Jong-Hann Jean

An adaptive control scheme for coordinated multimanipulator systems

The problem of adaptive coordinated control of multiple robot arms transporting an object is addressed. A stable adaptive control scheme for both trajectory tracking and internal force control is presented. Detailed analyses on tracking properties of the object position and velocity and the internal forces exerted on the object are given. It is shown that this control scheme achieves satisfactory tracking performance without using the measurement of contact forces and their derivatives. It can be shown that this scheme can be realized by decentralized implementation to reduce the computational burden. Moreover, some efficient adaptive control strategies can be incorporated to reduce the computational complexity. >

Robust Visual Servo Control of a Mobile Robot for Object Tracking Using Shape Parameters

In this paper, we present the development of a robust visual servo system for object tracking applications of a nonholonomic mobile robot. The system mainly consists of an adaptive shape tracking algorithm and a robust visual servo controller. The adaptive shape tracking algorithm is designed to automatically detect the shape contours of moving objects, extract the shape parameters, and continuously track the object in shape parameter space. Based on direct measurements of the shape parameters, the visual servo controller is designed using the sliding mode control technique. Through a Lyapunov-based stability analysis, a sufficient condition on the selection of control gains to achieve the tracking goal in finite time is provided, and simulation and experimental tests of the proposed approach are illustrated.

Adaptive force control of single-link mechanism with joint flexibility

An adaptive force control, scheme is presented that enables a single-link mechanism with joint flexibility to track a desired force trajectory. A dynamic model of the link system is derived, based on which a two-stage controller is constructed. It is shown that although all the system parameters including environment stiffness are unknown except for some of their bounds, all signals inside the closed-loop system remain uniformly bounded. Moreover, the force tracking error is driven to zero asymptotically. Simulation examples are provided to demonstrate the effectiveness of the proposed controller. >

Voting-Based Motion Estimation for Real-Time Video Transmission in Networked Mobile Camera Systems

In a video-based surveillance system, a mobile camera can provide dynamical and wider monitoring range and the video data transmitted from cooperative mobile cameras can be used to actively detect the objects of interest. However, it is a difficult task to accurately detect the moving objects from the image frames captured by the mobile cameras and the data flow of surveillance video from multiple cameras could be huge. The camera motion usually causes the shifting of static background as well as the moving objects in the captured image frames. In order to correctly estimate the motion of moving objects, a voting-based motion estimation algorithm is proposed to process the image frames captured by the mobile camera. Based on the estimation, a content-based video transmission mechanism is then implemented to further effectively decrease encoding cost and bandwidth utilization. The overall approach consists of voting-based motion estimation, moving object edges detection and content-based sampling coding at temporal and spatial scales. Without knowing the prior knowledge of camera motion, the motion estimation algorithm only utilizes the shifting information of edges of static background to estimate the camera movement. The shifting information is determined based on the voting decision of several representative regions of interest and the estimated motion is then used to compensate for the visual content obtained from the captured image frames. The proposed algorithms have been experimentally tested on several practical scenarios and it is demonstrated that, under limited network bandwidth, the transmitted image quality can be progressively achieved and the transmission bandwidth utilization can be effectively decreased.

Efficient adaptive hybrid control strategies for robots in constrained manipulation

The authors address the problem of adaptive hybrid controller design for constrained robots, with consideration of computational efficiency. Two efficient control schemes based on Lagrange-Euler and Newton-Euler dynamics formulations are presented. Detailed analyses of tracking properties of joint positions, velocities, and constrained forces are derived for both the Lagrange-Euler approach and the Newton-Euler approach. Although control laws in these two approaches are developed independently, a close connection between them is indicated, which suggests a possible bridge over different general adaptive approaches based on the two dynamics formulations.<<ETX>>

Adaptive visual tracking of moving objects modeled with unknown parameterized shape contour

The paper presents a new approach to establish a visual tracking system which can automatically detect the shape contours of moving objects, extract their shape parameters, and continuously track locations of these moving objects in the shape parameter space. The system consists of a robust shape detection algorithm based on the randomized Hough transform (RHT) method and an adaptive object tracking algorithm. The paper demonstrates that, through the combination of a motion detector and the RHT method, the resultant shape detection algorithm is computationally efficient and is robust to noise and object occlusion. On the other hand, the tracking algorithm tracks the shape contours and updates the shape parameters corresponding to the translational, rotational, and scaling motion of moving objects. The tracking algorithm uses a decomposition of the parameter space into lower dimensional subspaces for computational efficiency. Finally the paper provides several simulation and experiment results to validate the new approach.

Development of a patrol robot for home security with network assisted interactions

In this paper we present the development of a patrol robot system for home security with some considerations on its interaction functionalities. The system integrates a variety of sensors to gather environmental information and detect abnormal events including fire alarm, intruder alert and lethal gas leakage. To facilitate a security robot to live with people in a home environment, we implement some dedicated human-robot interactions, including a face mask with several facial expressions and a force feedback steering wheel controller. All of the sensor measurements and the dedicated interactions can be remotely accessed via the Internet. We further design an indoor patrol algorithm that can autonomously command the mobile robot to move randomly, avoid obstacles, or steer along a wall baseline based on ultrasonic and vision data fusion. Finally, we apply the patrol robot system to patrol the second floor of EE building of our campus and provide several experimental results for validating its performance.

Robust visual servo control of a mobile robot for object tracking in shape parameter space

In this paper, we develop a robust visual servo system for object tracking applications of a nonholonomic mobile robot. The system mainly consists of an adaptive shape tracking algorithm and a robust visual servo controller. The adaptive shape tracking algorithm is designed to automatically detect the shape contours of moving objects, extract the shape parameters, and continuously track the object in shape parameter space. Based on direct measurements of the shape parameters, the visual servo controller is designed by using the sliding mode control technique and is robust to uncertainties of the objects motion. Through a Lyapunov-based stability analysis, a sufficient condition on selection of control gains to achieve the tracking goal in finite time is provided.

Zoom-based head tracker in complex environment

In this paper, we establish a nearly real-time surveillance tracking system, which is able to detect any person who intrudes to a prohibited area and lock his head image at the scene center. The entire underlying algorithm consists of a motion detector, an elliptical head tracking algorithm, auto-zooming ability, and a VPDA filter which is modified by probabilistic data association filter (PDA filter). The system operates about 35 ms and actively controls the camera platform pan and tilt motion to track a person in real environment.

Development of an indoor patrol robot based on ultrasonic and vision data fusion

In this paper we present the development and implementation of a patrol robot for indoor environments. First, we propose an indoor patrol strategy by using ultrasonic sensors. According to the gathered range information of the environment, we apply the wall-following strategy to design of patrol rules for determining the navigation commands of the patrol robot. Then we design a steering controller based on the potential field method to drive the patrol robot moving along the wall baselines. In addition, we propose another navigation strategy by using ultrasonic and vision data fusion to improve the accuracy and robustness of the sensing system. We implement a visual navigation controller to successfully steer the patrol robot following the wall and keeping a certain distance to the wall.