Chun-Hsu Ko

Active and Passive Control of Walk-Assist Robot for Outdoor Guidance

In the currently aging society, walk-assist robots can play an important role in improving the activities of daily living of the elderly. In this paper, we propose a robot walking helper with both passive and active control modes for guidance. From the perspective of human safety, the passive mode adopts a braking control law on the wheels to differentially steer the vehicle. However, if the user walks uphill in the outdoor environment, external forces need to be supplied to the human-walker system. In this paper, we add an active mode to guide the user in situations where the passive control mode alone with user-applied forces is not adequate for guidance. The theory of differential flatness is used to plan the trajectory of control gains within the proposed scheme of the controller. Since the user input force and slope angle of the path are not known a priori , the theory of model predictive control is used to periodically compute the trajectory of these control gains. The simulation and experiment results show that the walk-assist robot, along with the structure of this proposed control scheme, can guide the user to a goal on a slope effectively.

Walk-Assist Robot: A Novel Approach to Gain Selection of a Braking Controller Using Differential Flatness

With the growth of elderly population in our society, technology will play an important role in providing functional mobility to humans. From the perspective of human safety, it is desirable that controllers for walk-assist robots be dissipative, i.e., the energy is supplied by the human to the walker, while the controller modulates this energy, also the motion of the walker, while dissipating this energy. The simplest form of a dissipating controller is a brake, where resistive torques are applied to the wheels proportional to their speeds. The fundamental question that we ask in this paper is how to modulate these proportionality gains over time for the two wheels so that the walker can perform point-to-point motions in the state space. The unique contribution of this paper is a novel way in which the theory of differential flatness is used to plan the trajectory of these braking gains. Since the user input force is not known prior, the theory of model predictive control is used to periodically compute the trajectory of these braking gains. The simulation results show that the walking assist robot, along with the structure of this proposed control scheme, can guide the user to a goal accurately.

Effective Maneuver for Passive Robot Walking Helper Based on User Intention

In response to an aging society, a robot walking helper has come up as a research focus. To be practical for use in daily lives for the elderly, it should be able to follow user intention during maneuver and provide motion assistance when demanded. As quite a number of guidance schemes have been proposed, the studies on maneuver are comparatively few. This paper thus proposes a maneuvering system for the passive type of robot walking helper based on user intention. The proposed system first recognizes motion intention from user-applied force and hip rotation, and then utilizes an assistive control strategy to generate proper braking torque for effective maneuver. Experiments in a real environment are conducted for demonstration.

Control and path planning of a walk-assist robot using differential flatness

With the growth of elderly population in our society, technology will play an important role in providing functional mobility to humans. In this paper, we propose a robot walking helper with both passive and active control modes of guidance. From the perspective of human safety, the passive mode adopts the braking control law on the wheels to differentially steer the vehicle. The active mode can guide the user efficiently when the passive control with user-applied force is not adequate for guidance. The theory of differential flatness is used to plan the trajectory of control gains within the proposed scheme of the controller. Since the user input force is not known a-priori, the theory of model predictive control is used to periodically compute the trajectory of these control gains. The simulation results show that the walking assist robot, along with the structure of this proposed control scheme, can guide the user to a goal effectively.

Walk-assist robot: A novel approach to gain selection of a braking controller using differential flatness

With increasing populations of the elderly in our society, robot technology will play an important role in providing functional mobility to humans. From the perspective of human safety, it is desirable that controllers for walk-assist robots be dissipative, i.e., the energy is supplied from the human to the walker, while the controller modulates this energy. The simplest form of a dissipating controller is a brake, where resistive torques are applied to the wheels proportional to their speeds. The fundamental question that we ask in this brief is how to modulate these proportional gains over time for the two wheels so that the walker can perform point-to-point motions. The unique contribution of this brief is a novel way in which the theory of differential flatness is used to plan the trajectory of these braking gains. Since the user input forces are not known a priori , the trajectory of the braking gain is computed iteratively during the motion. Simulation and experimental results show that the walk-assist robot, along with the structure of this proposed control scheme, can guide the user to reach the goal.

