Article
Automation & Control Systems
Huanhuan Huang, Houde Liu, Chongkun Xia, Hongwei Mei, Xuehai Gao, Bin Liang
Summary: In this paper, a sampling-based time-optimal path parameterization (S-TOPP) method is proposed to solve time-optimal trajectory planning problems with bounded jerks. S-TOPP establishes a tree of feasible nodes connected by edges to find a time-optimal trajectory on the temporal dimension. By optimizing the sampling strategy and using a lazy strategy, S-TOPP achieves better results and is more in line with the needs of practical tasks compared to other methods.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2023)
Article
Chemistry, Multidisciplinary
Yaosheng Zhou, Guirong Han, Ziang Wei, Zixin Huang, Xubing Chen
Summary: In this paper, a new optimal trajectory planning method for a manipulator is proposed to optimize operating efficiency and ensure smooth motion. The method uses inverse kinematics algorithm and B-spline curve interpolation method to obtain position sequences and construct joint trajectories. The proposed method provides ideal trajectories for the joint controller and allows the manipulator to smoothly track specified trajectories in the shortest time.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Industrial
Shingo Tajima, Burak Sencer
Summary: This paper presents a real-time trajectory generator that uses a dynamic command scaling approach to generate trajectories in real-time, fully utilizing the stroke, velocity, acceleration, and dynamic limits of the dual-stage drives, enabling coordinated high-speed dual-stage contouring motion to be realized.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2023)
Article
Chemistry, Multidisciplinary
Pu Wu, Zongyan Wang, Hongxiang Jing, Pengfei Zhao
Summary: This paper proposes a multi-objective integrated trajectory planning method based on an improved butterfly optimization algorithm (IBOA), aiming to improve the dynamic performance of the Delta parallel pickup robot in high-speed pick-and-place processes. The method focuses on improving dynamic positioning accuracy and running stability at high speeds and accelerations.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Jianxin Guo, Mingyong Zhao, Lixian Zhang
Summary: This paper proposes a time-bound optimal planning model to balance the cutting efficiency and the cutting security. By considering the kinematic constraints as a fuzzy set and using fuzzy optimization method, a compromise bound is obtained. The original problem is simplified into a convex problem and solved numerically.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Review
Thermodynamics
Yunyue Zhang, Zhiyi Sun, Qianlai Sun, Yin Wang, Xiaosong Li, Jiangtao Yang
Summary: This paper investigates the optimal trajectory planning of a hydraulic robotic excavator using the Sequential Quadratic Programming (SQP) algorithm, considering a trade-off between time and acceleration. By utilizing cubic splines for interpolation in joint space, the optimal angle curves for each joint are obtained and the excavator's optimal time-jerk trajectory planning is achieved. Experimental results demonstrate that the SQP method is more efficient in solving the optimal solution under the same weight, resulting in smoother excavating trajectories and improved stability and efficiency in autonomous operation.
ADVANCES IN MECHANICAL ENGINEERING
(2021)
Article
Automation & Control Systems
Jian-wei Ma, Song Gao, Hui-teng Yan, Qi Lv, Guo-qing Hu
Summary: This study introduces a new convex optimization approach for time-optimal trajectory planning that effectively restrains acceleration mutation and addresses torque and jerk limits by reasonably increasing computation time. The proposed method can reduce joint jerk values by over 80% and produce smoother joint torque curves compared to a similar method.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2021)
Article
Automation & Control Systems
Emilio Perez, Robert Landers, Douglas Bristow
Summary: In additive manufacturing processes, corners with small curvature create a conflict between path following error and velocity error. This study introduces an optimal trajectory smoothing method that balances these errors to improve part quality.
Article
Engineering, Chemical
Quan Xiao, Guofei Xiang, Yuanke Chen, Yuqi Zhu, Songyi Dian
Summary: This paper proposes a time-optimal trajectory planning method for a flexible manipulator to solve the problem of trajectory planning under multiple constraints during video inspection in a narrow 3D space. The method formulates the pose constraints, driving constraints, and obstacle constraints using space vector method, kinematics, and space mapping. A multi-constraint optimization model is constructed to generate a smooth drive cable trajectory by minimizing the total time of continuous path motion.
Article
Computer Science, Information Systems
Wa Zhang, He Chen, Haiyong Chen, Weipeng Liu
Summary: In industrial crane systems, complex situations such as oversized payloads or obstacles may occur. This study proposes an optimal time trajectory planning method for double-pendulum crane systems, considering multiple physical constraints to ensure obstacle avoidance objectives and improve safety and transportation efficiency. The effectiveness of the proposed method is verified through simulations.
Article
Automation & Control Systems
Min Set Paing, Naoki Uchiyama
Summary: In this study, a method to achieve guaranteed kinematic constraints of a time-optimal trajectory using cubic B-spline and convex hull was investigated. Both simulation and experimental results validate that the proposed method ensures trajectory smoothness and time optimality while satisfying motion constraints.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Robotics
Philipp Foehn, Angel Romero, Davide Scaramuzza
Summary: Quadrotors are known for their agility, but planning time-optimal trajectories through multiple waypoints has been a challenge. This study introduces a new method that simultaneously optimizes time allocation and trajectory to generate truly time-optimal trajectories, surpassing human expert drone pilots in a drone-racing task.
Article
Automation & Control Systems
Bendali Nadir, Ouali Mohammed, Nguyen Minh-Tuan, Said Abderrezak
Summary: This paper presents a new technique using multiquadric radial basis functions to generate smooth motion trajectories for robot manipulators. By minimizing two objective functions, an optimal trajectory is obtained which takes into account the execution time and the jerk along the entire trajectory. With the proposed interpolation technique, the trajectory planning problem in joint space is effectively solved, satisfying kinematics limits. Experimental results demonstrate the competent performances of this technique in generating smooth trajectories in short transfer time.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Engineering, Civil
Antonio Artunedo, Jorge Villagra, Jorge Godoy
Summary: This study introduces a human-like speed planning method for minimizing travel time on predefined paths, which has been tested and validated through experiments on real environments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Gonzalez-Villagomez Esau, Rodriguez-Donate Carlos, Mata-Chavez Ruth Ivonne, Cabal-Yepez Eduardo, Lopez-Hernandez Juan Manuel, Palillero-Sandoval Omar
Summary: Industrial machines often suffer from excessive long-term vibrations, which deteriorate their movement, stability, and precision. This study proposes an innovative acceleration outline based on a Gaussian function to reduce vibrations and improve machine stability.
Article
Engineering, Industrial
Xiaoliang Yan, Reed Williams, Elena Arvanitis, Shreyes Melkote
Summary: This paper extends prior work by developing a semantic segmentation approach for machinable volume decomposition using pre-trained generative process capability models, providing manufacturability feedback and labels of candidate machining operations for query 3D parts.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
Article
Engineering, Industrial
Jing Huang, Zhifen Zhang, Rui Qin, Yanlong Yu, Guangrui Wen, Wei Cheng, Xuefeng Chen
Summary: In this study, a deep learning framework that combines interpretability and feature fusion is proposed for real-time monitoring of pipeline leaks. The proposed method extracts abstract feature details of leak acoustic emission signals through multi-level dynamic receptive fields and optimizes the learning process of the network using a feature fusion module. Experimental results show that the proposed method can effectively extract distinguishing features of leak acoustic emission signals, achieving higher recognition accuracy compared to typical deep learning methods. Additionally, feature map visualization demonstrates the physical interpretability of the proposed method in abstract feature extraction.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
