Abstract:Autonomous grasping with an aerial manipulator in the applications of aerial transportation and manipulation is still a challenging problem because of the complex kinematics/dynamics and motion constraints of the coupled rotors-manipulator system. The paper develops a novel aerial manipulation system with a lightweight manipulator, an X8 coaxial octocopter and onboard visual tracking system. To implement autonomous grasping control, we develop a novel and efficient approach that includes trajectory planning, v… Show more
“…Therefore, the force interaction can be regarded as a significant disturbance, and the research on this operation mainly focuses on the center of gravity compensation or the grasping path planning. Haoyao Chen et al formulated the trajectory planning for aerial grasping control as a multi-objective optimization problem, and introduced a vision-based trajectory compensation and tracking control method to address the external disturbance and the coupled affection between the manipulator and the octocopter [ 10 ]. Guangyu Zhang et al designed a UAM platform and proposed a controller that could compensate for the shift in the system’s center of mass, caused by the movement of the manipulator [ 11 ].…”
Section: Related Workmentioning
confidence: 99%
“…The research of UAM applications has gained some achievements in the last decade, including grabbing stationary or moving objects [ 10 , 11 ], picking up and transporting goods [ 12 , 13 , 14 ], inspecting infrastructure [ 15 , 16 ], and installing and retrieving equipment [ 17 , 18 , 19 , 20 ]. Continuous contact operations cause the UAM to lose its degree of freedom in a specific direction, so the stability control of the UAM can be more complicated.…”
Contact force control for Unmanned Aerial Manipulators (UAMs) is a challenging issue today. This paper designs a new method to stabilize the UAM system during the formation of contact force with the target. Firstly, the dynamic model of the contact process between the UAM and the target is derived. Then, a non-singular global fast terminal sliding mode controller (NGFTSMC) is proposed to guarantee that the contact process is completed within a finite time. Moreover, to compensate for system uncertainties and external disturbances, the equivalent part of the controller is estimated by an adaptive radial basis function neural network (RBFNN). Finally, the Lyapunov theory is applied to validate the global stability of the closed-loop system and derive the adaptive law for the neural network weight matrix online updating. Simulation and experimental results demonstrate that the proposed method can stably form a continuous contact force and reduce the chattering with good robustness.
“…Therefore, the force interaction can be regarded as a significant disturbance, and the research on this operation mainly focuses on the center of gravity compensation or the grasping path planning. Haoyao Chen et al formulated the trajectory planning for aerial grasping control as a multi-objective optimization problem, and introduced a vision-based trajectory compensation and tracking control method to address the external disturbance and the coupled affection between the manipulator and the octocopter [ 10 ]. Guangyu Zhang et al designed a UAM platform and proposed a controller that could compensate for the shift in the system’s center of mass, caused by the movement of the manipulator [ 11 ].…”
Section: Related Workmentioning
confidence: 99%
“…The research of UAM applications has gained some achievements in the last decade, including grabbing stationary or moving objects [ 10 , 11 ], picking up and transporting goods [ 12 , 13 , 14 ], inspecting infrastructure [ 15 , 16 ], and installing and retrieving equipment [ 17 , 18 , 19 , 20 ]. Continuous contact operations cause the UAM to lose its degree of freedom in a specific direction, so the stability control of the UAM can be more complicated.…”
Contact force control for Unmanned Aerial Manipulators (UAMs) is a challenging issue today. This paper designs a new method to stabilize the UAM system during the formation of contact force with the target. Firstly, the dynamic model of the contact process between the UAM and the target is derived. Then, a non-singular global fast terminal sliding mode controller (NGFTSMC) is proposed to guarantee that the contact process is completed within a finite time. Moreover, to compensate for system uncertainties and external disturbances, the equivalent part of the controller is estimated by an adaptive radial basis function neural network (RBFNN). Finally, the Lyapunov theory is applied to validate the global stability of the closed-loop system and derive the adaptive law for the neural network weight matrix online updating. Simulation and experimental results demonstrate that the proposed method can stably form a continuous contact force and reduce the chattering with good robustness.
