Xiangxu Dong

A Robust Real-Time Embedded Vision System on an Unmanned Rotorcraft for Ground Target Following

In this paper, we present the systematic design and implementation of a robust real-time embedded vision system for an unmanned rotorcraft for ground target following. The hardware construction of the vision system is presented, and an onboard software system is developed based on a multithread technique capable of coordinating multiple tasks. To realize the autonomous ground target following, a sophisticated feature-based vision algorithm is proposed by using an onboard color camera and navigation sensors. The vision feedback is integrated with the flight control system to guide the unmanned rotorcraft to follow a ground target in flight. The overall vision system has been tested in actual flight missions, and the results obtained show that the overall system is very robust and efficient.

Development of an Unmanned Coaxial Rotorcraft for the DARPA UAVForge Challenge

In this paper, we present a comprehensive design for a fully functional unmanned rotorcraft system: GremLion. GremLion is a new smallscale unmanned aerial vehicle (UAV) concept using two contra-rotating rotors and one cyclic swash-plate. It can fit within a rucksack and be easily carried by a single person. GremLion is developed with all necessary avionics and a ground control station. It has been employed to participate in the 2012 UAVForge competition. The proposed design of GremLion consists of hardware construction, software development, dynamics modeling and flight control design, as well as mission algorithm investigation. A novel computer-aided technique is presented to optimize the hardware construction of GremLion to realize robust and efficient flight behavior. Based on the above hardware platform, a real-time flight control software and a ground control station (GCS) software have been developed to achieve the onboard processing capability and the ground monitoring capability respectively. A GremLion mathematical model has been derived for hover and near hover flight conditions and identified from experimental data collected in flight tests. We have combined H1 technique, a robust and perfect tracking (RPT) approach, and custom-defined flight scheduling to design a comprehensive nonlinear flight control law for GremLion and successfully realized the automatic control which includes take-off, hovering, and a variety of essential flight motions. In addition, advanced mission algorithms have been presented in the paper, including obstacle detection and avoidance, as well as target following. Both ground and flight experiments of the complete system have been conducted including autonomous hovering, waypoint flight, etc. The test results have been presented in this paper to verify the proposed design methodology.

A Robust Real-Time Vision System for Autonomous Cargo Transfer by an Unmanned Helicopter

Motivated by the 2013 International UAV Innovation Grand Prix, we design and implement a real-time vision system for an unmanned helicopter autonomously transferring cargoes between two platforms. In the competition, four cargoes are initially placed inside four circles on one platform, respectively. They are required to be transferred one by one into the four circles on the other platform. This paper presents the core algorithms of the proposed vision system on ellipse detection, ellipse tracking, and single-circle-based position estimation. Experiments and the great success of our team in the competition have verified the efficiency, accuracy, and robustness of the algorithms. Our team was ranked first in the final round competition.

Vision-aided Estimation of Attitude, Velocity, and Inertial Measurement Bias for UAV Stabilization

This paper studies vision-aided inertial navigation of small-scale unmanned aerial vehicles (UAVs) in GPS-denied environments. The objectives of the navigation system are to firstly online estimate and compensate the unknown inertial measurement biases, secondly provide drift-free velocity and attitude estimates which are crucial for UAV stabilization control, and thirdly give relatively accurate position estimation such that the UAV is able to perform at least a short-term navigation when the GPS signal is not available. For the vision system, we do not presume maps or landmarks of the environment. The vision system should be able to work robustly even given low-resolution images (e.g., 160 ×120 pixels) of near homogeneous visual features. To achieve these objectives, we propose a novel homography-based vision-aided navigation system that adopts four common sensors: a low-cost inertial measurement unit, a downward-looking monocular camera, a barometer, and a compass. The measurements of the sensors are fused by an extended Kalman filter. Based on both analytical and numerical observability analyses of the navigation system, we theoretically verify that the proposed navigation system is able to achieve the navigation objectives. We also show comprehensive simulation and real flight experimental results to verify the effectiveness and robustness of the proposed navigation system.

