This paper introduces a new concept of multi-locomotion robot inspired by an animal. The robot, &#x2018;Gorilla Robot II&#x2019;, can select the appropriate locomotion (from biped locomotion, quadruped locomotion and brachiation) according to an environment or task. We consider &#x2018;brachiation&#x2019; to be one of the most dynamic of animal motions. To develop a brachiation controller, architecture of the hierarchical behaviour-based controller, which consists of behaviour controllers and behaviour coordinators, was used. To achieve better brachiation, an enhanced learning method for motion control, adjusting the timing of the behaviour coordination, is proposed. Finally, it is shown that the developed robot successfully performs two types of brachiation and continuous locomotion.

Hideki Kajima

Yasuhisa Hasegawa

Toshio Fukuda

Learning Algorithm for a Brachiating Robot

A model of the human arm was developed to study coordination of multi-joint movement in the vertical plane. The arm was represented as a two-segment, two-degree of freedom dynamic system with net muscle torques acting at the shoulder and elbow. Kinematic data were collected from a subject who performed unrestrained vertical movements with only the initial and final hand elevations prescribed. Movements were performed with and without a hand-held load. The method of computed torques was implemented to obtain net muscle torques, which enables position and velocity feedback to be used to estimate joint angular accelerations that produce a more stable simulation of arm movement. The model simulation was then used to calculate the contributions of the net muscle torques, gravitational torques and velocity-interaction torques to the angular accelerations of the shoulder and elbow and also to the vertical acceleration of the hand. The net muscle torques and gravity were the prime movers of the arm. The velocity-dependent effects contributed little to the dynamics of arm movement and were, in fact, insignificant when the hand was loaded. The muscles of the shoulder and elbow acted synergistically to elevate the arm in the sagittal plane. The hand was accelerated upward by the elbow first, until the point of maximum elbow flexion, after which the shoulder became the prime mover. Gravity acted consistently to accelerate the hand downward. Coordination was notably invariant to changes in external load. Some compensation for load was observed in the control, and these differences were attributed mainly to an increase in system inertia.

Ajay Seth

John J. McPhee

Marcus G. Pandy

Multi-Joint Coordination of Vertical Arm Movement

A high-efficiency, easy-to-use input device is not only important for data entry but also for human-computer interaction. To date, there has been little research on input devices with many degrees of freedom (DOF) that can be used by the handicapped. This paper presents the development of an electromyography (EMG)-based input device for forearm amputees. To overcome the difficulties in analysing EMG and realising high DOF from biosignals, the following were integrated: (1) an online learning method to cope with nonlinearity and the individual difference of EMG signals; (2) a smoothing algorithm to deal with noisy recognition results and transition states; and (3) a modified Huffman coding algorithm to generate the optimal code, taking expected error and input efficiency into consideration. Experiments showed the validity of the system and the possibility for development of a quiet, free-posture (no postural restriction) input device with many DOF for users, including forearm amputees.

Wenwei Yu

Ryu Kato

Fukuda Fabio

Hiroshi Yokoi

Yukinori Kakazu

An EMG Keyboard for Forearm Amputees

This paper presents a methodology we have developed and used to implement an artificial binocular vision system capable of emulating the vergence of eye movements. This methodology involves using weightless neural networks (WNNs) as building blocks of artificial vision systems. Using the proposed methodology, we have designed several architectures of WNN-based artificial vision systems, in which images captured by virtual cameras are used for controlling the position of the &#x2018;foveae&#x2019; of these cameras (high-resolution region of the images captured). Our best architecture is able to control the foveae vergence movements with average error of only 3.58 image pixels, which is equivalent to an angular error of approximately 0.629&#xb0;.

Karin S. Komati

Alberto F. De Souza

Using Weightless Neural Networks for Vergence Control in an Artificial Vision System

This paper presents a model for the simulation of pedestrian dynamics inspired by the behaviour of ants in ant trails. Ants communicate by producing a pheromone that can be smelled by other ants. In this model, pedestrians produce a virtual pheromone that influences the motion of others. In this way all interactions are strictly local, and so even large crowds can be simulated very efficiently. Nevertheless, the model is able to reproduce the collective effects observed empirically, eg the formation of lanes in counterflow. As an application, we reproduce a surprising result found in experiments of evacuation from an aircraft.

Andreas Schadschneider

Ansgar Kirchner

Katsuhiro Nishinari

From Ant Trails to Pedestrian Dynamics

DNA sequence analysis is of great significance for increasing our understanding of genomic functions. An important task facing us is the exploration of hidden structural information stored in the DNA sequence. This paper introduces a DNA structure-based adaptive wavelet transform (WT) &#x2013; the bionic wavelet transform (BWT) &#x2013; for DNA sequence analysis. The symbolic DNA sequence can be separated into four channels of indicator sequences. An adaptive symbol-to-number mapping, determined from the structural feature of the DNA sequence, was introduced into WT. It can adjust the weight value of each channel to maximise the useful energy distribution of the whole BWT output. The performance of the proposed BWT was examined by analysing synthetic and real DNA sequences. Results show that BWT performs better than traditional WT in presenting greater energy distribution. This new BWT method should be useful for the detection of the latent structural features in future DNA sequence analysis.

Fei Chen

Yuan-Ting Zhang

A DNA Structure-Based Bionic Wavelet Transform and Its Application to DNA Sequence Analysis

Rene V. Mayorga

Editorial Foreword

About this journal

Applied Bionics and Biomechanics publishes original research articles as well as review articles that seek to understand the mechanics of biological systems, or that use the functions of living organisms as inspiration for the design of new devices.

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Chief Editor, Professor Qiguo Rong, is the Vice Chair of the Department of Mechanics and Engineering Science at Peking University, China. His research focuses on the biomechanical behaviors of musculoskeletal systems.

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Applied Bionics and Biomechanics - Table of contents 2003

Applied Bionics and Biomechanics | Hindawi

title

Applied Bionics and Biomechanics publishes original research articles as well as review articles that seek to understand the mechanics of biological systems, or that use the functions of living organisms as inspiration for the design of new devices.

Applied Bionics and Biomechanics