Optimized trajectory planning for mobile robot in the presence of moving obstacles

Navigation and obstacle avoidance are essential for mobile robots. In the dynamic environment, the obstacles may move with varying velocities. It is thus crucial to develop an effective scheme for moving obstacle avoidance. Motivated by this, in this paper, we propose such a scheme based on parametric trajectory planning. With the conditions for collision avoidance formulated as the constraints, a feasible collision-free trajectory is then derived by solving an unconstrained optimization problem. The corresponding control torques for robot governing is calculated using the dynamic model and derived trajectory, with the information about the obstacle not known a priori. Simulations are performed to demonstrate the efficiency of the proposed approach.

Guidance and obstacle avoidance of passive robot walking helper based on receding horizon control

Along with the coming of the aging society, the passive robot walking helper is introduced for providing safe mobility for the elderly, which features continuous energy dissipation from the system with brakes for steering. When this passive walking helper is applied for guidance and obstacle avoidance, it is crucial to determine proper braking torques in accordance with user-applied force for avoiding the obstacles and reaching the desired location. Motivated by it, in this paper, we propose such an approach based on receding horizon control. The proposed approach is efficient in braking torque derivation and allows the walking helper to stop at the goal with parking control. With the desired location to reach, the proposed scheme first plans a smooth path for the walking helper to follow based on Dubins curve [13]. The process of torque derivation is then formulated into solving an optimization problem with constraints that guarantee system passivity. When the walking helper detects the obstacles, the obstacle avoiding strategy is activated to bring it to deviate from them, which is achieved by including the constraints for obstacle avoidance into the optimization process. Simulations and experiments are performed to demonstrate the effectiveness of the proposed approach.

Collision-free guidance for passive robot walking helper

With the increase of aging population, robot walking helpers have been developed to assist the elderly in their daily life. Based on our previous work, a passive robot walking helper (named i-Go) equipped with a guidance strategy, in this paper, we further propose a navigation scheme for obstacle avoidance. The proposed scheme first locates the waypoints in the collision-free areas, and then guides the i-Go to reach the desired target with the specified orientation. Simulations and experiments are performed to verify the effectiveness of the proposed scheme. The results demonstrate that the scheme can guide the user to avoid the obstacles and successfully approach the target with the specified orientation.

Effective control for an upper-body exoskeleton robot using ANFIS

In responding to the coming of an aging society, the exoskeleton robot is of focus, which provides assistance for people with locomotive problems. As the exoskeleton robot is worn by the user, the interaction in between induces several severe challenges, including adequate controller design. To deal with the nonlinearity involved during motion governing, in this paper, we take advantage of the capability of the adaptive network-based fuzzy inference system (ANFIS), and propose an ANFIS-PID controller for the exoskeleton type of robot. Especially, we apply it to a 2-DOF upper-body exoskeleton robot, HAMEXO-I, developed in our laboratory. With the proposed controller, we intend to let HAMEXO-I adaptable for a wide range of users, and able to serve for simple daily activities. Experiments are performed to demonstrate its effectiveness.

Motion and Visual Control for an Upper-Limb Exoskeleton Robot via Learning

The arrival of an aging society brings up many challenges, including the demanding need in medical resources. In responding, the exoskeleton robot becomes one of the focuses, which provides assistance for people with locomotive problems. Motivated by it, our laboratory has developed a wearable upper-limb exoskeleton robot, named as HAMEXO. It is of 2 DOF and intended to provide motion assistance for users in their daily activities. To serve the purpose, HAMEXO is equipped with a visual system to detect objects in the environment, and also a motion controller for its governing. To deal with the coupling involved during the movements of the two joints and the need to adapt to various users, we adopted the learning approach for controller design. Experiments are performed to demonstrate its effectiveness.