Most of industrial robotic manipulators are driven by servo motors through transmission mechanisms (reduction gears) . This paper presents a more detailed analysis of manipulator dynamics, in which rotational effects of driving motor on dynamic characteristics of the manipulator are taken into consideration. To carry out the analysis, a new modeling technique is introduced in the treatment of reduction gears in the equation of motion. In the analysis, the motor rotor itself is regarded as one of links. The function of power transmission element, that is, a kinematic relation between the link rotational angle and the motor rotational angle is interpreted as a constraint condition. Then the constraint condition and the equation of motion are solved simultaneously. This method is applied to one type of the industrial robotic manipulators to demonstrate the strict effects of the centrifugal and Coriolis forces caused by motor rotation on the dynamic characteristics of the manipulator.
The mobile robot based on the quadruped walking has specific characteristics, such as the ability to form an adaptive and active base in standstill posture, to make slow but smooth statically stable walking, and to make bumpy but fast dynamically stable running. This paper discusses to exhibit these advantages by introducing a new concept of the gait control named dynamic and static fusion gait, which covers from statically stable to dynamically stable walking. The gait is shown to realize by introducing a generalized trot gait which unifies crawl and trot gait, and a sideway sway compensation trajectory which sway the center of the gravity of the body to lateral direction to realize dynamic stability. The paper elaborates the algorithm to generate the continuous trajectory of the center of gravity of the body and the foot. The walking experiment is done by using test constructed walking vehicle model TITAN IV and the continuous accerelation locomotion from standstill to dynamic walk of up to 400 mm/sec is shown to realize.
An approach to robot hybrid position/force control, which allows force manipulations to be realized without overshoot and overdamping while in the presence of unknown environment, is given in this paper. The main idea is to use dynamic compensation for known robot parts and fuzzy compensation for unknown environment so as to improve system performance. The fuzzy compensation is implemented by using rule based fuzzy approach to identify unknown environment. The establishment of proposed control system consists of following two stages. First, similar to the resolved acceleration control method, dynamic compensation and PD control based on known robot dynamics, kinematics and estimated environment stiffness is introduced. To avoid overshoot the whole control system is constructed overdamped. In the second stage, the unknown environment stiffness is identified by using fuzzy reasoning, where the fuzzy compensation rules are obtained a priori as the expression of the relationship between environment stiffness and system response.
Binocular Vision has been considered to be a method of three dimensional measurement, and this leads to lack of discussing how to decide the size of region that apply physical restriction, the reliability of disparities. These missing issues are quite important for robots when they use it as a method of percepting depth information. In this paper, we propose an adaptive algorithm to compute reliable disparities fast. It is composed of two processes. One is the process that compute disparities with the uniform radius of the correlation window. It can compute disparities with high reliability by eliminating false disparities sequencially. Another is the process that compute disparities with the adaptive radius of the correlation window. Since this process automaticaly selects the minimum radius of the correlation window in which reliable disparities can be detected, fast computation of disparities is realizable. It is shown that the algorithm of Adaptive Disparity Detection is effective for various images.
“Teaching by Showing” is a straightforward teaching method in which a human instructor shows an assembly task to a robot by simply performing it with his own hand, and the robot automatically generates a program by watching the example task. For such a method to be realized, visual recognition of human action sequences becomes a crucial issue. In this paper, an experimental system that demonstrates the teaching method is presented. The system observes example tasks by stereo video cameras and generates symbolic descriptions of action sequences, which are translated into manipulator command sequences. Actions are modeled as partial state changes over segmented time intervals. And the partial state descriptors constitute the environment model. Segmentation events are defined for actions involved in hand assembly tasks, which are detected in terms of time differences of visual features. Integrating these, an algorithm of action recognition is fully described. It automatically segments and classifies every action in a robust and efficient manner. An experiment revealed that the system can recognize each action correctly in real time, and it can carry out the instructed task successfully.
In consideration of control ability of designed robot manipulator control system and the important ability or limit of robot manipulator, new trajectory planning method is proposed on the basis of high and qualitative judgment. Fuzzy reasoning is one of the powerful way in this case. It is introduced into trajectory planning in order to carry out trajectory planning systematically. This method is called fuzzy trajectory planning. Unsolved problems in previously proposed variable speed trajectory planning are solved by the proposed fuzzy trajectory planning method. Parallel drive robot manipulator is taken to be an example to show the effectiveness of the proposed method.
In order to reduce difficulties in carrying . out control experiments of an actual robot in a real environment and to speed up the development of the autonomous control algorithms for a mobilerobot, this paper proposes a mobile robot control system using a virtual environment, which consists of an actual robot hardware and a model environment assumed around the robot. By measuring the robot motion in real time, the system knows the position of the robot in the model environment, simulates the data the robot would obtain with its external sensors if the environment were real and sends it to the robot. The robot is autonomously controlled in the model environment using the external sensor data. Because the environment is a model, there is no trouble such as collisions with real objects and damages of the robot hardware, even if the control of the robot fails. It is also easy to evaluate the control algorithms using the real time motion measurement of the robot. We constructed an experiment system using the virtual environment and controlled the robot in it. We developed a collision avoidance algorithm against a wall and a method in which the position estimation error of dead reckoning is corrected based on wall recognition using the range information of ultrasonic sensors. Thus, we demonstrated the effectiveness of the system.
This paper describes the amphibious electrical manipulators JARM-10, JART-25, JART-100 and JARM-25 which were developed in the program of reactor decommissioning technology development carried out by the Japan Atomic Energy Research Institute. They are multi-functional telerobotic light-duty (10 and 25 daN) and heavy-duty (100 daN) Manipulators which can be used in hostile environments in reactor dismantling work such as high radiation, underwater work and electrical noise. Each manipulator can be operated in either a bilateral masterslave, a teach-and-playback or a programmed control mode. By combining these modes appropriately, it is possible to perform complex tasks of remote handling. The usefulness of the telerobotic systems for dismantling nuclear reactors has been demonstrated by successful application of the JARM-25 for remote underwater dismantlmeent of highly radioactive reactor internals of complex form of an experimental nuclear power reactor.
The problem of automatically generating a world map for mobile robots is addressed. A proposed map, based on the cognitive map of human, is qualitative and contains information such as action at an intersection with a landmark, relative-location between two locations and a sequence of landmarks in a path. A method of pathfinding using the map and modes of robot movement necessary for tasks such as map generation and pathfinding are described. As a result of computer simulation, the validity of our approach have been certified.