A. Paulo Coimbra

Robot navigation and manipulation based on a predictive associative memory

Proposed in the 1980s, the Sparse Distributed Memory (SDM) is a model of an associative memory based on the properties of a high dimensional binary space. This model has received some attention from researchers of different areas and has been improved over time. However, a few problems have to be solved when using it in practice, due to the non-randomness characteristics of the actual data. We tested an SDM using different forms of encoding the information, and in two different domains: robot navigation and manipulation. Our results show that the performance of the SDM in the two domains is affected by the way the information is actually encoded, and may be improved by some small changes in the model.

ZMP trajectory reference for the sagittal plane control of a biped robot based on a human CoP and gait

This paper introduces two new important issues to be considered in the design of the zero moment point (ZMP) trajectory reference for the sagittal plane balance control of an autonomous walking biped robot with an human-like gait. ZMP trajectory reference generation is very important in the design and balance control of the walking of a biped robot. ZMP reference generation algorithms based on the linear inverted pendulum model (LIPM) and moving ZMP references in the swing phase have already been proposed with the ZMP trajectory during the swing phase being designed moving along a symmetric trajectory relative to the center of the foot. It was verified experimentally that in the human gait the ZMP trajectory moves along the foot in a way that it is shifted forward relative to its center. To take this into account a shift parameter is then proposed to move forward the XZMP trajectory reference during the swing phase. It was also verified experimentally that in the human gait the ZMP trajectory amplitude depends on the swing time. Its variation law has been determined experimentally and it was verified that this range decreases as the swing time increases, reducing to zero for a static gait. It is then proposed a parameter H to take into account this variation with the swing time of the gait. Six experiments were carried out for three different XZMP trajectory references. In order to evaluate and compare the performance of the biped robot using the three XZMP trajectory references two performance indexes are proposed.

SVR CONTROLLER FOR A BIPED ROBOT IN THE SAGITTAL PLANE WITH HUMAN-BASED ZMP TRAJECTORY REFERENCE AND GAIT

This paper introduces two new important issues to be considered in the design of the zero moment point (ZMP) trajectory of a biped robot. It was verified experimentally that in the human gait the ZMP trajectory moves along the foot in a way that it is shifted forward relative to its center. To take this into account a shift parameter is then proposed. It was also verified experimentally that in the human gait the ZMP trajectory amplitude depends on the swing time, reducing to zero for a static gait. It is then proposed a parameter to take into account this variation with the swing time of the gait. Six experiments were carried out for three different XZMP trajectory references. In order to evaluate and compare the performance of the biped robot using the three XZMP trajectory references two performance indexes are proposed. For the real-time balance control of this 8 link biped robot it was used an intelligent computing control technique, the Support Vector Regression (SVR). The control method uses the ZMP error and its variation as inputs and the output is the correction of the robots ankle and torso angles, necessary for the sagittal balance of the biped robot.

Thermal analysis of a ZnO surge arrester using the finite element approach

In the design stage of a metal oxide surge arrester, the heating and cooling simulation is particularly important since the temperature rise in the ZnO elements, caused by absorbing surge energy, can produce the phenomena of thermal runaway. In the present paper, the heating and cooling analysis of a ZnO surge arrester under different operating conditions is performed using CAD/CAE techniques. This analysis was performed taking into account the steady-state and the transient heat transfer phenomena. The results were obtained using CADdyTERM, a finite element software package developed by the authors. These computer programs allow to handle the complex geometry of the device as well as the highly nonlinear resistance of the metal oxide elements. Finally the results are discussed and some important and practical conclusions concerned with the heating and cooling of the surge arrester are pointed out.In the design stage of a metal oxide surge arrester, the heating and cooling simulation is particularly important since the temperature rise in the ZnO elements, caused by absorbing surge energy, can produce the phenomena of thermal runaway. In the present paper, the heating and cooling analysis of a ZnO surge arrester under different operating conditions is performed using CAD/CAE techniques. This analysis was performed taking into account the steady-state and the transient heat transfer phenomena. The results were obtained using CADdyTERM, a finite element software package developed by the authors. These computer programs allow to handle the complex geometry of the device as well as the highly nonlinear resistance of the metal oxide elements. Finally the results are discussed and some important and practical conclusions concerned with the heating and cooling of the surge arrester are pointed out.

Tuning a PD Controller Based on an SVR for the Control of a Biped Robot Subject to External Forces and Slope Variation

Real-time balance control of an eight-link biped robot using a zero moment point (ZMP) dynamic model is difficult to achieve due to the processing time of the corresponding equations. To overcome this limitation an intelligent computing technique based on Support Vector Regression (SVR) is developed and presented in this paper. To implement a PD controller the SVR uses the ZMP error relative to a reference and its variation as inputs, and the output is the correction of the angle of the robots torso, necessary for its sagittal balance. The SVR was trained based on simulation data generated using a PD controller. The initial values of the parameters of the PD controller were obtained by the second Ziegler-Nichols method. In order to evaluate the balance performance of the biped robot, three performance indexes are used. The ZMP is calculated by reading four force sensors placed under each of the robots feet. The gait implemented in this biped is similar to a human gait, which is acquired and adapted to the robots size. The main contribution of this paper is the fine-tuning of the ZMP controller based on the SVR. To implement and test this, the biped robot was subjected to external forces and slope variation. Some experiments are presented and the results show that the implemented gait combined with the correct tuning of the SVR controller is appropriate for use with this biped robot. The SVR controller runs at 0.2 ms, which is about 50 times faster than a corresponding first-order TSK neural-fuzzy network.

