A Review of Spatial Robotic Arm Trajectory Planning

Dai, Ye; Xiang, Chao-Fang; Zhang, Yuan; Jiang, Yupeng; Qu, Wen-Yin; Zhang, Qihao

doi:10.3390/aerospace9070361

Cited by 29 publications

(7 citation statements)

References 74 publications

(78 reference statements)

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“…Aginaga et al presented a comprehensive analysis of singularities in the 6RUS mechanism [8], identifying critical configurations and providing guidelines for singularity avoidance. Dai et al proposed a path planning algorithm that considers singularity avoidance to ensure smooth and continuous motion of the 6RUS manipulator [9]. These studies contribute to a better understanding of singularities and provide practical solutions to mitigate their adverse effects on the 6RUS mechanism's performance.…”

Section: Forewordmentioning

confidence: 99%

A Forward Solution Algorithm of 6RUS Parallel Mechanism Based on Dual Quaternion Method

Dong,

Du,

2023

International Journal of Aerospace Engineering

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The 6RUS parallel manipulator is a highly versatile and widely used robotic mechanism with six degrees of freedom. Its intricate kinematic structure and its capability to perform complex motion tasks have garnered significant research interest in recent years. The kinematic analysis of the 6RUS mechanism plays a crucial role in understanding its operational characteristics and optimizing its performance for various applications. In this paper, we present a state-of-the-art kinematic algorithm for the 6RUS parallel manipulator. Our algorithm is aimed at addressing the challenges associated with accurately determining the pose and motion of the end-effector relative to the base, considering the complexity of the mechanism’s architecture. By leveraging advanced mathematical modeling techniques and utilizing efficient computational algorithms, our proposed algorithm offers improved accuracy, efficiency, and robustness in determining the kinematic parameters of the 6RUS mechanism. The key contributions of this work include the development of a comprehensive forward and inverse kinematic model for the 6RUS parallel manipulator, incorporating the effects of joint constraints, singularities, and workspace limitations. We also present a detailed analysis of the algorithm’s performance in comparison to existing approaches, demonstrating its superiority in terms of computational efficiency and accuracy. The proposed kinematic algorithm holds significant potential for enhancing the design, control, and trajectory planning of 6RUS parallel manipulators. It provides a solid foundation for advanced applications such as robotic surgery, industrial automation, and virtual reality systems. The results presented in this paper contribute to the growing body of knowledge in parallel manipulator research and pave the way for future developments in the field.

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Section: Forewordmentioning

confidence: 99%

A Forward Solution Algorithm of 6RUS Parallel Mechanism Based on Dual Quaternion Method

Dong,

Du,

2023

International Journal of Aerospace Engineering

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“…Industrial robot trajectory planning encompasses the generation of trajectories through interpolation between predefined via‐points, employing interpolation functions. which can be classified into two types based on the planning space: operation space trajectory planning and joint space trajectory planning (Dai et al, 2022; Li et al, 2018). Operation space trajectory planning represents the generated trajectories as a sequence of robot End‐Effector (EE) positions, which are then converted into joint space using inverse kinematics to enable control (Korein & Ish‐Shalom, 1987).…”

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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“…Processing the Jacobian matrix in a certain way can allow the robotic arm to work in the singular region, such as through methods like damping least squares. However, these methods have issues with error accumulation and multiple solutions [14]. Therefore, when it is not necessary to pass through the singular region, it is better to select a reasonable trajectory that avoids singular points.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning and Singularity Avoidance Algorithm for Robotic Arm Obstacle Avoidance Based on an Improved Fast Marching Tree

Wu,

Hui

et al. 2024

Applied Sciences

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The quest for efficient and safe trajectory planning in robotic manipulation poses significant challenges, particularly in complex obstacle environments where the risk of encountering singularities and obstacles is high. Addressing this critical issue, our study presents a novel enhancement of the Fast Marching Tree (FMT) algorithm, ingeniously designed to navigate the complex terrain of Cartesian space with an unprecedented level of finesse. At the heart of our approach lies a sophisticated two-stage path point sampling strategy, ingeniously coupled with a singularity avoidance mechanism that leverages geometric perception to assess and mitigate the risk of encountering problematic configurations. This innovative method not only facilitates seamless obstacle navigation but also adeptly circumvents the perilous zones of singularity, ensuring a smooth and uninterrupted path for the robotic arm. To further refine the trajectory, we incorporate a quasi-uniform cubic B-spline curve, optimizing the path for both efficiency and smoothness. Our comprehensive simulation experiments underscore the superiority of our algorithm, showcasing its ability to consistently achieve shorter, more efficient paths while steadfastly avoiding obstacles and singularities. The practical applicability of our method is further corroborated through successful implementation in real-world robotic arm trajectory planning scenarios, highlighting its potential to revolutionize the field with its robustness and adaptability.

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A Review of Spatial Robotic Arm Trajectory Planning

Cited by 29 publications

References 74 publications

A Forward Solution Algorithm of 6RUS Parallel Mechanism Based on Dual Quaternion Method

A Forward Solution Algorithm of 6RUS Parallel Mechanism Based on Dual Quaternion Method

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

Trajectory Planning and Singularity Avoidance Algorithm for Robotic Arm Obstacle Avoidance Based on an Improved Fast Marching Tree

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