Coordinated Control of a Free-floating Space Robot for Capturing a Target

Xu, Wenfu; Meng, Deshan; Xu, Chao; Liang, Bin

doi:10.3724/sp.j.1218.2013.00559

Cited by 4 publications

(5 citation statements)

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“…As we mentioned previously, the grasping tasks is a task-priority based behavior. The task-space DOFs [13] are used to describe the required DOFs to accomplish the grasping task; so we define n1, n2, and n3 to represent the task-space DOFs of the endeffector position, the end-effector attitude, and the base attitude constraints, respectively, (herein, for spatial case, n1=n2=n3=3; for planar case, n1=2 and n2=n3=1) [14]. Furthermore, the relationship between the grasping tasks and the minimum task-space DOFs is concluded in Table 1.…”

Section: A Analysis Of Typical Grasping Tasksmentioning

confidence: 99%

“…For the grasping strategies in [12], [14]- [17], all the planning strategies are designed in the free-floating phase, i.e., the space robot has reached the berth position with working in the free-floating mode. So the manipulator DOFs should be greater than or equal to the minimum task-space DOFs, e.g., for grasping targets with controlling the base attitude it needs the manipulator to have redundant DOFs (i.e., at least 9 and 4 DOFs for spatial case and planar case respectively).…”

Section: B Optimal Coordinated Grasping Strategymentioning

confidence: 99%

“…Here, the rotation matrices ω ω ω ω is the angular velocity vector, and ω is the skew-symmetric matrix of ω . Substituting (12) into (14) and integrating it, we can calculate the end-effector and base attitude as…”

Section: Modified Generalized Jacobian Matrixmentioning

confidence: 99%

“…X f f f and the objective function Γ is calculated by using (14) and (16) based on a hypothetical berth position 0h r .…”

Section: E Planning Proceduresmentioning

confidence: 99%

See 3 more Smart Citations

Optimal coordinated planning strategy for space robots grasping targets

Zhang

Liu

2017

2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation And

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The task of capturing a space target using a space robot carrying robotic manipulators can be divided into two phases: controlling the robot to reach a desired berth position near the floating target, and manipulating the manipulator to grasp the target. Most of the existing planning strategies only focus on a point-to-point trajectory planning of the manipulator to ensure the end-effector to reach a desired pose, while the berth position is usually set manually. In this paper, we propose an optimal coordinated planning strategy for space robots to grasp targets. Both the manipulator's joint trajectories and the robot's berth position are considered to autonomously accomplish the coordinated planning of the end-effector and the robot base. From the perspective of the task-space constraints, the manipulator is first planned to satisfy the attitude constraints of the end-effector and base, and then the berth position is planned to meet the end-effector's position. A Modified Generalized Jacobian Matrix (MGJM) is proposed to describe the velocity mapping from the joint space to the attitude of the end effector and the base. Based on the MGJM and Particle Swarm Optimization (PSO), the whole planning task is turned to optimize the joint trajectories and the berth position. Simulated experiments have verified that the proposed planning strategy can successfully automate the two phases of a space robot to grasp target in the space.

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Section: A Analysis Of Typical Grasping Tasksmentioning

confidence: 99%

Section: B Optimal Coordinated Grasping Strategymentioning

confidence: 99%

Section: Modified Generalized Jacobian Matrixmentioning

confidence: 99%

“…X f f f and the objective function Γ is calculated by using (14) and (16) based on a hypothetical berth position 0h r .…”

Section: E Planning Proceduresmentioning

confidence: 99%

See 2 more Smart Citations

Optimal coordinated planning strategy for space robots grasping targets

Zhang

Liu

2017

2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation And

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“…Oda等人 [17] 通过估计机械臂产生的角动量, 然后对基座平台姿态进行补偿控制, 对机械臂运动与基座平台姿态进行了协调控制. 徐文福等人 [18] 提出在自由漂浮基下, 由空间机械臂自身的控制实现机械臂与基座平台协调运动的方法. Jayakody等人 [19]…”

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Autonomous reinforcement learning control for space robot to capture non-cooperative targets

Liu

et al. 2019

Sci. Sin.-Phys. Mech. Astron.

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Method for Robot Capturing Object Thrown out in Natural Wind Environment

Zheng

Zhao

Kang

et al. 2021

J. Phys.: Conf. Ser.

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It is difficult for a robot to capture object which is thrown out in the environment with natural wind. Equation of state and measurement of the object in the environment with natural wind is studied. Using the measurement equation and the state equation when there is no natural wind, the average acceleration of the object caused by natural wind can be estimated. Moreover, the variance of the object acceleration caused by natural wind can be estimated using the statistical characteristics and probability distribution of natural wind. Then a method for robot capturing the object based on Kalman filter is proposed. Simulation results show that the trajectory of the object changes obviously when two groups of typical natural wind are used. The object trajectory can be tracked by the robot accurately after it deviates from the object trajectory for about eight sampling periods.

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Coordinated Control of a Free-floating Space Robot for Capturing a Target

Cited by 4 publications

References 0 publications

Optimal coordinated planning strategy for space robots grasping targets

Optimal coordinated planning strategy for space robots grasping targets

Autonomous reinforcement learning control for space robot to capture non-cooperative targets

Method for Robot Capturing Object Thrown out in Natural Wind Environment

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