Reusing Primitive and Acquired Motion Knowledge for Gait Generation of a Six-legged Robot Using Genetic Programming

There has been growing interest in motion planning problems for mobile robots. In this field, the main research is to generate a motion for a specific robot and task without previously acquired motions. However it is too wasteful not to use hard-earned acquired motions for other tasks. Here, we focus on a mechanism of reusing acquired motion knowledge and study a motion planning system able to generate and reuse motion knowledge. In this paper, we adopt a tree-based representation for expressing knowledge of motion, and propose a hierarchical knowledge for realizing a reuse mechanism. We construct a motion planning system using hierarchical knowledge as motion knowledge and using genetic programming as a learning method. We apply a proposed method for the gait generation task of a six-legged locomotion robot and show its availability with computer simulation.     

Consistency property of extended least-squares parameter estimation for stochastic diffusion equation

The extended least-squares parameter estimate for stochastic heat diffusion equations is considered. The unknown parameter is a heat diffusion coefficient which is a function of a spatial variable. Almost sure convergence for the estimated parameter is proved. A numerical example is demonstrated for supporting the theoretical results developed here.     

Sensor Fusion System Using Recurrent Fuzzy Inference

In robotic and manufacturing systems, it is difficult to measure the state of systems accurately because of many uncertain factors and noise, and it is very important to estimate the state of systems. We must measure the phenomena of systems by multiple sensors and estimate the state of systems by acquiring information of sensors. However, we can not acquire all of sensor information synchronically, because each sensor has particular sensor information and measuring time. For estimating the state of systems by multiple sensors, a multi-sensor fusion system fusing various sensory information is needed. In this paper, we propose a Recurrent Fuzzy Inference (RFI) with recurrent inputs and apply it to a multi-sensor fusion system for estimating the state of systems. The membership functions of RFI are expressed by Radial Basis Function (RBF) with insensitive ranges. The shape of the membership functions can be adjusted by a learning algorithm. The learning algorithm is based on the steepest descent method and incremental learning which can add new fuzzy rules. The effectiveness of the multi-sensor fusion system using RFI will be shown through a numerical experiment of moving robot and estimation of surface roughness in grinding process.     

Partial redundancy elimination for access expressions by speculative code motion

We present a new memory access optimization for Java to perform aggressive code motion for speculatively optimizing memory accesses by applying partial redundancy elimination (PRE) techniques. First, to reduce as many barriers as possible and to enhance code motion, we perform alias analysis to identify all the regions in which each object reference is not aliased. Secondly, we find all the possible barriers. Finally, we perform code motions in three steps. For the first step, we apply a non‐speculative PRE algorithm to move load instructions and their following instructions in the backwards direction of the control flow graph. For the second step, we apply a speculative PRE algorithm to move some of them aggressively before the conditional branches. For the third step, we apply our modified version of a non‐speculative PRE algorithm to move store instructions in the forward direction of the control flow graph and to even move some of them after the merge points. We implemented our new algorithm in our production‐level Java just‐in‐time compiler. Our experimental results show that our speculative algorithm improves the average (maximum) performance by 13.1% (90.7%) for jBYTEmark and 1.4% (4.4%) for SPECjvm98 over the fastest algorithm previously described, while it increases the average (maximum) compilation time by 0.9% (2.9%) for both benchmark suites. Copyright © 2004 John Wiley & Sons, Ltd.     

Calculations from texture of earing in deep drawing for FCC metal sheets

The present study aims to calculate the height at each peripheral position of a cup drawn from polycrystalline sheet using texture data. In the analytical treatment the polycrystalline sheet is simplified to an aggregation of many single crystals with various orientations, and the texture is represented by a three-dimensional crystallite orientation distribution function. The ear is calculated crystallographically using the orientation distribution function as a volume fraction of a certain oriented crystal. In the experiment aluminium, Al-Mg alloy and copper sheets which are treated under various conditions of cold rolling and heat treatment are used. The average textures over the thicknesses of the sheets are measured by the Schulz reflection method. The calculated ears based on the measured textures are compared with the experimental ears for each material. The results show that all the principal features of the ears of drawn cups are predicted satisfactorily by the calculation.     

Dynamical coherence patterns in neural field model at criticality

Phase synchronization is a mechanism that plays a crucial role in information processing in the brain, and coherence is one of the factors used to evaluate the pairwise degree of phase synchronization. Coherence is also an important measure for examining brain functions because it implies communication and cooperation among neurons. In this work, we study the coherence patterns of spontaneous activity in a neural field model at criticality where a second-order phase transition occurs with special properties that differentiate it from other regions. The results are summarized as follows. First, in high-frequency bands, the system outside the critical region is unable to communicate efficiently via phase synchronization. Second, the dynamical coherence patterns at the criticality show switching between high and low coherence states. Finally, we found that in a very brief period, there is high broadband coherence between some pairs of spatial points. This phenomenon can be observed only in the critical region.     

Preparation and characterization of nanoporous films derived from alicyclic copolyimides having pendent poly(propyleneglycol) groups

Nanoporous films were prepared with alicyclic copolyimides (coPIs) having polypropylene glycol (PPG) side chains by way of spontaneous phase separation in the film forming process and the subsequent thermal degradation of PPG moieties. PIs having various content (6.5, 11.9, 26.3, 52.7 wt%) and different length (M_w = 1.2 × 10³ and 2.4 × 10³) of PPG side chains were examined in order to clarify the relationship between chemical structure and pore characteristics. Nanopores were formed by heating the coPI films at 200 °C for 9 h under slightly reduced pressure. The size and the number of the pores observed by SEM varied depending on the content and molecular weight of PPG moieties. In many cases, the pore size was larger than those of the reported values for related aromatic copolyimide films. The dielectric constant of the nanoporous films ranged from 2.52 to 3.38.     

A robust implicit state observer for multiple-input multiple-output uncertain systems

A new mathematical method of estimating the state for uncertain continuous-time multiple-input multiple-output minimum-phase (with respect to the relation between the disturbance and the output) dynamical systems with arbitrarily relative degrees is presented. For the systems with relative degree one, the state observer which is perfectly robust to disturbances is constructed by using only the input and output information. The estimating error of the state decays to zero exponentially. For the systems with higher relative degrees, the state observer is formulated for the first time, where the input and output information, and the a priori information of the upper and lower bounds of the disturbances are employed. In this case, the estimating error of the state can be controlled to be as small as is needed by the design parameters. The attraction of the proposed observers lies in their robustness to disturbances and insensitivity to the high-frequency noises accompanying the inputs. A design example and its simulation results are presented to illustrate the proposed algorithm.