In this paper, we propose a new solid model named “Hierarchical Sphere Model” (HSM) for modeling coordinated robots and present a feasible interference check algorithm running on HSM. HSM arranges region informations in a hierarchical tree structure and its node corresponds to a spherical region. To detect any interference between objects modeled with HSM, regions which must be investigated can be compressed small by using hierarchy of HSM. Hence the algorithm works efficiently in spite of complicated robots' shape. Furthermore, any interference can be checked just by recursively calculating the distance between spheres corresponding to HSMs' nodes no matter how the robots move. Therefore, HSM is suitable for modeling coordinated robots with complex shape.
Criteria to evaluate the performance of new robot actuators whose output torques or forces are the function of their angular displacement, from the point of view of the characteristics as energy converters, are proposed. The power of linear actuators which reciprocate, is defined as the maximum time average power from the analogous image with a reciprocating engine, and also the same power is defined for the reciprocating rotary actuator. The energy is defined as the one cycle average of static force or torque when actuators reciprocate statically. In order to evaluate the lightness and compactness of actuators, the power and energy are devided by the mass or volume of the actuators. The criteria were applied to new robot actuators to know their merits and demerits as energy converters. As the results, their situations are made clear by the significant difference over two times of the evaluation values among each other, and moreover it was understood that these criteria are very useful not only for the evaluations of new robot actuators but also for the development of new robot actuators.
In this paper, a new control method for a bilateral master-slave manipulator is proposed. The proposed method yields stable and fast response of the control system. These are essential to obtain a precise position control and a sensitive force reflection control. In the conventional position-force control method, each control loop of the master and the slave arms are connected in series to construct a bilateral control loop. Therefore the total phase lag through the bilateral control loop becomes twice as much as that of one arm control. Such phase lag makes the control system unstable and control performance worse. To improve the stability and the control performance, we propose “parallel control method.” In the proposed method, the control loops of the master and the slave arms are connected in parallel so that the total phase lag is reduced to as much as that of one arm. The stability condition of the proposed method is studied and it is proved that the stability of this method can be guaranteed independent of the rigidness of a reaction surface and the position/force ratio between the master and the slave arms while the stability of the conventional method depends on them.
Significant subject on edge detection is that edge points with small level change can be detected without mis-detection by noise or change of gray level on shadow or curved surface. In our study we propose a new edge detection method based on variance of gray level. This is effective method, because the variance of gray level indicates the distribution of gray level. Edge points are detected by V3 value calculated by following expression. V3(I, J)=V2(I, J)/V1(I, J)=1/n2ΣiΣj(L(I+i, J+j)-Mean)2 V2(I, J)=1/n2ΣiΣj(L(I+i, J+j)-Mean)2-V1(I, J)| For the edge points, V3 value is less than 0.65 when step change is greater than 4*σnoise. The othen hand, for the points in the processing region without the edge line, V3 value is greater than 0.65. Therefore, V3 operator enables to detect only edge points with step change.
This paper discribes an autonomous robot manipulation system based on geometrical modeling and processing. We call it Kraft (Kobe Robot Arm Free from Teaching). Kraft plans the manipulator motion by the following sequence, Firstly, the model of the working environment is obtained interactively by a range finder and the geometric model of its Secondly, the motion is planned from the model by a collision avoidance algorithm and an automatic generation method of the grasping position. Thirdly, the planned motion is checked by an offline simulator using graphic animation and collision detection by numerical calculation. Finally, the obtained motion is executed by a manipulator with 7 d. o. f. The burden of the software implementation has been reduced, because Kraft has a solid modeler as its kernel. It is confirmed that Kraft could plan the ‘pick up’ motion autonomously in the working environment with relatively simple obstacles, and that not the preciseness of the model of the working environment but the consistency of it is crucial for the following motion planning.
This paper presents an open architecture robot control system for lower level manipulator control such as motion control or force control. Basically, the system consists of three elements: an industrial robot manipulator called A-HAND, a servo-computer with the motor driver units, and a host computer. The system is called ARS/A (Aoba Robot System for A-HAND). The robot and the servo-computer are regarded as an independent robotic module with a standard interface to the host computer, from which it accepts a set of real time commands to control the robot. Any computer to have the interface may be connected to the robotic module as a host computer. To design the set of real time commands is a crucial issue because it determines the capability and flexibility of the robot system. This paper proposes a set of real time commands which are needed for lower level control experiments. The set was found through experiences. A real time monitor called MOS/A (Motor Operating System for A-HAND) to process the commands to control the robot are implemented on the servo-computer. The MOS commands are defined as functions of a C language on the host computer. The C language is called ARC/A (Aoba Robot C Language for A-HAND) to have other robot control utility functions such as graphic simulation functions as well as the MOS functions. Sample programs show that ARC/A is an efficient programming tool for lower level control.