Visual Grasping For Aerial Manipulator Based On Trajectory Optimization And Kinematic Compensation

With the rapid development of aerial robotics,unmanned aerial vehicle(UAV)has been successfully applied in more and more fields.Nowadays,UAVs are already very mature in observation-based applications such as aerial photography.However,there are still many challenges in other fields.Base d on the existing mature algorithms and extensions,more and more researchers have tried and explored the further application of UAVs,including the most representative air transport,air operations and interaction.As a new hot research topic of UAV applications,the study of aerial manipulator system includs flight adaptive robotic arm design,complex system modeling and controller,aerial SLAM,intelligent planning and other related expansion technologies.The research of aerial manipulator system usually focuses on the operation of object grasping.In general,accurate and highly-maneuvering control of aerial manipulator system requires accurate dynamic modeling;however,it is challenging to obtain complete modeling.At present,most of the related researches are based on simulation or in simple environments without obstacles.The existing methods like visual servoing cannot accomplish the collision avoidance task in slightly complicated environments.To solve these problems,a light-weight robotic arm is presented to reduce the dynamic coupling of the system,and furthermore a kinematic aerial grasping method is proposed.The proposed grasping method does not rely on the system dynamics model and thus avoids the difficulty of dynamic parameters' calibration.Because the existing visual servoing solutions are easy to lose tracking the target and cannot work in the complicated environments with obstacles,the dissertation presents a novel visual system to track the target in real time and obtain the target pose by using a monocular vision camera.At the same time,by transforming the trajectory planning problem into an optimization problem with multiple objectives and constraints,NSGA-II multi-objective optimization is used to solve the trajectory planning problem.Another innovative point compared with the existing research is that this dissertation considers the problem of pose variations caused by dynamic and external factors,a trajectory correction scheme and a trajectory tracker based on filtering and time-partitioned interpolation control are proposed to achieve high grasping performance.In this dissertation,the visual grasping methods of aerial manipulator are verified by several experiments.By using the proposed approach,autonomous visual grasping operation with our aerial manipulators system under complicated constraints is performed with satisfied performance.The approach does not depend on the dynamic model,but can still achieve a good performance under some interference with universality.The research in the dissertation can promote the further applications of UAVs.