Xuanping Cai

Teleoperation of robots via the mobile communication networks

Internet-based teleoperation is becoming an important research field in robotics. Most of existing works employed the wired Internet or wireless local area network to transmit signals, which largely limited the movement of the robots. This paper presented a teleoperation project based upon mobile communication networks. Using mobile networks as the wireless transmission media free robots from space restriction, which is favorable for long distance and wide area tasks. But compared with the wired Internet, mobile network has much narrower bandwidth and thus is subject to longer random time-delays in data transfer, which leads to more difficult design of the controller. In despite of severe network environment, the stability of the system is guaranteed first. With information acquisition from multi sensors fixed on robots, bilateral teleoperation with real-time haptic and video feedback is provided. Especially a method has been developed to transfer smooth video stream in mobile networks based on experimental investigation and comparison of existing methods for real-time video transfer. The operator can control robots via various methods such as mobile handset, joystick, speech, etc. An experiment of robots formation was carried out to verify the efficiency of the proposed project

Distributed target tracking with energy consideration using mobile sensor networks

This paper presents a fully distributed algorithm for target tracking using a mobile sensor network. It tries to maintain the target being visible to the mobile network all the time while consuming as little motion energy as possible. Meanwhile the network connectivity is maintained. At every time, only the nodes around the target are activated while other nodes keep idle. Certain functions are defined to quantify the main aspects in the tracking such as the target escaping probability and the network connectivity status. They transform the tracking into a multi-objective optimization problem. To solve this global problem, a local motion strategy is proposed. Simulation results show that our algorithm yields good performance.

Detection of moving targets with a moving camera

In this paper we propose a new method of detecting moving objects from a moving camera based on SIFT(The Scale Invariant Feature Transform) features matching and dynamic background modeling. Firstly, feature points are extracted by SIFT algorithm to compute the affine transformation parameters of camera motion, and guided by RANSAC to remove the outliers. We adopt background subtraction approach to detect moving objects, with shadow and ghost removing. The robustness of SIFT Features matching and the validity of picking out outliers by a RANSAC algorithm make the parameters of affine transform model to be computed accurately, and by the background subtraction approach with dynamically-updated background model, foreground objects can be detected perfectly. Experimental results demonstrate that our algorithm can detect moving objects accurately, and keep the integrity of foreground objects, comparing with optical flow method.

Multi-robot formation control using potential field for mobile ad-hoc networks

Mobile ad-hoc networks are characterized by self-organization, rapid deployment and fault tolerance, however of limited communication range and frequent topology change. For a multi-robot formation supported by mobile ad-hoc networks, when the robots change their formation to avoid obstacles or for other purposes, a robot may easily lose its wireless connection with the network if it goes beyond the communication range. The wireless connections among all the robots must be maintained during their motion. To address this problem, we propose an environmental potential field model which includes a special attractive force determined by the inter-robot distances, in addition to the classical attractive force and the repulsive forces, respectively, defined by the goal and obstacles. Simulations have been conducted to verify the proposed method, and the results demonstrate that our approach can effectively control the change of the formation of a multi-robots system in mobile ad-hoc networks

System identification and attitude control of a small scale unmanned helicopter

This paper copes with the problem of identifying the attitude dynamics of a small scale helicopter using the frequency sweep technology based on the flight data collected near the hovering condition. The frequency domain responses of a helicopter in the lateral, longitudinal and yaw channels are analysed by the partial coherence method, and the transfer functions are obtained by the weighted fitting method. The proposed method can identify the attitude dynamics including the actuator dynamics using the flight data only without carrying out any additional ground experiments. The models identified are verified by comparing model outputs with the experimental data on a small scale helicopter in our lab. We also carried out experiments on the attitude control of the helicopter to further validate the identified models.

An improved method for multi-robot cooperative localization based on relative bearing

The problem of multi-robot cooperative localization based on relative bearings is researched in this paper. Relative bearings of different robots are fused with motions to improve the localization accuracy of robots. We analyse the situations about relative positions of the robots and their motion trajectories. Some relative positions and motion trajectories of the robots easily lead to not-converged localization results. We present an improved method to overcome the fault. The robust and practicability of localization are greatly increased. Simulation results prove the method is effective in dealing with the cooperative localization problem.

Nonlinear system and control of the model-scale helicopter

A nonlinear model and control of a small-scale helicopter near hovering are investigated. Aiming at the characteristics of the model helicopter, the stabilizer bar dynamics is studied, and the tail rotor with the electronic gyro is discussed in detail. In addition, the main rotor inflow dynamics is modeled basing on the three-state nonlinear Pitt/Peters model. Then, a simplified nonlinear model is proposed for system identification and controller design. It is proved that the attitude-heave subsystem can be linearized by the dynamic feedback linearization technique. So, we conclude that the full nonlinear model can also be feedback linearized.

Dynamic visual servoing of a small scale autonomous helicopter in uncalibrated environments

This paper presents a novel adaptive controller for image-based visual servoing of a small autonomous helicopter to cope with uncalibrated camera parameters and unknown 3-D geometry of the feature points. The controller is based on the backstepping technique but differs from the existing backstepping-based methods because the controller maps the image errors onto the actuator space via a depth-independent interaction matrix to avoid estimation the depth of the feature points. The new design method makes it possible to linearly parameterize the closed-loop dynamics by the unknown camera parameters and coordinates of the feature points in the three dimensional space so that an adaptive algorithm can be developed to estimate the unknown parameters and coordinates on-line. Two potential functions are introduced in the controller to guarantee convergence of the image errors and to avoid trivial solutions of the estimated parameters. The Lyapunov method is used to prove the asymptotic stability of the proposed controller based on the nonlinear dynamics of the helicopter. Simulations have been also conducted to demonstrate the performance of the proposed method.

Redeployment for mobile wireless sensor networks

Guarantied connectivity and coverage is the goal of redeployment in wireless sensor network, which is constrained by limited sensor resources and limited sensor transmission capability. To solve fragmentation in sparse networks, a DFS_LF (Depth-First-Search_ Leader-Follower) algorithm is applied. By searching the nearest sensor node to a virtual collective object as a leader node a tracking chain can be formed by using of Leader-Follower method. To coverage holes in dense networks, an algorithm based on RHR_C (Right-Hand-Rule_Centroid) is adopted. RHR is used to find triangle-shaped communication holes (the relationship between the communication hole and sensing coverage ratio can be identified theoretically), and then Centroid method is used to fill those holes. Simulation results proved the validity of presented algorithms.

Nuclei enhancement and segmentation in color cervical smear images

Cell image segmentation is one of the hot topics in medical image processing. Most of the classical cell image segmentation algorithms perform the segmentation directly on the original image and result in the loss of the cell nuclei with low intensity contrast. To solve this problem, this paper presents a novel nuclei segmentation method. Based on analyzing the characteristics of the cell nuclei, we first enhance the nuclei according to their unique features in the image. The proposed nuclei enhancement method combines the intensity and the color information of the image, and is thus effective to enhance the nuclei with relatively low intensity contrast. Then, the morphological reconstruction is employed to extract the regional maxima of the enhanced image, and several shape description parameters are finally used to screen out the true cell nuclei from the extracted regions. Experiments have been performed on real cervical smear images, and the results validate the effectiveness of the proposed method for nuclei segmentation in cervical smear images.