“…Owing to their extensive applications, many recent works have focused on developing effective aerial manipulation systems (AMSs) [49]. As a result, a variety of base platforms [99,50,18] and arms with different number of degrees-of-freedom [49,113] have been proposed to develop efficient and practical aerial manipulation systems. An emerging trend in aerial manipulation also includes reforming the arm types from rigid-link robots to soft [107] and continuum ones [106] to improve their operational capabilities.…”
<p>Aerial manipulation systems (AMSs) are highly coupled nonlinear systems which have attracted significant attention of researchers and industries due to their applications. However, the progress has been slow in part due to the extreme level of nonlinearities which makes their modeling and control quite challenging. </p>
<p>In the first phase, to get insight into the dynamics and control of AMSs, conventional AMSs with rigid-link arms were modeled. Next, different control approaches for conventional AMSs control were proposed and the behavior of the system in the presence of different control schemes was compared in terms of accuracy, efficiency, stability and robustness. Four proposed control methods for conventional AMSs included (i) inverse dynamic, (ii) hierarchical linear-quadratic regulator (LQR), (iii) sliding mode, and (iv) semi-optimal nonlinear control techniques. Based on this preliminary study, a controller was selected for its formulation for the next phase of the project. </p>
<p>In the next phase, the research focused on modeling and control of aerial continuum manipulation systems (ACMSs) that are distinguished from conventional aerial manipulation systems (AMSs). In ACMS, typical rigid-link arms are replaced with continuum robotic arms to boost their advantages. Using continuum arm extends the capability of AMSs by increasing their compliance and dexterities. Also, AMSs with continuum arms are more compatible to work in cluttered and less structured environments. However, modeling and control of such complex and nonlinear system is much more challenging compared to those of conventional rigid AMSs. </p>
<p>The reported research in this thesis is continuation of the ACMS initiative in Robotics, Mechatronics and Automation Laboratory at Ryerson University. In this research, a decoupled model for ACMS is formulated for the first time followed by a decoupled control technique for this system. Cosserat rod theory was adopted for decoupled dynamic modeling of ACMS. Also, a robust adaptive control approach was proposed to cope with the problem of complexity and high level of modeling uncertainties. The stability of the proposed control method was proven using Lyapunov stability theorem. </p>
<p>Subsequently, to consider interactions between aerial vehicle and continuum arm, coupled model and control for ACMS were developed. Coupled dynamic modeling for ACMSs was formulated based on Euler-Lagrange theory. For this purpose, a general vertical take-off and landing (VTOL) vehicle equipped with a tendon-driven continuum arm was considered. The modeling approach was complemented with a control technique to demonstrate the validity of the proposed method for such a complex system. Both simulation and experimental results were reported to verify the effectiveness of the proposed modeling technique. </p>
<p>Finally, design of the first vision-based adaptive control for ACMSs circumventing the need for a priori knowledge of system dynamic model was proposed. For this purpose, a vision based reduced-order adaptive control scheme was developed. It was shown that using vision feedback in combination with adaptive control method enables effective treatment of nonlinearities, coupling and uncertainties present in typical ACMSs. The method was verified using simulation results. </p>
“…The development of this technology is motivated by interest in reducing the time, cost and risk for human workers associated with the realization of certain tasks in high altitude or difficult access workspaces such as power lines [1,2], chemical plants [3], oil and gas refineries [4], and other infrastructures [5,6]. Recent works in this field have demonstrated the possibility to conduct operations such as object grasping [7][8][9], valve turning [10], sensor installation and retrieval [2,11], contactbased inspection [3,12,13], insulation of cracks and leaks [14], or the realization of other tasks with grippers and other tools [15,16]. Several prototypes and morphologies of manipulators have been specifically developed for their integration in multi-rotors, including multi-joint arms [17,18], dual arm systems [7,10], linear actuators [11], delta manipulators [14], compliant joint arms [2,19,20], long reach aerial manipulators [2,21], or three-arm manipulators used for object grasping and as reconfigurable landing gear [22].…”
This paper presents an aerial manipulation robot consisting of a hexa-rotor equipped with a 2-DOF (degree of freedom) Cartesian base (XY–axes) that supports a 1-DOF compliant joint arm that integrates a gripper and an elastic linear force sensor. The proposed kinematic configuration improves the positioning accuracy of the end effector with respect to robotic arms with revolute joints, where each coordinate of the Cartesian position depends on all the joint angles. The Cartesian base reduces the inertia of the manipulator and the energy consumption since it does not need to lift its own weight. Consequently, the required torque is lower and, thus, the weight of the actuators. The linear and angular deflection sensors of the arm allow the estimation, monitoring and control of the interaction wrenches exerted in two axes (XZ) at the end effector. The kinematic and dynamic models are derived and compared with respect to a revolute-joint arm, proposing a force-position control scheme for the aerial robot. A battery counterweight mechanism is also incorporated in the X–axis linear guide to partially compensate for the motion of the manipulator. Experimental results indoors and outdoors show the performance of the robot, including object grasping and retrieval, contact force control, and force monitoring in grabbing situations.
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