Table of contents

A base parameter set which is defined to be a minimum set of inertial parameters that can determine dynamic model uniquely is shown for Torque-unit Manipulator (TUM) which has been proposed as a new design concept of manipulator. The elements of the base parameter set are also the parameters that can be identified independently from motion data and input data, i.e., measured values. The base parameters play very important role for dynamic modelling of manipulators such as model based control and simulation of the manipulator motion. The base parameters are given completely in closed from of linear combinations of the link inertial parameters. Also, a control strategy for all state variables of TUM is given by using the base parameters.

This study aims at realizing a 3-D dynamic bipedal walking using two oscillators of a CPG approach based on its body dynamics. We have developed a 3-D biped that comprises flat feet with force sensors, ankle joints composed of ball joints surrounded by coil springs, telescopic knees, and active hip joints using a direct drive (DD) motor. We introduced the Owaki-Ishiguro method called 'TEGOTAE based approach' as ground contact information in the phase oscillator to the knee joint, and we achieved 3-D dynamic bipedal gait using RW06 only by the knee oscillation based on the phase oscillator. The bipedal walking was excited only by the knee oscillation, therefore, the gait was strongly affected by the body dynamics. This means that the gait might be affected strongly by disturbances, because passive dynamic walking, which achieved only by the body dynamics and interaction to environment, is not robust against such disturbances. In this study, therefore, we conduct some experimental tests to elucidate adaptability against ground variations.

Pattern recognition deals with obtaining and processing certain data on objects in the real world aimed at characterizing their common properties and classifying them with respect to these properties into classes. This paper deals with a method of pattern recognition with respect to the basic position of images. Factor analysis is used for classification. Factor analysis is a special statistical method using the same features and pattern classes as in discriminant analysis. The m dimensional vector is an input parameter. The method can classify into n groups of patterns. Pattern recognition can work in real time.

In these days, various control systems for robot arms using surface myoelectric signals have been developed. Abundant pattern recognition techniques have been proposed to predict human motion intent based on these signals. However, it may become burdensome for users to train voluntary control of myoelectric signals with these systems. In this study, we are seeking to develop schemes to evoke surface myoelectric signals and facilitate skill acquisition of robot arm manipulation. In this paper, we construct a simple 1-link robot arm which is controlled by estimating the wrist motion from the surface myoelectric signals on the forearm. We make several training experiments for skill acquisition of robot arm manipulation with and without physical constraints of the wrist, or with and without mechanical vibration stimulation. Then, we investigate the differences in facilitation effects of skill acquisition comparing with the results from these training experiments.

A dual mode optical measurement sensor was developed to measure free form surfaces and detects cracks revealed with liquid penetrant test. The fusion of a multi-line laser triangulation sensor with texture images, acquired by the sensor, allows the detection of the crack and the calculation of position and orientation for proper positioning and alignment of a friction stir welding head for crack repair. In order to test the proposed procedure, the sensor was mounted on a motorized linear stage to measure a simulated crack on a pipe section. Results show that the crack can be detected and the 3D position and orientation can be defined on the reconstructed surface for crack repair procedures.

We are developing a small unmanned ground vehicle to support rescue missions by exploring sediment-related disaster areas. To simplify the vehicle operation, we employ a laser pointer as guidance system. In this paper, we describe a method to detect the laser-pointer spot under sunlight and a fuzzy learning method for guiding the vehicle towards the corresponding target position. To verify the spot detection, we performed experiments in laboratory emulating sunlight conditions, whereas to validate the guidance method, we developed a fuzzy control system whose input-variable ranges were determined from preliminary experiments and whose outputs include turning, backward, and forward motions of the vehicle. Likewise, experimental results confirm the effectiveness of the proposed guidance method.

In this paper, we address the problem of localization of swimming robots inside liquid storage tanks. Our proposed localization technique uses two or more proximity sensors with one or more angular orientation sensors while exploiting the cylindrical geometry of tanks. For the planar case, we study the map of the sensor error to the robot position error using a Monte Carlo error optimization analysis. We study the case of two, three and four proximity sensors while varying the relative orientation placement of these sensors. We conclude that the use of one orientation sensor, and four proximity sensors spaced 45 degrees apart give the least error in computing the robot position inside the tank from sensor measurements.

An architecture of human-robot navigation system, based on ultra-wideband positioning, twofold ultrasonic sensors for heading, and an augmented reality smart-glasses interface, is presented. The position is obtained by a trilateration algorithm based on Extended Kalman Filter, and the heading by fusing the ultra-wideband position with the phase difference measured by the ultrasonic system. The phase difference received at the ultrasonic sensor is extract using the three parameter sine fitting algorithm. For this application in the CERN tunnel of the Large Hadron Collider, the inspection robot precedes the human during the navigation in the harsh environment, and collects temperature, oxygen percentage, and radiation level. The environment measurements are displayed by the smart-glasses at the operator, and in case of a dangerous condition, the operator is warned by the augmented reality interface. The navigation and monitoring system allows to maintain safety the relative human-robot position. Preliminary simulation results of the positioning and heading system are discussed to validate the main idea.

During the Humanitarian-demining actions, teleoperation of sensors or multi-sensor heads can enhance-detection process by allowing more precise scanning, which is use-ful for the optimization of the signal processing algorithms. This chapter summarizes the technologies and experiences developed during 16 years through national and/or European-funded projects, illustrated by some contributions of our own laboratory, located at the Royal Military Academy of Brussels, focusing on the detection of unex-ploded devices and the implementation of mobile robotics systems on minefields.