Jinjun Rao

Unmanned airships for emergency management

There are keen demands of robotic technologies in management of many kinds of emergencies. In this paper, we argue that unmanned airships present a unique potential in emergency management cycle, and their applications for surveillance, search and rescue, and communication are discussed. To make our lighter-than-air platform an autonomous airship with significant levels of autonomy for emergency management, the hardware infrastructure and software of the flight control system are designed and detailed. Based on a decoupled longitude and latitude dynamic model, the control architecture is developed, and a fuzzy control strategy is applied in mission path following problem. An application case of target searching using the autonomous airship is given and analyzed.

Robotic airship mission path-following control based on ANN and human operator’s skill

Robotic airships have numerous low-speed and low-altitude application potentials. Mission path following is one such application, which, however, presents an autonomy challenge. In this paper, a yawing controller, which is based on artificial neural network (ANN) and human operator skills, is proposed for mission path following of robotic airships. First, the path-following errors based on the operator’s point of view are discussed. Then, a data acquisition system is designed to collect the flight data under manual control, and the data are then processed and used for offline training and validation of a multilayer feed-forward neural network. Finally, the trained neural network is reconstructed in the flight control system for yawing control, and the experimental results confirm the effectiveness of this method. It is also shown that the ANN controller is robust even with wind disturbance.

A flight control and navigation system of a small size unmanned airship

Unmanned airships present an enormous potential for low-speed and low-altitude exploration applications. In order to develop a flight robot based on a small size unmanned remotely controlled airship, a flight and navigation system is presented in this paper. The hardware and software of the system are designed. As the kernel of the system, the flight control and navigation strategies are detailed. On the basis of the airship dynamic model, the architecture of the control system is presented, and the fuzzy controllers are employed and optimized using an improved genetic algorithm. Based on the airship model and the control and navigation strategies, the simulation studies of 3D path tracking problem are given and analyzed.

Low Cost Hand Gesture Learning and Recognition System Based on Hidden Markov Model

Focusing on recognizing some typical gestures based on 3-axis MEMS accelerometer to interact with an application of human-machine interactive game, the hand gesture problem is analyzed firstly, then theory basis of HMM is introduced. In order to obtain training gesture data for HMM, and also to provide a hardware basis for gesture recognition, a low cost data acquisition system hardware is researched and designed. The system can get the acceleration data of user’s gesture and transmit them wirelessly to a personal computer. In the hand gesture recognition approach, k-mean algorithms are applied to cluster and abstract the vector data from sensor. And then the quantized vectors are put into a hidden Markov model to learn and recognize user’s gestures. Finally the gesture recognition library is implemented in C# development environment, and is utilized in a human-machine interactive game application. The results show that the typical gesture emerging in the game can be identified in a high rate, and the user can experience more interest and interaction.

GA-Based Flight Motion Model Parameter Identification of a Subminiature Fixed-Wing Unmanned Aerial Vehicle

Subminiature fixed-wing unmanned aerial vehicles (SUAVs) present an enormous potential for low-altitude exploration applications. In order to develop a robotic SUAV and realize high level of autonomy, the flight motion model of the platform with wingspan of 1.8 m is studied thoroughly. Based on the rectilinear trim flight and small perturbation theory, the linear parametric model is investigated. The flight experiments are designed, and the flight data measurement system is developed to collect the input and output data. Through outliers processing, data smoothing, data fusion, etc, all the required data for parameter identification are figured out. As the estimation method, improvements of GA are detailed, and the comparison of model verification indicates that improved GA has prominent effects in flight motion model parameter identification of SUAV.

Flight control system of a robotic portable unmanned aerial vehicle

Portable fixed-wing Unmanned Aerial Vehicles (PUAV) present enormous potential. In order to develop a robotic PUAV with significant levels of autonomy, the flight control system is studied. The platform is introduced and dynamics model is studied firstly. Then the infrastructure hardware and the architecture of the flight control system are detailed. As the core of the flight control system, the attitude controller using variable fuzzy controller is investigated, and a bilinear interpolation approach is presented to realize quick inference with low computation cost of the embedded micro processor. The flight simulation and experiment validates the performance of the flight control system of PUAV.

Small UAV controlled by an online adaptive fuzzy control system

Since small unmanned helicopter flight attitude control process has strong time-varying characteristics and random disturbances, the conventional control methods with unchanged parameters are often unworkable. An online adaptive fuzzy control system (AFCS) is designed in this paper, in a way that a process model of the plant or its approximation in the form of a Jacobian matrix is not required. An online AFCS implements a simultaneous online tuning of fuzzy rules and the output scale factors of the system. A two-cascade controller is designed with an inner (attitude controller) and outer controller (navigation controller) of the small unmanned helicopter. At last, an attitude controller based on an online AFCS is implemented. The flight experiments show that the proposed fuzzy logic controller provides quick response, small overshoot, high accuracy, robustness and adaptive ability. It satisfies the needs of autonomous flight.

Design of double ducted tilting SUAV navigation system based on multi-sensor information fusion

Recently, the UAV has become the research focus at home and abroad. this paper puts forward a new aircraft type: double ducted tilting Subminiature UAV system, and carries out the research of the navigation system for this suav. This paper puts forward to apply the gyroscope, accelerometer and magnetometer, using kalman filtering algorithm to establish the optimal attitude matrix, namely the best digital platform. The optimal attitude matrix based on this method can avoid the long-term accumulated errors of attitude matrix in conventional integrated navigation. In addition, the paper puts forward kalman algorithm combined with integrated navigation, which can be adjusted according to the motion information of the carrier. Based on this method, the integrated navigation system can gain the best navigation information under different motion state. Finally, this paper proves that the navigation system design based on multisensor information fusion.

An Adaptive Filter for a Small Attitude and Heading Reference System Using Low Cost Sensors

Small Attitude And Heading Reference System (AHRS) based on MEMS are small size, light weight, low power consumption, and low cost by the inclusion of micro sensors. Small AHRS have many potential uses beyond air- and spacecraft applications. However, the MEMS sensors have large noise, bias and scale factor errors due to drift. An extended Kalman filter with adaptive gain was used to build a small AHRS system based on a stochastic model. The adaptive filter tunes its gain automatically based on the system dynamitic sensed by the movement state to yield optimal performance.

Robotic small unmanned aerial vehicle system for disaster information gathering

Small fixed-wing unmanned aerial vehicles (SUAVs) present an enormous potential for low-altitude exploration applications. In order to develop a robotic SUAV with high level of autonomy for disaster information gathering, the flight control and navigation system is presented and the hardware and software are detailed. Then the dynamic model of flight motion of SUAV is studied. As the kernel of the system, the architecture of flight control and navigation strategies are presented, then variable universe fuzzy attitude controller and mission path tracking controller are introduced in detail. The flight experiments for low altitude information gathering using this robotic SUAV are implemented and the flight results are given and analysed.