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Robust Control of a Quadrotor using Takagi-Sugeno Fuzzy Model and an LMI Approach
Hyeonbeom Lee,H. Jin Kim 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10
This paper presents robust control for a quadrotor using TS (Takagi-Sugeno) fuzzy model and an LMI (Linear Matrix Inequality) approach. TS fuzzy model can provide an effective representation of nonlinear systems with a set of local linear models. We present TS fuzzy model for the quarotor which is composed of local linear models valid in different operation points. Also, a state feedback controller is designed based on LMIs with the pole placement method. Simulation results illustrate the more stable tracking performance of the proposed controller in comparison with a conventional LQR controller.
Estimation, Control, and Planning for Autonomous Aerial Transportation
Lee, Hyeonbeom,Kim, H. Jin IEEE 2017 IEEE transactions on industrial electronics Vol.64 No.4
<P>This paper presents estimation and control synthesis for an aerial manipulator to carry an unknown payload. Online estimation is based on parametrization of the aerial manipulator, which consists of a multirotor and a robotic arm. With the estimated physical properties, an augmented adaptive controller is proposed so that the end effector of the robotic arm can track the desired trajectory. Relying on this control structure, finally, we propose a flight motion generation method satisfying the joint angle limitation based on the analysis of the allowable flight area with respect to the joint angle variation. To validate our approach, the simulation results with comparison of conventional adaptive controller are shown. We also perform load carrying experiments using a custom-made aerial manipulator.</P>
Constraint-Based Cooperative Control of Multiple Aerial Manipulators for Handling an Unknown Payload
Lee, Hyeonbeom,Kim, H. Jin IEEE 2017 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS - Vol.13 No.6
<P>This paper presents the planning and control synthesis of cooperative aerial manipulators to carry an unknown object together. The online parameter estimation algorithm is designed to estimate the unknown physical parameters of the common payload such as mass and moment of inertia, without the need of multiaxis force/torque sensors. Based on the augmented adaptive sliding mode controller with the estimated physical parameters, the desired trajectory of each aerial manipulator is generated to track the desired trajectory of corresponding end effector. In order to carry an unknown object safely considering the actuation limit of the hexacopter, we use the task priority to satisfy the unilateral constraints determined by the allowable flight envelope. To validate our approach, the experimental result on a successful transportation by using multiple custom-made aerial manipulators is shown. This result suggests that the proposed approach can be utilized for safe cooperative aerial transportation.</P>
Planning and Control for Collision-Free Cooperative Aerial Transportation
Lee, Hyeonbeom,Kim, Hyoin,Kim, H. Jin IEEE 2018 IEEE transactions on automation science and engine Vol.15 No.1
<P>This paper presents planning and control synthesis for multiple aerial manipulators to transport a common object. Each aerial manipulator that consists of a hexacopter and a two-degree-of-freedom robotic arm is controlled by an augmented adaptive sliding mode controller based on a closed-chain robot dynamics. We propose a motion planning algorithm by exploiting rapidly exploring random tree star (RRT*) and dynamic movement primitives (DMPs). The desired path for each aerial manipulator is obtained by using RRT* with Bezier curve, which is designed to handle environmental obstacles, such as buildings or equipments. During aerial transportation, to avoid unknown obstacle, DMPs modify the trajectory based on the virtual leader–follower structure. By the combination of RRT* and DMPs, the cooperative aerial manipulators can carry a common object to keep reducing the interaction force between multiple robots while avoiding an obstacle in the unstructured environment. To validate the proposed planning and control synthesis, two experiments with multiple custom-made aerial manipulators are presented, which involve user-guided trajectory and RRT*-planned trajectory tracking in unstructured environments.</P><P><I>Note to Practitioners</I>—This paper presents a viable approach to autonomous aerial transportation using multiple aerial manipulators equipped with a multidegree-of-freedom robotic arm. Existing approaches for cooperative manipulation based on force decomposition or impedance-based control often require a heavy or expensive force/torque sensor. However, this paper suggests a method without using a heavy or expensive force/torque sensor based on closed-chain dynamics in joint space and rapidly exploring random tree star (RRT*) that generates the desired trajectory of aerial manipulators. Unlike conventional RRT*, in this paper, our method can also avoid an unknown moving obstacle during aerial transportation by exploiting RRT* and dynamic movement primitives. The proposed planning and control synthesis is tested to demonstrate performance in a lab environment with two custom-made aerial manipulators and a common object.</P>
Concave Wall Surface Tracking for Aerial Manipulator Using Contact Force Estimation Algorithm
Seon-il Lee,Hyeongseok Kim,Uikyum Kim,Hyeonbeom Lee 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
This paper presents a control algorithm of a contact-based inspection for an Unmanned Aerial Vehicle (UAV) manipulator without using a force sensor. The conventional contact-based operation methods for a ground-based manipulator require a force sensor, but the force measurement is noisy on uneven surfaces. The noisy measurement can cause an unstable flight of the UAV when using direct force measurement as an input. To resolve this issue, we design a contact-force estimation algorithm of a UAV and desired trajectory generation algorithm. Contact-force is estimated by using the dynamics of a UAV and IMU sensor. In addition, to track the concave wall safely, we propose a heading-angle alignment algorithm. Through the Gazebo simulation, we show that the proposed method is effective compared to the force-sensor-based existing method.
이상일(Sangil Lee),김표진(Pyojin Kim),김창현(Changhyeon Kim),이현범(Hyeonbeom Lee),김현진(H. Jin Kim) 제어로봇시스템학회 2017 제어·로봇·시스템학회 논문지 Vol.23 No.6
This paper surveys visual odometry technology for unmanned systems. Visual odometry is one of the most important technologies to implement vision-based navigation; therefore, it is widely applied to unmanned systems in recent years. Visual odometry estimates a trajectory and a pose of the system, and it could be classified into the following: 1) stereo vs. monocular, 2) feature-based or indirect vs. direct, and 3) linear vs. nonlinear based on the number of cameras, information attributes, and the optimization process, respectively. In the paper, we discuss the state-of-the-art issues of research activities related to visual odometry and summarize future direction for the research.
김형진(Hyeongjin Kim),이현범(Hyeonbeom Lee) 제어로봇시스템학회 2021 제어·로봇·시스템학회 논문지 Vol.27 No.8
The purpose of autonomous navigation is to reach the destination without collision. Traditionally, mobile robots have used LIDAR, sonar sensors, or stereo cameras to avoid obstacles. However, UAVs suffer from the selection of sensors due to payload capacity. To resolve this issue, we design the method using the only a monocular camera for obstacle avoidance on a quadrotor. In order to obtain the depth images, we use a CNN (Convolutional Neural Network). To improve the depth estimation performance, we develop a data augmentation algorithm of the magnified images especially ranging from 0.5~1 meters. By using the estimated depth image, the desired direction of the quadrotor is set. To validate our proposed algorithm, we conduct experiments with real drones in indoor environments. An analysis of the experiments shows that the proposed method can be utilized for navigation in cluttered environments.