The cell production method, which facilitates high-product-mix and low-volume manufacturing, has been expanding into the mainstream, and demand has been growing for a robot similar in size to workers that can dexterously act as a multiskilled worker and handle heavy materials in a cell production line. We have developed a hydraulic double-arm robot that is equipped with hydraulic actuators for the arms, allowing it to handle heavy materials, and the TV800 vertical articulated robot arm consisting of electric actuators produced by Toshiba Machine Co., Ltd. For the wrists, allowing it to also achieve dexterous handling operations through visual feedback and compliance control. Also, we have developed a new fault detection system equipped with this robot. This system can detect faults of materials, not only by visual inspection, but also by weight inspection using the pressure of hydraulic cylinder.
A path-generating regulator is a control method for two-wheeled or four-wheeled mobile robots to converge a position and heading angle of a vehicle to the origin. We have proposed a method for performing obstacle avoidance by modifying the target heading angle to correspond to obstacle and shown the simulation results. In the paper, we perform obstacle avoidance experiment by a real vehicle and confirm the validity. Moreover, we discuss the application of the proposed method to the situation with unknown obstacles. To cope with unknown obstacles, we employ a laser range finder and update the steering control when the obstacles are found. We verify the vehicle trajectory obtained from the experiments and conclude that the performance of the proposed method is enough to be applied to the real vehicle.
Real-time depth estimation is used in many applications, such as motion capture and human-computer interfaces. However, conventional depth estimation algorithms, including stereo matching or Depth from Defocus, use optimization or pattern matching methods to calculate the depth from the captured images, making it difficult to adapt these methods to high-speed sensing. In this paper, we propose a high-speed and real-time depth estimation method using structured light that varies according to the projected depth. Vertical and horizontal stripe patterns are illuminated, and focus is placed at the near and far planes respectively. The distance from the projector is calculated from the ratio of the amount of the blur due to defocus(bokeh) between the stripes projected on the object surface. This method needs no optimization, and the calculation is straightforward. Therefore, it achieves high-speed depth estimation without parallel processing hardware, such as FPGAs and GPUs. A prototype system of this method calculates the depth map in 0.2ms for 2,500 sampling points using an off-the-shelf personal computer. Although the depth resolution and accuracy are not on par with conventional methods, the background and the foreground can be separated using the calculated depth information.
In this study, a fundamental method to tune a basic input/output gain (BIOG) according to usage conditions is proposed for improving work performance in human-machine systems. For improving operability and workability, an I/O gain tuning is effective, but frequent and drastic changes degrade the operability by confusing the machine dynamics. The proposed tuning system adjusts a BIOG at long intervals on the basis of comprehensive features in operator and work content obtained from histogram of control lever input. The target value is set to the normal distribution, meaning that all ranges of the control lever are evenly used in a spring-type lever, as leveling histogram independent of an operator and work content provides the consistent operational feeling, which leads to comfortable operability. To meet practicality and effectiveness, a BIOG curve is set to a polygonal line involving a break point and a saturation point that are tuned by equivalent transform of area differences between the obtained histogram and normal distribution curves. Results of experiments conducted by using a hydraulic arm system showed that the proposed BIOG tuning system improves time efficiency by reducing the area difference while increasing the subjective usability compared with a conventional fixed BIOG system.
Some research institutions have developed biped-walking robots aimed for prospective cooperative working with humans. Among various research items related to them, waist joint is important because it gives so much influence to the stability of upper body. Many biped-walking robots developed so far use a single rotary joint in waist joint, but it has a crucial drawback in energy consumption to stabilize the upper body. In our research a new mechanism has proposed, which consists of a crossover 4-bar linkage controlled by two motors via springs. The crossover 4-bar linkage is intrinsically more stable than a single rotary joint. Two springs are arranged counteractively to regulate the stiffness of the waist joint. This paper shows a stability index to evaluate stability of the crossover 4-bar linkages. It also proposes a mechanism of the waist joint followed by examinations of allocation of the linkages and springs in terms of stiffness control. We developed a test machine based on the simulation results and achieved some experiments, which clearly showed the experimental results are well coincident with the theoretical one.