Intelligent robot navigation using view sequences and a sparse distributed memory

Different approaches have been tried to navigate robots, including those based on visual memories. The Sparse Distributed Memory (SDM) is a kind of associative memory based on the properties of high dimensional binary spaces. It exhibits characteristics such as tolerance to noise and incomplete data, ability to work with sequences and the possibility of one-shot learning. Those characteristics make it appealing to use for robot navigation. The approach presented in this work was to navigate a robot using sequences of visual memories stored into a SDM. The robot makes intelligent decisions, such as selecting only relevant images to store during path learning, adjusting memory parameters to the level of noise and inferring new paths from learnt trajectories. The method of encoding the information may influence the tolerance of the SDM to noise and saturation. The present paper reports novel results of the limits of the model under different typical navigation problems. An algorithm to build a topological map of the environment based on the visual memories is also described.

Low cost vision system for human gait acquisition and characterization

This paper presents a low cost system for human gait analysis. Two opposite-faced web cameras are used to acquire images of the walking of a person carrying a set of passive marks, where the color is chosen to contrast with the ambient dominant color. It is also used a treadmill with passive marks, where the user walks at different speeds. The acquired trajectories of the marks are used to determine body joint angles and other 3D crossed angles, obtained by both opposite sides from video images processing. With this low cost measurement system the analysis and reconstruction of human gait can be done with a mean error of 2 degrees, becoming a good alternative to more expensive systems to be used in human gait characterization. The system can be used to detect human gait pathologies and to accomplish physical rehabilitation.

Investment risk analysis for photovoltaic power plant in the free contracting environment

This research work presents a methodology for investment risk analysis in a photovoltaic power plant. Stochastic modeling are developed for the variables solar irradiance, photovoltaic panel temperature and price of electricity in the Brazilian spot market. A case study is presented to validate the applicability of the methodology. The method is developed considering various characteristics of the Brazilian market, specifically for the Free Contracting Environment, but can be adapted to other markets.

SVR Controller for a Biped Robot with a Human-like Gait Subjected to External Sagittal Forces

This paper describes the control of a biped robot that uses an SVR (Support Vector Regression) for its balance. The control system was tested subjected to external sagittal pulling and pushing forces. Biped robots have leg link structures similar to the human’s anatomy. To be able to maintain its stability under dynamic situations such robotic systems require good mechanical designs and force sensors to acquire the zero moment point (ZMP). Research in biped robotics has recently had a great surge due to the challenges of the subject and the media impact of famous biped robots like Honda’s. (Vukobratovic, 1990) developed a mathematical model of a biped robot and its method of control. Some research works (Zarrugh & Radcliffe, 1979), (Nakamura et al., 2004), (Jang et al., 2002) have reported the gait of biped robots based on human kinematics data, and a very good study of human body kinematics was done by Winter (Winter, 1990). Because a biped robot is easily knocked down, its stability must be taken into account in its gait design. Zheng (Zheng & Shen, 1990) proposed a method of gait synthesis taking into account the static stability. Chevallereau (Chevallereau et al., 1998) discussed dynamic stability through the analysis of the reaction force between the base of the foot and the ground. Unfortunately the defined trajectory does not assure the satisfaction of the stability restriction. To assure the dynamic stability of a biped robot, Shin (Shin et al., 1990) and Hirai (Hirai et al., 1998) proposed standard methods for gait synthesis based on the zero moment point (ZMP). Basically this method consists of designing a desired ZMP trajectory, duly correcting the movement of the torso to maintain the ZMP trajectory as designed. However, because the change of the ZMP to accommodate the movement of the torso is limited, not all desired ZMP trajectories are possible (Park & Kim, 1998). The ZMP position can be obtained computationally using a model of the robot. However there might be a significant difference between the real and the calculated ZMP due to the difference between the real robot’s physical parameters and its approximated mathematical model. To avoid this error, four force sensors are usually used on each foot to obtain an estimate for the real ZMP.

Human knee joint walking pattern generation using computational intelligence techniques

Computational intelligence techniques (CITs) can be used to generate the human knee joint angle walking pattern in the sagittal plane, useful in medical rehabilitation as a specific reference of normal pattern depending on the subject’s age, mass, height and stride duration. In this paper, the knee joint angle reference curves in the sagittal plane were generated by using three different CITs: artificial neural network, extreme learning machine (ELM) and multi-output support vector regression. The gait pattern of a woman is different of the gait pattern of a man, and consequently, their knee joint angle curves are also different. Thus, it was necessary to train and test each of the three CITs for each gender. The data used by the CIT were obtained from volunteers with healthy gait and with different characteristics (gender, age, height and weight). The volunteers’ knee joint angle curves were collected by a system mainly constituted by a treadmill, two web cameras and passive marks positioned at volunteers’ joints. These gait analyses were made for five different walking speeds. It was observed that the best curves for each gender were generated using the ELM. Therefore, the ELM can be used to generate the normal knee joint angle curves expected for any person with specific characteristics (age, mass, height, stride duration), and physicians can use these specific normal curves for comparison purposes instead of using the standard knee joint angle curves of the literature which do not take into consideration the specific characteristics of the joint angle source.