Kiyoto Ito

Action-Intention-Based Grasp Control With Fine Finger-Force Adjustment Using Combined Optical-Mechanical Tactile Sensor

This paper presents a control method that makes it possible for a home-use manipulation system to easily grasp objects with various weights and hardnesses. To provide easy operability for nonprofessional persons, an action-intention-based man-machine interaction method was developed. To enable the fine finger-force control required for grasping various objects, a combined optical-mechanical tactile sensing method with high-sensitivity slip detection was also developed. In addition, as a platform for manipulation systems with many sensors, a hierarchical multiprocessor controller was built. The developed methods were evaluated experimentally by using a prototype manipulation system consisting of a robotic hand and a user interface. The evaluation results demonstrate that the manipulator system can be used to easily grasp various objects, such as a rolled-up paper towel (weighing 4 g) and a clay-filled cardboard tube (weighing 500 g). Operability in remote control was also evaluated. The developed methods make it possible to fine-tune the finger force according to target object on the basis of tactile sensing information.

Dual rate Kalman filter considering delayed measurement and its application in visual servo

This paper describes a Kalman filter for a class of linear system in which: 1) The sampling time of measurement is longer than the control period. 2) The measurement is delayed. Using the delayed measurement and the present and past time predicted state, the pseudo-measurement in present time is constructed. The optimal Kalman gain is designed to minimize the trace of the covariance of estimation error. A dual rate recursive algorithm is proposed to estimate the state synchronously with the control signal. A visual servo system is demonstrated to verify the effectiveness of the proposed method.

Fast and accurate vision-based positioning control employing multi-rate Kalman filter

To achieve fast and accurate positioning control, a controller based on a visual servo employing a multi-rate Kalman filter was implemented and experimentally evaluated. Although a visual servo is expected to achieve robust positioning control by eliminating positional errors due to operation environments, applying visual information to positioning control faces three challenges, namely, lower sampling speed, longer delay, and lower positional accuracy than those possible by using a conventional position encoder. To overcome these problems, a multi-rate Kalman filter with a time-delay compensation technique is employed to combine visual information with encoder-based positional information. Two models describing a positioning-control experimental system using a one-axis linear stage with a camera were investigated to determine the optimum structure of the Kalman filter. Evaluation of the experimental system showed that the designed controller achieves high-precision (±10 μm) positioning control within approximately 10-ms settling time while simultaneously adjusting the environmental positional errors.

Mobile dual-arm robot for automated order picking system in warehouse containing various kinds of products

We have prototyped a mobile dual-arm robot and an automated order picking system including the robot for warehouses that contain various kinds of products. By using self-localization, model-based object recognition and arm trajectory planning, the robot can autonomously move to the front of the shelf that has a target product, fetch the product from the shelf and put the product in a carton transported by an automated guided vehicle. Especially for adjusting to various kinds of products and their storage situations, the robot makes two arms collaborate and mounts tables to lift and rotate two arms and four different types of end effectors. In experimental tests, the robot successfully picked out bottles in a case and picked up two different sizes of boxes directly placed on shelves with different heights. In the result, our proposed system can automate whole order picking operations in warehouses where the operations are currently performed by workers.

Scalable robotic-hand control system based on a hierarchical multi-processor architecture adopting a large number of tactile sensors

A robotic-hand controller with operating performance scalable according to the number of connected tactile sensors was developed. To eliminate performance bottlenecks that appear with increasing number of sensors, the controller architecture adopts multiple processors connected in a loosely-coupled hierarchical structure. Moreover, to maximize operation throughput of the system, a technique for gathering sensor data while all components operate asynchronously was also developed. A prototype robotic-hand system based on this architecture was constructed. The system experimentally demonstrated 62%-reduced control latency and 6.5-times faster sensor-data processing, thus achieving seven times greater performance scalability as compared with a conventional controller architecture. As a result, the proposed architecture enables the robotic-hand system to grasp objects with different weights and hardnesses.

Hierarchical 3D interconnection architecture with tightly-coupled processor-memory integration

In this paper, two designs of a 3D interconnection architecture for stacked processor-memory large-scale integrations (LSIs) were investigated. With consideration given to stacking formation, a hierarchical 3D interconnection architecture with a tightly coupled processor-memory stacking configuration is proposed for achieving both higher throughput per unit area and lower power consumption in the vertical communications. Compared with a baseline stacking configuration, the proposed architecture has the 38% fewer vertical interconnects for the same throughput and reduces power consumption by 21%. The performances of three-dimensional stacking chips with 64-processor cores are also estimated. As a result, the proposed architecture achieves twenty-times-lower power consumption of inter-chip communications than conventional 2D integration. A uni-directional interconnect configuration and a 3D two-way flow-control protocol were also developed to achieve maximal utilization of the 3D interconnection network. According to simulations using a cycle-accurate stacking LSI model, the proposed technique achieves 90% utilization of the interconnection network, while a conventional design achieves less than 60%.

Placement-position search technique for packing various objects with robot manipulator

In this study, a placement-position search technique for robot-executable, space-efficient packing of various objects with a robot manipulator has been developed. The technique is used to enable placing objects in order from the corner of a container, fulfilling the following conditions: (A) the corner is within the reach of a robot manipulator, and (B) the robot manipulator does not collide with surrounding obstacles when it moves an object to the corner. The technique is as follows: a robot manipulator holding an object alternates between motions in a straight line and random reflections from a surface of either a container or already-packed objects in a simulation of robot movement. The motions and reflections are under physical constraints such as the reach of the robot manipulator and collisions between the robot and surrounding obstacles. The technique was evaluated with numerical examples based on the CAD data of an actual industrial-robot-manipulator using five types of objects, and the robot-packable corner for each object was determined. We therefore concluded that the technique is essential for the packing of various objects with a robot manipulator. The technique is expected to be used for packing with a robot manipulator in warehouses and factories.