Ken Endo

Co-evolution of morphology and walking pattern of biped humanoid robot using evolutionary computation - evolutionary designing method and its evaluation

In this paper, evolutionary designing method of a biped walking robot is proposed and evaluated in comparison with traditional manner. Usually, the structure and control system of robot have been designed separately. Therefore, the structure is given in advance when the control system is developed. This results in a great deal of trial-and-errors. On the other hand, evolutionary designing method carries out these operations simultaneously. Two calculations are conducted of which morphologies are changed (evolutionary designing method) and not changed (traditional manner) during the evolution. As a result, almost the same number of pareto optimal solutions are emerged. However, solutions generated with evolutionary designing method obtain higher fitnesses than the others. This means that evolutionary designing method could be powerful and efficient method for the real robot.

Method for controlling master-slave robots using switching and elastic elements

A new type of master-slave control methodology, which has the merits of both unilateral and bilateral ones, is proposed. The methodology is built on switching the unilateral feedback controls of position and force as required using switching and elastic elements. Proposed methodology not only eliminates the demerits of bilateral control, but also supplies the mechanical force feedback to the operator. It utilizes a feature of human factor that direct displacement feedback is not as important as visual and force feedback. Effectiveness of the proposed method is confirmed by experiments using a developed simple single axis master-slave arm system. Driving test of the experimental devices and sensory evaluations are conducted. As a result, it is confirmed that the methodology successfully provides the sense of touch to the operator of the system.

A Control Method for Humanoid Biped Walking with Limited Torque

This paper presents an energy-efficient biped walking method that has been implemented in a low-cost humanoid platform, PINO, for various research purposes. For biped walking robots with low torque actuators, a control method that enables biped walking with low torque is one of the most important problems. While many humanoids use high-performance motor systems to attain stable walking, such motor systems tend to be very expensive. Motors that are affordable for many researchers have only limited torque and accuracy. Development of a method that allows biped walking using low-cost components would have a major impact on the research community as well as industry. From the view point of high energy-efficiency, many researchers have studied a simple planar walker without any control torque. Their walking motions, however, are decided by the relationship between a gravity potential effect and structural parameters of their robots. Thus, there is no control of walking behaviors such as speed and dynamic change in step size. In this paper, we propose a control method using the moment of inertia of the swing leg at the hip joint, and confirm that a robot controlled by this method can change its walking speed when the moment of inertia of the swing leg at the hip joint is changed without changing the step length. Finally, we apply this control method to the PINO model with torso in computational simulations, and confirm that the method enables stable walking with limited torque.

Co-evolution of Morphology and Controller for Biped Humanoid Robot

In this paper, we present a method for co-evolving structures and control circuits of bi-ped humanoid robots. Currently, bi-ped walking humanoid robots are designed manually on trial-and-error basis. Although certain control theory exists, such as zero moment point (ZMP) compensation, these theories does not constrain design space of humanoid robot morphology or detailed control. Thus, engineers has to design control program for apriori designed morphology, neither of them shown to be optimal within a large design space. We propose evolutionary approaches that enables: (1) automated design of control program for a given humanoid morphology, and (2) co-evolution of morphology and control. An evolved controller has been applied to a humanoid PINO, and attained more stable walking than human designed controller. Co-evolution was achieved in a precision dynamics simulator, and discovered unexpected optimal solutions. This indicate that a complex design task of bi-ped humanoid can be performed automatically using evolution-based approach, thus varieties of humanoid robots can be design in speedy manner. This is a major importance to the emerging robotics industries.

Morph: A Desktop-Class Humanoid Capable of Acrobatic Behavior

A desktop class humanoid robot, morph3, developed for humanoid robotics is described. Consideration to body form is given in order to appeal to a general audience. 138 sensors such as accelerometers, rate gyros, pressure sensors, and force sensors are mounted on morph3. We describe the electrical network which is utilized on-board the humanoid body, and describe some advantages of the system. Actual dynamical behavior such as walking, turning, and motions using the whole-body is performed on the humanoid robot.

Simultaneous design of morphology of body, neural systems and adaptability to environment of multi-link-type locomotive robots using genetic programming

In this paper, morphology of body and neural systems that define the locomotion of multilinked locomotive robots that can adapt to changes in environment are designed using the evolutionary computation. The morphology of the body and neural systems have a close relationship to each other. The model of the robot is designed so that the morphology of the body and neural systems emerge simultaneously. The morphology of the body and neural systems are generated using a genetic programming. The tasks are that the robots move on ground including hills of different heights in the two dimensional lateral simulated world under the effect of gravity. The robots are evaluated based both on a moving distance and an efficiency. As a result, various combinations between the morphology of the body and neural systems of the robots were emerged. The evolved robots were able to go over hills which they had not experienced.

Generation of Optimal Biped Walking for Humanoid Robot by Co-evolving Morphology and Controller

In this paper, a method for co-evolving morphology and controller of bi-ped humanoid robots is proposed. Currently, structure and walking pattern of humanoid robots are designed manually on trial-and-error basis. Although certain control theory exists, for example zero moment point (ZMP) compensation, these theories do not constrain structure of humanoid robot or detailed control. Thus, engineers has to design control program for apriori designed morphology, neither of them shown to be optimal within a large design space. Therefore, evolutionary approaches that enables co-evolution of morphology and control can be useful for designing the humanoid robot. Co-evolution was achieved in a precision dynamics simulator, and discovered unexpected optimal solutions. This indicate that a complex design task of bi-ped humanoid can be performed automatically using evolution-based approach, thus varieties of humanoid robots can be design in speedy manner. This is a major importance to the emerging robotics industries.