm (Wang et al. in Scanning 18:582–588, 1996 and IEEE Trans. Med. Imaging 15(5):657–664, 1996). The object to be reconstructed is partitioned into a number of subregions and assigned to different processing elements (PEs). Within each PE, local iterative reconstruction is performed to recover the subregion. Several numerical experiments were conducted on a high performance computing cluster. And the FORBILD head phantom (Lauritsch and Bruder ) was used as benchmark to measure the parallel performance. The experimental results showed that the proposed parallel algorithm significantly reduces the reconstruction time, hence achieving a high speedup and efficiency.

Sequential multi-criteria feature selection algorithm based on agent genetic algorithm

A multi-criteria feature selection method-sequential multi-criteria feature selection algorithm (SMCFS) has been proposed for the applications with high precision and low time cost. By combining the consistency and otherness of different evaluation criteria, the SMCFS adopts more than one evaluation criteria sequentially to improve the efficiency of feature selection. With one novel agent genetic algorithm (chain-like agent GA), the SMCFS can obtain high precision of feature selection and low time cost that is similar as filter method with single evaluation criterion. Several groups of experiments are carried out for comparison to demonstrate the performance of SMCFS. SMCFS is compared with different feature selection methods using three datasets from UCI database. The experimental results show that the SMCFS can get low time cost and high precision of feature selection, and is very suitable for this kind of applications of feature selection.     

Single image 3D reconstruction based on control point grid

In order to construct 3D meshes from a single image quickly and intuitively, this paper presents a 3D reconstruction method based on control point grid. The key idea is to calculate the 2D control point grid of the target area and elevate each control point according to a parameterized 3D growing rule proposed from prior knowledge. First, the contour of the target object is divided into a major component and side components and the skeleton of each component is extracted. 2D control point grid is calculated combining the curvature and geometric feature of the contour and lifted into 3D space with corresponding height defined by parameter mapping. Finally, a complete 3D model is obtained after component combination and texturing. Experimental results show that this method can reasonably and efficiently recover the 3D shape of the target object while maintaining fine curvature and geometric features.     

Hyperspectral anomaly detection using spectral–spatial features based on the human visual system

ABSTRACT

Anomaly detection (AD) is one of the most attracting topics within the recent 10 years in hyperspectral imagery (HSI). The goal of the AD is to label the pixels with significant spectral or spatial differences to their neighbours, as targets. In this paper, we propose a method that uses both spectral and spatial information of HSI based on human visual system (HVS). By inspiring the retina and the visual cortex functionality, the multiscale multiresolution analysis is applied to some principal components of hyperspectral data, to extract features from different spatial levels of the image. Then the global and local relations between features are considered based on inspiring the visual attention mechanism and inferotemporal (IT) part of the visual cortex. The effects of the attention mechanism are implemented using the logarithmic function which well highlights, small variations in pixels’ grey levels in global features. Also, the maximum operation is used over the local features for imitating the function of IT. Finally, the information theory concept is used for generating the final detection map by weighting the global and local detection maps to obtain the final anomaly map. The result of the proposed method is compared with some state-of-the-art methods such as SSRAD, FLD, PCA, RX, KPCA, and AED for two well-known real hyperspectral data which are San Diego airport and Pavia city, and a synthetic hyperspectral data. The results demonstrate that the proposed method effectively improves the AD capabilities, such as enhancement of the detection rate, reducing the false alarm rate and the computation complexity.