We have proposedmotion sketch  as a method to represent an interaction between a one-eyed learning agent (a mobile robot) and its environment. In this paper, we extend the basic idea inmotion sketch, tight coupling of perception and action, tostereo sketchby which a stereo-vision based mobile robot learns various kinds of behaviors such as target reaching and obstacle avoidance. Here, we deal with target reaching behavior with whichmotion sketchcopes by detecting and avoiding occlusions. First, an input scene is segmented into homogeneous regions by the enhanced ISODATA algorithm with MDL principle in terms of image coordinates and disparity information obtained from the fast stereo matcher based on the coarse-to-fine control method. Then, the segmented regions including the target area and their occlusion status identified during the stereo and motion disparity estimation process construct a state space for a reinforcement learning method to obtain a target reaching behavior. As a result of learning, the robot can avoid obstacles without describing them explicitly. We give the computer simulation results and the real robot implementation to show the validity ofstereo sketch.
Ultrasonic range finders have already been used successfully in indoor mobile robots. However, in outdoor environment, the sensor should be robust against noise from vehicle engines, costruction machines and other sound sources. The aim of this paper is to describe a simple, low-cost, and robust ultrasonic range finder witch is based on the cross-correlation technique for accurate ranging of multiple objects in the field of view of the range finder. This sonar transmits wave coded by the pattern that consist of some narrow pulses, then calculates the cross-correlation between the transmitted signal form and the received signal. Furthermore, several this range finder can work simultaneously. The experimental results show this sonar is much more robust against noise than the conventional sonar, and the sensor can find objects fast and precisely for measureing with another sonar simultanousely.
This paper describes a software framework which can support different types of bodies and behaviors with different processing times. The system we propose consists of 3 parts, “Mother, Brain, Sensor & Actuator”. Brain consists of robot behavior programs and their supporting libraries, and Sensor & Actuator consists of sensor processing and actuator control system. Mother consists of tools to produce and evolve Brain programs. In building tools and libraries for such a platform you are faced with two major problems. One is, system architecture will always have a trade-off relationship with “extensibility” and “shareablity” . The other problem you encounter is the difference in execution time between the low-level real-time reactive environment and the high-level behavioral software. In this paper we describe the methods and the software environment that we built which overcomes the problems mentioned above, based on the remote-brained robotic approach. This system enables us to develop flexible multiprocess networks made of processes with differing computing times which in turn enables the contruction of various brain architectures.
A pneumatic actuator makes it possible to construct light and small motion control system, because it has the characteristics of high power/weight ratio and so on. The flexibility due to air compressibility is fairly effective for contact tasks with soft and fragile objects, for example, as a human. On the contrary, the low stiffness due to air compressibility makes the control performance easily influenced by a friction force at sliding part. In this study, a 3 D.O.F. flexible actuator without sliding part comprising elastic rubber balls is developed as an end effector of robot manipulator. The modelled static characteristics are compared with some experiments. It is shown that in the low pressure range, the characteristics of actuator can be approximated by the linear model derived based on the concept of spherical shell. The position control system is constructed according to the linear actuator model and the fundamental position control performances are investigated. In some experimental results obtained from PI controller, the satisfactory position control performances are obtained.
The key for performing a robotic task in an uncertain environment is a control in the object-centered coordinate system. The visual servoing has been studied as an object-centered control method, however, it is unsuitable for tracking a trajectory because it is a PTP control. In this paper, a novel trajectory tracking control method using visual information is presented. We apply the preview control so that a manipulator can track a trajectory described in the object-centered coordinate system. In the preview control, the criterion to be minimized is the integral of the summation of square tracking error and kinetic energy. The optimal control law in the discrete time system is also proposed. Since this method refers to the future information, it can reduce a tracking error and suppress the amplitude of the velocity. Experimental results show that exact and smooth tracking is realized.
This research is concerned with a control method for trajectory tracking and obstacle avoidance by redundant manipulators. When an operation system dose not require preparations about positioning and definition of a contour of a working object, the working efficiency will be improved. Working to unknown objects is desired to be executed automatically. When a trajectory of manipulator's hand is on the surface of the object, the object could be an obstacle, and both the trajectory tracking and obstacle avoidance must be controlled parallel in the same time. We have formerly presented a redundancy control system using a preview control to achieve simultaneously these two tasks. The preview control system is a method to change the current arm form by referring to the form in the future. However, the manipulator sometimes happens to collide against the passed obstacle. This paper proposes a new redundancy control method to solve this problem. This system consists of both the preview and postview controls, considering into the past arm form by using its redundancy. This system is applied to objects which contour is concave and the effectiveness is verified through simulation experiments.
Design of a satellite mounted robot system which is teleoperated from a ground control station needs some key parameters to be decided in advance. Those are a required communication capacity, a required performance of a vision system and a robot control system. The required communication capacity is decided mainly by the required quality of the video image which is sent from the remote robot site. These parameters were decided by the teleoperation experiments under the simulated space robot operation environment on an on-ground space robot testbed. Effect of the time delay in the robot control loop and its countermeasures were also evaluated.
When a robot arm is mounted on a satellite to perform tasks, the satellite attitude must be maintained to retain the communication link and to generate electrical power from its solar pannels. It is not realistic to control the total system as one dynamic system, since the number of degrees of freedom becomes large, and the computational requirement for the satellite-mounted computer becomes stringent. The proposed control method used independent control systems for control of the motion of the robot arm and satellite attitude control. The robot arm control system estimates the angular momentum which will be produced by the robot arm motion, and the attitude control system compensates for the disturbance by using the feedforward control. The robot controller also manages the motion plan of the robot arm in order not to disturb the satellite's attitude stability.
