Shotaro Nakagawa

Optimal posture control for stability of intelligent cane robot

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 users 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.

Control of intelligent cane robot considering usage of ordinary cane

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 users 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.

Fall detection and prevention in the elderly based on the ZMP stability control

An intelligent cane robot is designed for assisting the elderly or physically challenged people walking in daily life. The cane robot is driven by an Omni-directional mobile base; an aluminous stick is fixed on the base. A variety of sensors are installed on the cane robot for estimating the users intention and status (normal walking or falling). The users intentions of to which user want to move can be estimated by analyzing the active force on cane robot. As a nursing-care robot, the safety is a most important concern; before the elderly fall over, the cane robot should detect the sign of the falling and control the robot to assist the elderly to prevent it. Therefore a fall detection concept is proposed to estimate the risk of the falling based on the theory of zero moment point (ZMP) stability. An on-shoe sensor is designed to measure the ground reaction force and calculate the ZMP based on distributed force. The safety walking status is defined in the case of the ZMP is in the boundary of the support polygon. While the ZMP moving out of that boundary, the user will fall over.

Tandem stance avoidance using adaptive and asymmetric admittance control for fall prevention

Fall prevention is one of the most important functions of walking assistance devices for users 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 bodys turning of a person proceeds before lower limbs 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 robots turning motion according to the positions of a support leg and a swing leg. The cane robot measures users 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 users upper bodys behavior to prevent the user from being in tandem stance.

Real-time fall and overturn prevention control for human-cane robotic system

A Intelligent Cane Robot(iCane) has been proposed to assist the elderly walking in daily life. As a nursing-care robot, the safety and dependability are the most important issues that should be investigated. For preventing the human subject from falling, the angle of human body and the acceleration of center of gravity(COG) should be less than some threshold. Although in a human-in-the-loop system, the human subject is regarded a uncontrollable object. However, while the user is falling over, the cane robot can move to a appropriately position and support the user for balance. As the prerequisite condition that the cane robot support the human balance, the stability of cane robot should be ensured firstly. According Newton-Euler Law, a dynamic model is proposed to present the stability of human-cane robotic system. A impedance control are used to achieve position, posture and force control of iCane for fall prevention. The simulation and experimental results show the performance of fall prevention by using iCane.

Fall detection for the elderly using a cane robot based on ZMP estimation

For assisting the elderly or physically challenged walking, a cane robot which be driven by an Omni-directional mobile robot has been proposed. A variety of sensors fixed on the cane robot is used for monitoring users motion and detecting environment around user. The users intentions of to which user want to move can be estimated by monitoring the applied force to cane robot, then the cane robot is controlled to move and aid user to walk. As a nursing-care robot, the safety is a most important concern; therefore a fall detection concept is proposed to estimate the risk of falls in elderly by referencing to the Zero Moment Point (ZMP) stabilization. An on-shoe sensor is proposed to estimate ZMP by obtaining dynamic reaction force at the contact of the foot with the ground. The safety of elderlys walking is defined in the case of that the ZMP is inside support polygon. If ZMP is on or out of the boundary of support polygon, the user will fall down or have a trend of falling down. Experimental results are presented success of proposed ZMP estimation and fall detection schemes.

Fall detection for elderly by using an intelligent cane robot based on center of pressure (COP) stability theory

An intelligent cane robot was designed for aiding the elderly and handicapped people walking. The robot consists of a stick, a group of sensors and an omni-directional basis driven by three Swedish wheels. Multiple sensors were used to recognize the users “walking intention”, which is quantitatively described by a new concept called intentional direction (ITD). Based on the guidance of filtered ITD, a novel intention-based admittance motion control (IBAC) scheme was proposed for the cane robot. To detect the fall of user, a detection method based on Dubois possibility theory was proposed using the combined sensor information from force sensors, a laser ranger finder (LRF) and an on-shoe load sensor. The human fall model was represented in a two-dimensional space, where the relative position between the center of pressure (COP) and the center of support triangle was utilized as a significant feature. The effectiveness of proposed fall detection method was also confirmed by experiments.

Real time posture control for stability improvement of intelligent cane robot

For aiding the elderly who have muscle weakness on lower limbs, an intelligent cane robot system was proposed and constructed. An omni-directional mobile robot with three omni-directional wheels was used as the base. An aluminum stick was fixed on the mobile base of cane robot. We proposed a Concept called “intentional direction (ITD)” for estimating the users walking intention by analyzing the signal of a 6-axis force/torque sensor which is fixed to the handle of 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. Therefore, A universal joint driven by two DC motors was designed to improve the stability of cane robot by controlling the posture of the stick. 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.

Virtual friction model for control of cane robot

A cane-type robot called intelligent cane has been developed to support the elderly during walking. By supporting a part of a users body weight, the cane robot aims to reduce a load applied to a users affected leg. Therefore, while the users 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 users 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.