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Real-Time Smooth Corner Trajectory Planning for Industrial Robots Under Linear and Angular Kinematic Constraints

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Intelligent Robotics and Applications (ICIRA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14272))

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Abstract

Path-invariant corner transition trajectory planning is crucial for industrial robots to achieve error-controllable and smooth motion in many manufacturing applications. It usually consists of a spline-based local smoothing procedure for position and orientation linear segments and a real-time feedrate scheduling process. In traditional parameter-synchronization-based methods, the angular motion is regarded as a slave motion following the linear motion by sharing the same curve parameter, which might result in violation of angular kinematic constraints. To overcome this problem, this paper presents a real-time corner trajectory generation method based on a new time-synchronization algorithm. First, the position and orientation linear segments are G2-continuously transited by inserting error-controlled cubic B-splines and quaternion B-splines at the corners, and subdivided into numerous pairs of blocks. Then the jerk-limited motion profiles of each block pair are planned separately and synchronized to share the same motion duration. The motion profiles for all block pairs can be efficiently obtained by sequentially applying the proposed method from the first to the end block pair without the bi-directional scanning procedure in the literature. The resulting motion profiles respect tangential linear and angular kinematic limits up to jerk in Cartesian space and guarantee continuous acceleration of joint trajectories simultaneously. Simulation experiments verify the effectiveness of the proposed method.

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Correspondence to Wenjie Chen .

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Peng, J., Zhang, Z., Chen, W. (2023). Real-Time Smooth Corner Trajectory Planning for Industrial Robots Under Linear and Angular Kinematic Constraints. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14272. Springer, Singapore. https://doi.org/10.1007/978-981-99-6480-2_27

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  • DOI: https://doi.org/10.1007/978-981-99-6480-2_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-6479-6

  • Online ISBN: 978-981-99-6480-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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