Pei Di

Human-Walking-Intention-Based Motion Control of an Omnidirectional-Type Cane Robot

An intelligent cane robot is designed for aiding the elderly and handicapped peoples walking. The robot consists of a stick, a group of sensors, and an omnidirectional basis driven by three Swedish wheels. Recognizing the users walking intention plays an important role in the motion control of our cane robot. To quantitatively describe the users walking intention, a concept called “intentional direction (ITD)” is proposed. Both the state model and the observation model of ITD are obtained by enumerating the possible walking modes and analyzing the relationship between the human-robot interaction force and the walking intention. From these two models, the users walking intention can be online inferred using the Kalman filtering technique. Based on the estimated intention, a new admittance motion control scheme is proposed for the cane robot. Walking experiments aided by the cane robot on a flat ground and slope are carried out to validate the proposed control approach. The experimental results show that the user feels more natural and comfortable when our intention-based admittance control is applied.

Robust Model-Based Online Fault Detection for Mating Process of Electric Connectors in Robotic Wiring Harness Assembly Systems

Mating a pair of electric connectors is one of the most important steps in a robotic wiring harness assembly system, which can be modeled by static piecewise affine (PWA) systems. To design a fault detection system for this application, a set-membership approach for static PWA systems is proposed, in which parallelotopic approximation of feasible parameter sets is adopted. An online algorithm is obtained to estimate bounds of uncertain transition points of the PWA model. Based on the estimation, a robust online fault detection algorithm is proposed. The robustness and sensitivity of the algorithm are analyzed. The effectiveness of these methods is finally confirmed through experiments.

Motion control of omni-directional type cane robot based on human intention

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.

Study of Fall Detection Using Intelligent Cane Based on Sensor Fusion

A three-wheeled omni-directional cane robot is designed for aiding the elderly walking. A new human fall detection method is proposed based on fusing sensory information from a vision system and a laser ranger finder (LRF). This method plays an important role in the fall-prevention for the cane robot. The human fall model is represented in a 2D space, where the distance between the head and the average leg position is a significant feature to detect the fall. The possibility distribution of this distance is estimated by using Dubois possibility theory. Fall detection is implemented by using a simple rule based on the possibility distribution. The proposed method is confirmed through experiments.

A novel fall prevention scheme for intelligent cane robot by using a motor driven universal joint

In this study, we propose a novel fall prevention scheme for an omni-direction type cane robot by using a DC motor driven universal joint. The cane robot which is driven by three omni-wheels is called Intelligent Cane Robot (iCane). It is designed for aiding the elderly and handicapped people walking as shown in Fig.1. The motion of cane robot is controlled for both normal and abnormal walking conditions. The users 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. For the abnormal walking, we mainly studied the case of users fall down. The center of gravity (COG) of user can be estimated from the angle of an inverted pendulum which represents human dynamic model. Fall prevention algorithm based on the relationship between users COG and the cane is proposed. Because the size of the cane robot is small, when the robot is preventing the user falling down, firstly, the stability of the cane robot should be ensured. A universal joint which is driven by two DC motors is used to reduce the moment causing the cane robot falling over. The proposed method is verified through experiments.

Rail-guided Multi-robot System for 3D Cellular Hydrogel Assembly with Coordinated Nanomanipulation

The 3D assembly of micro-/nano-building blocks with multi-nanomanipulator coordinated manipulation is one of the central elements of nanomanipulation. A novel rail-guided nanomanipulation system was proposed for the assembly of a cellular vascular-like hydrogel microchannel. The system was equipped with three nanomanipulators and was restricted on the rail in order to realize the arbitrary change of the end-effectors during the assembly. It was set up with hybrid motors to achieve both a large operating space and a 30 nm positional resolution. The 2D components such as the assembly units were fabricated through the encapsulation of cells in the hydrogel. The coordinated manipulation strategies among the multi-nanomanipulators were designed with vision feedback and were demonstrated through the bottom-up assembly of the vascular-like microtube. As a result, the multi-layered microchannel was assembled through the cooperation of the nanomanipulation system.

i-Hand: An intelligent robotic hand for fast and accurate assembly in electronic manufacturing

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.

Evolutionary artificial potential field method based manipulator path planning for safe robotic assembly

To design a safe path planning for the manipulator is a key issue during the human worker and manipulator cooperation cell assembly. In this study, a cell assembly system involving human worker and manipulator is designed. According to the camera vision information, the locations of the human worker and the manipulator are calculated, and then the potential field is calculated based on the Artificial Potential Field (APF) method. In order to generate a semi-optimal safe path planning for the manipulator, a criterion is imported to evaluate the path and an Evolutionary Algorithm (EA) is adopted to adjust the parameters to meet this criterion. The effectiveness of these methods is finally confirmed through simulation experiments.

Dynamic modeling and simulation of manipulating deformable linear objects

Deformable linear objects (DLOs) such as cables, hoses and wires are widely used in the real life, electric industries and medical operations. In this paper, we propose a new approach to simulate manipulating DLOs in the robotic assembly. The dynamic 2D deformation of an inextensible linear object is formulated using FEM approach. Based on the model, simulation can be efficiently implemented by matrix computation and numerical solvers for differential equations. The proposed method provides faster computation speed than methods based on differential geometry coordinate systems. Some simulation examples are illustrated to confirm the effectiveness of our methods.

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.