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Aerial Grasping with a Lightweight Manipulator Based on Multi-Objective Optimization and Visual Compensation
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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, visual trajectory tracking and kinematic compensation. Trajectory planning for aerial grasping control is formulated as a multi-objective optimization problem, while motion constraints and collision avoidance are considered in the optimization. A genetic method is applied to obtain the optimal solution. A kinematic compensation-based visual trajectory tracking is introduced to address the coupled affection between the manipulator and octocopter, with the advantage of discarding the complex dynamic parameter calibration. Finally, several experiments are performed to verify the effectiveness of the proposed approach.
Title: Aerial Grasping with a Lightweight Manipulator Based on Multi-Objective Optimization and Visual Compensation
Description:
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, visual trajectory tracking and kinematic compensation.
Trajectory planning for aerial grasping control is formulated as a multi-objective optimization problem, while motion constraints and collision avoidance are considered in the optimization.
A genetic method is applied to obtain the optimal solution.
A kinematic compensation-based visual trajectory tracking is introduced to address the coupled affection between the manipulator and octocopter, with the advantage of discarding the complex dynamic parameter calibration.
Finally, several experiments are performed to verify the effectiveness of the proposed approach.
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