Jerk Optimized Motion Planning of Redundant Space Robot Based on Grey-Wolf Optimization Approach

Shrivastava, Abhishek; Dalla, Vijay Kumar

doi:10.1007/s13369-022-07002-1

Cited by 8 publications

(5 citation statements)

References 40 publications

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“…To verify the effectiveness of the suggested approach, the damped least square (DLS) and model predictive control (MPC) methods [47][48][49] Validation with damped least square method Figure 15 depicts the variation in end-effector position over time using the proposed method and DLS methods. By using the suggested method in this case, the deviation between the straight-line path and polynomial blend is 4°, whereas it is 12°when using the DLS method.…”

Section: Validation Of Proposed Methodsmentioning

confidence: 99%

“…To verify the effectiveness of the suggested approach, the damped least square (DLS) and model predictive control (MPC) methods 47–49 are applied. The robot is acquired in order to change the starting base attitude [ α , β , γ ] s = ( 0 . 0 , 0 . 0 , 0 . 0 ) ° to the desired base attitude [ α , β , γ ] d = ( 6 . 0 , 6 . 0 , 8 . 0 ) ° and desired end-effector attitude quaternion is [ v e , 0.25em p e 1 , 0.25em p e 2 , 0.25em p e 3 ] = [0.1220, 0.029, 0.028, 0.082] m. Where, [ v e ] signifies quaternion agreeing to rotation frame, [ p e 1 , p e 2 , p e 3 ] represent quaternion conforming to position frame, …”

Section: Validation Of Proposed Methodsmentioning

confidence: 99%

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Optimum joint and trajectory tracking control of multi-axes space manipulator based on amnesia feedback controller

Shrivastava

Dalla

Abhishek

2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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The space manipulators operate in an unstructured or unknown environment, increasing the dynamic complexity of space manipulator. Due to disturbance in manipulator base, the trajectory tracking control issue arises that cause error between reference and actual trajectory. Hence, to sort out these issues, this work presents optimum joint and trajectory tracking control of multi-axes space manipulator based on amnesia feedback controller. Firstly, the dynamic model of a 7DOF space manipulator built on Euler-Lagrange theorem, using the Jacobian matrix of individual link is designed. Later on, the Amnesia controller strategy is implemented that keeps a record of the trajectory tracking error and sends them to the robot tip. Compared to PID control scheme, the rising time, settling time, and overshoot is reduced even further when amnesia controller is used. The trajectory deviation using PID controller is 15°, while it is 3° using Amnesia controller, as expected. Hence, Amnesia controller reduces the trajectory tracking error between reference and actual trajectory of the redundant robot. The effectiveness of the proposed methodology employing a redundant 7DOF space robot has been verified. This proposed scheme can be utilized for on-orbit servicing and space debris removal through space craft.

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Section: Validation Of Proposed Methodsmentioning

confidence: 99%

Section: Validation Of Proposed Methodsmentioning

confidence: 99%

Optimum joint and trajectory tracking control of multi-axes space manipulator based on amnesia feedback controller

Shrivastava

Dalla

Abhishek

2023

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

show abstract

“…However, it is observed that trajectory planning solely based on the robot's task goals and functional realization lacks rigor and necessitates consideration of factors related to trajectory quality assessment. Among these factors, efficiency (Singh & Banga, 2022; Wang, Wu, et al, 2019; Zhang et al, 2022), energy consumption (Jiang et al, 2023; Li et al, 2022; Ren et al, 2023), and operational smoothness (Lin, 2014; Shrivastava & Dalla, 2022) stand out as the most prominent factors (Gasparetto et al, 2015). Efficiency and smoothness of industrial robots are two conflicting factors.…”

Section: Introductionmentioning

confidence: 99%

Time–jerk optimal trajectory planning for industrial robots with coupled interpolation function selection

Wang,

Zhang,

Zhou

et al. 2024

Journal of Field Robotics

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In the contemporary field of optimal trajectory planning for industrial robots, it is customary to construct trajectories through the manual predefinition of interpolation functions. Unfortunately, this method frequently overlooks the influence of the interpolation function itself on the optimization objectives, resulting in suboptimal outcomes. To remedy this limitation, an optimal trajectory planning method with coupled interpolation function selection is proposed, in which the total task time and the integral squared jerk are defined as optimization objectives. This method minimizes the optimization objectives while also factoring in the optimal interpolation function, and avoiding subjective interference. To address the aforementioned biobjective optimization problem better, an Improved MultiObjective Golden Eagle Optimizer is introduced. Population diversity and the ability to escape local optima are enhanced through the incorporation of Chaotic Mapping, Opposition‐Based Learning, Differential Evolution, and adaptive inertia weight strategy into the algorithm. The superiority of the algorithm is validated through a series of simulations on 17 benchmark functions. In the context of the robotic stirring operation within the automated block cast charging process, the proposed method is utilized to derive the time–jerk optimal trajectory. The results demonstrate the effectiveness of the proposed method.

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“…The planned trajectory is smoother, but the convergence speed is slower. Shrivastava et al [29] calculated the jerk-optimized trajectory of a redundant manipulator with the gray wolf optimizer. The approach can generate a minimal difference in the joint trajectory to guarantee joint stability.…”

Section: Introductionmentioning

confidence: 99%

Trajectory planning of large redundant manipulator considering kinematic constraints and energy efficiency

Liu,

Huang,

Liu

et al. 2023

Robotica

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For the large redundant manipulator, due to its long working distance and large mass, the number of links (i.e., manipulator’s arms) that can be driven to move simultaneously is limited. Otherwise, the control accuracy and motion stability of the manipulator will deteriorate. Focusing on that, a weighted Newton iteration (WNI) algorithm for trajectory planning of the manipulator is firstly proposed, where the motion of the manipulator joints is controlled by a weight matrix, which is constant and related to each link’s energy consumption. To dynamically adjust the weight matrix according to kinematic constraints and acquire better energy efficiency, an adaptive WNI (AWNI) algorithm is further proposed. In AWNI, the weight matrix is adjusted in real-time during the planning process, with considerations of the kinematic constraints and the energy consumption of the manipulator. The switch of the links between the working state and the non-working state is made through the weight matrix to achieve flexible control of the manipulator motion. Two evaluation functions are established to validate the effectiveness of AWNI in energy saving and motion stability control. Taking a 6 degrees of freedom (DOF) manipulator as an example, simulation experiments on trajectory planning are carried out and the results show the effectiveness of the proposed AWNI algorithm.

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Jerk Optimized Motion Planning of Redundant Space Robot Based on Grey-Wolf Optimization Approach

Cited by 8 publications

References 40 publications

Optimum joint and trajectory tracking control of multi-axes space manipulator based on amnesia feedback controller

Optimum joint and trajectory tracking control of multi-axes space manipulator based on amnesia feedback controller

Time–jerk optimal trajectory planning for industrial robots with coupled interpolation function selection

Trajectory planning of large redundant manipulator considering kinematic constraints and energy efficiency

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