This research is concerned with a stability control method with a criterion based on reaction for motion control of a mobile manipulator. Mobile manipulators can propel themselves around a work area and can operate over a wide area. Then, a stability evaluation and a stability control method must be required for mobile manipulators that are not fixed on a floor. The evaluation method based on ZMP (Zero Moment Point) criterion, in which the model is regarded as a particle system, is not satisfactory for evaluating stability of a mobile manipulator that consists of solid links. In addition, transient state during tipping over has not been discussed. In this paper, we propose a stability evaluation criterion based on reaction for the solid model of a dynamic mobile manipulator. First, equations of motion of the mobile manipulator for stable and unstable states of motion are formulated based on constraint conditions. Second, a stability criterion based on reaction is proposed by referring the formulated model. Third, the relationships between changes in reaction and changes in ZMP during tipping over are discussed through simulations. Finally, it is shown that a mobile manipulator can return from unstable transient state to stable state by performing stability compensation motion.
This research is concerned with an adaptive controller of a 1-link mobile manipulator for moving operation while traveling on an unknown irregular terrain. Considering a condition that the end-effecter of the mobile manipulator should track a desired trajectory in the vehicle-fixed coordinates while the mobile manipulator traveling on an unknown irregular terrain, it is subjected to effects of disturbance torques derived from influences depending on the terrain, and moreover it is difficult to measure precisely the shape of the terrain. Therefore, some kinds of leaning mechanism must be integrated to the controller to achieve accurate trajectory tracking performances. In this paper, we show that an adaptive controller with a neural network can compensate such kinds of unknown disturbances. The validity of the neuro-adaptive controller is clarified through real experiments, which compare the simple adaptive controller and neuro-adaptive controller in two different conditions, that is horizontal plane and irregular terrain. This experimental results show that the neuro-adaptive controller can maintain almost the same tracking performances even on the unknown irregular terrain like as the performances on horizontal plane.
The table tennis task involves dealing with the control and measurement issues that arise from the dynamical interaction between a robot and its environment. This paper describes how a robot with a flat paddle coordinates its movement in order to achieve efficient strokes for any given ball. We propose a method of generating stroke movement based on virtual targets that means the point at which the ball should be struck and the paddle velocity just before hitting the ball. These targets are predicted using inputs-outputs maps implemented efficiently by means of a k-d tree (k dimensional tree) . The paddle approaches these targets by using a visual feedback control scheme similar to the mirror law proposed by Koditschek. The results of the implementation are also given to show the effectiveness of the proposed method.
Visual attention is one of the key issues for robots to accomplish the given tasks, and the existing methods specify the image features and attention control scheme in advance according to the task and the robot. However, in order to cope with environmental changes and/or task variations, the robot should construct its own attention mechanism. This paper presents a method for image feature and state space construction by visio-motor learning for a mobile robot towards visual attention. The learning model which consists of the image feature generation and state vector estimation is suggested by a visual cortex architecture. The teaching data constructs the visio-motor mapping that constrains the image feature and state space construction as well. The method is applied to indoor navigation and soccer shooting tasks, and discussion is given.
Several types of running robots have already been studied and developed. But no one of them could perform gradual transition from stationary state to steady hopping or the reverse way. In order to create a three-dimensional running robot, we study a control method called Variable Constraint Control which can realize various kinds of gaits. First we have realized a motion pattern for an one-leg robot which is expressed as differential equations of characteristic values of the robot. It is an unified method for the control of hopping and stationary state. The motion type is easily switched by chaging the parameters of the equations. This paper presents a control method for a one-leg hopping robot, and relation between the parameters and the motion is discussed. A simulation result of it is showed at the end.
This paper describes an algorithm for robot perception of impedance, by which motion-force relation of the robot's end-effector during arbitrary motion is analyzed on-line. Using this method, the impedance that constrains the robot's motion is estimated; the uncertainties of the estimates are evaluated; and discontinuous changes of the impedance are detected. The estimated impedance can be used to identify local dynamic properties of the environment and temporary constraint condition imposed on the robot. The detected discontinuities can be used for segmentation of manipulated tasks and recognition of geometric structure of the environment. Because of its independency from any control methodologies, this method is multipurpose and applicable for both autonomous and remote-controlled robots. Results of preliminary experiments are presented.
This paper proposes a method for estimating position and orientation of multiple robots from a set of azimuth angles of with respect to landmarks and another robots which are observed by multiple omnidirectional vision sensors. Our method simultaneously perform self-localzation by each robot and reconstruction of relative configuration between robots. Under the situation where it is impossible to identify each index for the observed azimuth angles with that for the robots, our method reconstruct not only relative configuration between robots using“triangle and enumeration constraints”but also absolute one using the knowledge of landmarks in the environment. In order to show the validity of our method, this method is applied to multiple mobile robots each of which has an omnidirectional vision sensor in the real environment. The experimental results show that the result of our method is more precise than that of self-localization by each robot.
This paper proposes a flexible adapting system for human symbiotic robots that stably performs given tasks as preplanned even if physical contacts and interferences with humans occur during movement. In order to accomplish tasks stably while compliantly adapting to human motion keeping contacts, task constraints state transition and four types of motion phases (Preset motion, Human following motion, Task continuing motion, Posture recovering motion) which are switched according to contact situations are incorporated in this system. As a result of evaluation experiments, it was confirmed that the proposed system is effective for human-robot coordination to realize both high task performance and adaptability to humans.