Autonomous navigation of UAV in forest

This paper presents a navigation system that enables small-scale unmanned aerial vehicles to navigate autonomously in foliage environment without GPS using a 2D laser range finder. The navigation framework consists of real-time onboard motion estimation and trajectory smoothing using pose graph optimization, real-time dual layer control. In particular, onboard real-time motion estimation is achieved in a Kalman filter, fusing the planar velocity measurement from scan matching of laser range finder and the acceleration measurement of inertial measurement unit. The trajectory histories from the real-time autonomous navigation together with the observed features are fed into a pose-graph optimization framework. Poses in a sliding window are optimized using GraphSLAM technique. The inner loop of a quadrotor is stabilized using a commercial autopilot while the outer loop control is implemented using robust perfect tracking. The performance of the navigation system is demonstrated on the successful autonomous navigation of a small-scale UAV in forest. Consistent mapping of the environment in indoor and outdoor scenarios are achieved by projecting all the scan measurement on the post-optimized trajectory with GraphSLAM.

Distributed Formation and Reconfiguration Control of VTOL UAVs

In this brief, a novel distributed cascade robust feedback control approach is proposed for formation and reconfiguration control of a team of vertical takeoff and landing (VTOL) unmanned air vehicles (UAVs). This approach is based on dynamic communication network. It guarantees intervehicle collision avoidance and considers dynamic constraints of UAVs. In the outer loop of the cascade formation control, a potential field approach is used to generate a desired velocity for each UAV, which ensures that the team of UAVs can perform formation flying, formation rotating and reconfiguration, avoid intervehicle collision, as well as track a specified virtual leader. In the inner loop of the cascade formation control, the velocity of each UAV is designed to track its desired velocity generated by the outer loop, subject to dynamic constraints. The proposed approach is demonstrated via both simulation and flight test.

Development of a comprehensive software system for implementing cooperative control of multiple unmanned aerial vehicles

In this work, we focus on establishing a framework and developing a comprehensive real-time software platform for verifying and realizing flight coordination among multiple unmanned aerial vehicles (UAVs). The framework is capable of providing flexible architecture for design of cooperative control laws. The overall software platform incorporates the onboard real-time software for UAVs and that for the ground control station. It employs a distributed architecture to facilitate the deployment of experiments with multiple unmanned vehicles, efficient monitoring and commanding the UAVs from the ground station. The system has been successfully tested in the hardware-in-the-loop simulation and in actual flight formation experiment involving multiple UAVs.

Vision-based formation for UAVs

In this paper, we present a vision-based relative sensing system for UAVs to realize leader-follower formation flight without inter-vehicle communication. A monocular camera is mounted on the follower to detected the leader and measure the relative distance by using the geometry information of the leader without artificial markers. The measured relative distance is utilized to estimate the velocity and acceleration of the leader under the quasi-steady states assumption. Experimental results show that the proposed sensing system is capable of achieving the vision-based leader-follower formation flight.

Cascaded control of 3D path following for an unmanned helicopter

The objective of the paper is to design the control system of following a predefined 3D path while maintaining a specified flight speed and considering the timing constraint. This can be accomplished by a cascaded solution framework based on theoretical dynamic error modeling. The controller for each loop can thus be designed separately so that the design problem is simplified and the control system can be implemented easily in pratice. A promising performance has be demonstrated by an accurate nonlinear simulation at current stage.

Search and Rescue Using Multiple Drones in Post-Disaster Situation

We present the development and application of multiple autonomous aerial vehicles in urban search and rescue missions. The missions are designed by the 2014 International Micro Aerial Vehicle Competition, held in Delft, the Netherlands, August 2014. Different mission tasks are identified for search and rescue missions, such as aerial photography, low altitude flight in urban environment, indoor navigation and rooftop landing. These tasks are all of paramount importance for rescuers in a disaster-hit place. We have designed a team of micro aerial vehicles with specific configurations to meet the mission requirements. A range of key technologies have been developed, including robust controller design, real-time map stitching, indoor navigation and roof-top perching. The proposed solutions are successfully demonstrated in the competition.