Shupeng Lai

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.

Development of an Unmanned Helicopter for Vertical Replenishment

This paper presents an intelligent and robust guidance, navigation and control solution for a rotary-wing UAV to carry out an autonomous cargo transportation mission between two moving platforms. Different from the conventional GPS/INS-only navigation scheme, this solution also integrates sophisticated Lidar and vision systems capable of precisely locating cargo loading and unloading positions. Besides, another complementary GPS/INS system is set up on the moving platforms with communication to the unmanned helicopter so that the controlled UAV is able to follow the dynamic platforms with good tracking performance. The whole system has been successfully implemented, and with its superb performance the Unmanned Systems Research Group from the National University of Singapore won the first place in the final round of the rotary-wing category competition of the 2nd AVIC Cup — International UAV Innovation Grand Prix 2013.

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.

Autonomous Navigation of UAV in Foliage Environment

This paper presents a navigation system that enables small-scale unmanned aerial vehicles to navigate autonomously using a 2D laser range finder in foliage environment without GPS. The navigation framework consists of real-time dual layer control, navigation state estimation and online path planning. In particular, the inner loop of a quadrotor is stabilized using a commercial autopilot while the outer loop control is implemented using robust perfect tracking. The navigation state estimation consists of real-time onboard motion estimation and trajectory smoothing using the GraphSLAM technique. The onboard real-time motion estimation is achieved by a Kalman filter, fusing the planar velocity measurement from matching the consecutive scans of a laser range finder and the acceleration measurement of an inertial measurement unit. The trajectory histories from the real-time autonomous navigation together with the observed features are fed into a sliding-window based pose-graph optimization framework. The online path planning module finds an obstacle-free trajectory based the local measurement of the laser range finder. The performance of the proposed navigation system is demonstrated successfully on the autonomous navigation of a small-scale UAV in foliage environment.

An efficient UAV navigation solution for confined but partially known indoor environments

This paper presents a robust and efficient navigation solution for a quadrotor UAV to perform autonomous flight in a confined but partially known indoor environment. The main sensors used onboard of the UAV are two scanning laser range finders and an inertial measurement unit. When the indoor environment is structured and the coordinates of its key corner features are known, the UAV planer position can be efficiently calculated via the measurements from the first horizontally scanning laser range finder. The height of the UAV with respect to the ground can be robustly estimated by the second laser scanner which is mounted orthogonally to the first. Besides, this work also adopts a robust and perfect tracking control method with integral action to enable the UAV to track any smooth 3-D trajectories responsively and precisely. All computation is done onboard by an ARM-based embedded computer with limited processing power. The whole system was successfully tested in the 2013 Singapore Amazing Flying Machine Competition and helped the Unmanned Aircraft Systems Group from the National University of Singapore win the overall championship in the fully autonomous category.

Vision-based autonomous flocking of UAVs in unknown forest environment

This paper studies tandem flocking of a team of unmanned aerial vehicles (UAVs) equipped with limited range sensors exploring an obstacle-rich GPS-denied environment such as a forest or urban canyon. There is no communication between UAVs and the follower can only estimate its leaders relative position by its on-board camera. A vision-based leader-follower flocking strategy is proposed to achieve this kind of flocking in unknown cluttered environments. The leader UAV explores its way to reach a given goal position and the follower UAV follows its corresponding leader UAV via on-board camera and avoid obstacles at the same time. The simulation of a team of six UAVs demonstrates the effectiveness of our proposed flocking strategy in a forest environment.

3D motion planning for UAVs in GPS-denied unknown forest environment

In this paper, a decomposition hierarchic on-line motion planning approach consisting of path planning and trajectory generation is proposed for VTOL UAVs to fly in a GPS-denied unknown obstacle-rich environment such as forest and urban canyon. A closed-loop 3D path planning based on A* search algorithm is used to generate collision-free path and a 3D on-line trajectory generation based on maneuver automaton methods is used to generate a collision-free reference trajectory. The simulation and experiment on a VTOL UAV demonstrate the effectiveness of the proposed motion planning approach.

Drones for cooperative search and rescue in post-disaster situation

In this work, we report our solutions to the problems given in the 2014 International Micro Aerial Vehicle Competition, held in Delft, the Netherlands, August 2014, which involves using micro air vehicles in urban post-disaster search and rescue missions. Solutions to all key mission elements of the competition, including real-time map stitching, indoor navigation and roof-top perching, are documented and highlighted in this manuscript. The proposed solutions are successfully demonstrated in the competition and help us win the championship.

Relaxed formation in cluttered environments using rotor-craft UAV

Though multi-agent formation and consensus have been studied intensively recently, very few of the research focuses on their engineering realization using rotor-craft unmanned air vehicle (UAV) as the basic platform. Some assumptions in many theoretical study present challenges in engineering realization, such as the over-simplified dynamic model or sensor model of each agent. In this paper, we present an engineering approach of path planning and trajectory generation based on the model predictive control (MPC) with implementations on small-size, low-cost rotor-craft UAV platform. The proposed method presents a practical solution to the low level path planning and obstacle avoidance problem while opening possibilities for other high level mission planning logic. Based on this method, a study on relaxed formation with two quad-rotor UAV in cluttered environment is presented without making any idealized assumptions in measurement, communication and control.

High-Precision Multi-UAV Teaming for the First Outdoor Night Show in Singapore

Advancement in the development of automation in aerial robotics has created endless applications today by utilizing autonomous drones, or in other words, unmanned aerial vehicles (UAVs). Motivated ...