Fall prevention is one of the most important functions of walking assistance devices for user's safety. It is preferable that these devices obviates factors which induce falling over rather than helping them recovering from falling motion. Tandem stance, where both legs form a line along walking direction, is a factor of falling. It is often observed in turning motion because a swing leg moves in lateral direction as well as forward. Generally, upper body's turning of a person proceeds before lower limb's turning during walking, and the behavior of the lower limb is constrained by upper body turning. It is thus possible to control behavior of the lower limb for tandem stance prevention by constraining behavior of the upper body. This paper therefore introduces a tandem stance prevention method for safer walk of the elderly or physically challenged person. The method adjusts admittance of cane robot's turning motion according to the positions of a support leg and a swing leg. The cane robot measures user's leg position and estimates a walk phase of the user. By adjusting an admittance model of the cane robot based on the walk phase, the cane robot resists to turn while support leg is on the same side of the turning direction. As a result, the tandem stance is avoided. Through experiments, we confirmed that the cane robot successfully controls user's upper body's behavior to prevent the user from being in tandem stance.

A cane-type robot called intelligent cane has been developed to support the elderly during walking. By supporting a part of a user's body weight, the cane robot aims to reduce a load applied to a user's affected leg. Therefore, while the user's affected leg is a support leg, it is preferable that the cane robot stops to sufficiently support the user. In our previous work, the cane robot is controlled based on horizontal component of force applied to the cane robot and moment around a vertical axis. In this paper, virtual friction force, which is proportional to vertical component of force, is proposed to improve a walking assistance capability of the cane robot. In addition, virtual frictional coefficients are arranged based on the user's state inferred by a laser range finder. By employing the proposed method, the cane robot moves easily in the both legs support phase, stops in the healthy leg support phase, and supports the user reliably in the affected leg support phase.

3D assembly of cellular structures is important for the fabrication of biological substitute in tissue engineering. In this paper, a novel rail-guided multi-microrobotic system was proposed for the assembly of cellular structure. The cellular 2-dimensional (2D) module was fabricated by UV illumination of the crosslinkable hydrogel. The coordinated manipulation among the micromanipulators was performed with newly designed concentric movement along the rail, which realized the arbitrary change of micromanipulator posture. Through the rotation of the end-effectors around the specimen without swapping out the visual field, the manipulation flexibility was improved. The distance information between the micromanipulator and the module was acquired from vision feedback system and utilized for the automatic pick-up of the microstructure. Through the cooperation among multi-manipulators with hybrid motors, the micromanipulation to assemble the 3D structure with 30 nm operation resolution was achieved. Finally, the rail-guided DeSCom system realized the bottom-up fabrication of cellular vascular-like microtube with vision feedback.

Intelligent cane is a robot developed for assisting the elderly or handicapped people in walking. As a nursing-care device, the cane robot is designed to assist the elderly or handicapped people not only in indoor environments but also in outdoor environments. Therefore the cane robot is required to be smaller and lighter. In addition, it is preferred that the cane robot is movable in omni-directions so that it can be used in various situations. A concept called “intentional direction (ITD)” was proposed to estimate the user's walking intention by analyzing signals from a 6-axis force/torque sensor fixed to the handle of the aluminum stick. Admittance control method was applied to the motion control of the cane robot. In this paper, a new algorithm based on the usage and purpose of an ordinary cane is proposed. In the proposed algorithm, the cane robot is appropriately stopped to support the elderly more effectively. The effectiveness of the proposed method is verified through the experiments.

In electronic manufacturing system, the design of the robotic gripper is important for the successful accomplishment of the assembly task. Due to the restriction of the architecture of traditional robotic hands, the status of assembly parts during the assembly process cannot be effectively detected. In this research, an intelligent robotic gripper - i-Hand equipped with multiple small sensors is designed and built for this purpose, getting the essential parameters for some specific mathematical model. Mating connectors by robot, as an experimental case in this paper, is studied to evaluate the performance of i-Hand. A simple new model is proposed to describe the process of mating connectors, within which the distance between the connector and deformable Printed Circuit Board (PCB) is detected by i-Hand. An online Fault Detection and Diagnosis (FDD) algorithm is proposed. Various possible situations during assembly are considered and handled according to an event driven work flow. The effectiveness of proposed model and algorithm is proved by the experiments.

In this paper, an automatic system for single cell analysis inside an environmental scanning electron microscopy (ESEM) was proposed. Single yeast cell was put on an tungsten probe substrate inside ESEM. The endeffector for single cell analysis was fixed to an nanorobotic manipulator, which has three degrees of freedom, i.e. X, Y and Z translation. The real time images during the experiment can be observed by ESEM system in realtime. Therefore, the position of the endeffector and the single cell can be recognized by imaging processing. These position information were used as the feedback signal to control the movement of the nanorobotic manipulator. Finally, a single cell cutting experiment was performed to demonstrate the working mechanism of this system. Two types of cell pattern substrates were also designed and fabricated as the cell analysis chips for the automation single cell analysis in the future.

An intelligent cane robot (iCane) was designed for aiding the elderly who have muscle weakness on lower limbs. A commercial omni-directional wheels robot was used as an omni-directional mobile base, and an aluminum stick was installed on the base of cane robot. A Concept called “intentional direction (ITD)” was proposed for estimating the user's walking intention by analyzing the signal of a 6-axis force/torque sensor which is fixed to the handle of stick. A universal joint driven by two DC motors was designed to control the posture of the stick. As a care-nursing device, the cane robot was designed to assist the elderly in both indoor and outdoor environments. Therefore the size and weight of cane robot should be minimized. But in that case, there is high risk that the cane robot would be pushed over by the user. In this paper a constrained nonlinear multivariable algorithm was designed to optimize the stable posture of cane robot. By controlling the posture of stick, the maximums sufferable torque moment which lead to cane robot falling over can be increased. The experimental results show that the stability of cane robot can be enhanced effectively.

In this study, we present an omni-directional cane robot for aiding the elderly and handicapped people walking. The motion control problem is investigated for both normal and abnormal walking conditions. In the case of the user's normal walking aided by the cane robot, a concept called “Intentional Direction (ITD)” is proposed. Guided by the online estimated ITD, we apply the admittance control method in the motion control of cane robot. The gravity compensation is also considered because the user is possible to walk on a slope. For the abnormal walking, we mainly studied the case of user's falling down. The Center of Gravity (COG) of user can be estimated from the angle of an inverted pendulum which represents human model. Fall prevention algorithm based on the relationship between user's COG and the cane is proposed. This algorithm is also applied in the motion control of cane robot. The proposed method are verified through experiments.

A three-wheeled omni-directional cane robot is designed for aiding the elderly walking. Possible move modes are analyzed and a corresponding hybrid model is constructed to describe walking behavior. A concept called intentional direction is presented to denote the moving intention of a human. Based on experiments and some assumptions, dynamic model of intentional direction is obtained as well as its online estimation method. A new admittance control scheme is presented based on intentional direction, which provides natural and intuitive human machine interface. Experiment results show the effectiveness of the design.