Saving energy is one of the main topics of discussion in the modern world due to the limitation of energy resources and the deterioration of the environment on earth. It is, therefore, timely to consider saving the dissipative energy in a manipulator system in PTP motion control. This paper deals with the determination of the optimal trajectory which can minimize the dissipative energy in actuators of a horizontally articulated manipulator. The dissipative energy is dependent on the operating time and the angular functions of the joints. First it is proved that each optimal angular function is anologous, even for different operating times, and that the dissipative energy is inversely proportinal to the cube of the operating time. When obtaining the optimal angular functions by solving the two-point-boundary-value problem with non-linearity, it is essential to select a good starting function for the angles so that the solution does not fall into a local minimum. Therefore this paper proposes a starting function so that the driving currents of the joints can be reduced. The simulations show that the optimal trajectory based on the proposed starting function is effective in saving energy.
This paper investigates the stability of control system for a free-flying space robot which grapples a target satellite with remote teleoperation from the ground. As the robot body is not fixed in an inertial space, the manipulator motion causes the body movement and the target position changes in robot body frame. The operator finds the target motion by the delayed image data and controls the robot. Therefore the closed loop system of the remote teleoperation involves the operator and the communication equipment, which may decrease the stability. Firstly in this paper the operator performance is investigated by experiments using graphical simulation and simple operator model is produced. Using the operator model, stability condition of the closed loop system is derived as the function of conventional and generalized Jacobian matrices. The condition shows that the space robot can be controlled under long communication time delay, if the manipulator status is not close to the singular point. Finally, through experiments on the simulator it is confirmed that the space robot with remote teleoperation can capture the target.
Impedance control is one of the most effective control method for a manipulator in contact with its environment. In this method, however, the end-effector of the manipulator does not move until an external force is exerted. Therefore an impact force from the environment cannot be avoided. The present paper proposes a concept of a non-contact impedance control for a manipulator, which can regulate virtual impedance between the end-effector and external objects using visual information. First, a virtual force exerted from the object that is not contact with the manipulator is introduced. The virtual force is computed from the non-contact impedance and the motion of the object, so that the manipulator can respond the approaching object without any contact. Then the proposed method applies to an object avoidance problem and a contact task. Validity of the proposed method is verified through computer simulations. Finally, the proposed method is implemented using a direct-drive robot and a PSD camera system in the planar task space. Experimental results show that the non-contact impedance control is realized with a high sampling rate and a sufficient accuracy.
The purpose of this research is to make multiple robots perform the task according to the intention of an operator. As it is difficult for a human to operate all robots simultaneously, we propose the cooperation style in which the human operates one robot and the other autonomous robots assist it. In order to assist the human operating robot autonomously, it is necessary for the assistant robots to recognize the motion of the human operating robot in real time. For this purpose, we developed the motion recognition based cooperation system between the human operating robot and the autonomous assistant robot. In this paper, we proposed the motion recognition mechanism referring to the human cognition model. We implemented the motion symbolization method using the “Characteristic Matrix” and the motion recognition method using the “Feature Pattern” . As the assistance mechanism by the autonomous robot, we implemented “Task-Operation Model” to describe the motion and “Event Driven Method” to manage the execution. We indicated the effectiveness of these methods by the experiment using two hexapod robots which lifted up a box in cooperation.
In this paper, an impedance control system which uses together the inner torque control system with the disturbance observer is proposed for the pneumatic robot manipulator. It is assumed that the generated torque by a pneumatic actuator can be estimated from the pressure signals and the discharge volume. And we define that the disturbance torque includes the friction torque, load change and modeling error. At first in order to improve the control characteristics of pneumatic actuator driven by meter out method, we construct the inner torque control system by feeding back the generated torque. Secondly, to reduce the influence of the defined disturbance torque, we compose the impedance control systems with the disturbance observer which can estimate the defined disturbance torque based on the generated torque, the angular velocity and the reaction torque. In order to realize the robust impedance to the defined disturbance torque, we construct the torque based impedance control system which uses together the inner torque control system with the disturbance observer. The real command to the torque control system is generated from the impedance model and the positioning error. From some experiments, it is verified that the proposed impedance control system is effective to adjust the impedance of pneumatic robot manipulator.
This paper describes an adaptive hybrid visual servoing/force controller to realize visual servoing while the manipulator exerts contact force on a constraint surface. The proposed controller has a hybrid structure of force control and visual servoing control. It has on-line estimators for the parameters of the camera-manipulator system and for the parameters of the unknown constraint surface. It needs no α priori knowledge except the manipulator kinematics. First, we propose an estimator of an image Jacobian matrix which describes the relation between image features and the tip position/orientation of the manipulator. Second, a method to estimate the normal vector of the unknown constraintt surface is introduced. Then, an adaptive hybrid visual servoing/force controller is proposed. Finally, experimental results are shown to demonstrate the validity of the proposed method.
Multistage learning applied to obstacles avoidance is studied in this paper. We propose a new learning system which consists of the hierarchical fuzzy rules, fuzzy evaluation system and 2-stage learning automata. Then we show how an autonomous mobile robot can acquire the optimal action and fine attentive behavior using multistage learning through the interaction with the real world. In other words, the robot acquires how to pay attention to moving obstacles and how to avoid them using the steering and velocity control inputs, simultaneously. We also show the experimental results to confirm the feasibility of our method.