scholarly journals Optimal Trajectory Planning and Model Predictive Control of Underactuated Marine Surface Vessels using a Flatness-Based Approach

Author(s):  
Max Lutz ◽  
Thomas Meurer
2021 ◽  
Vol 11 (16) ◽  
pp. 7513
Author(s):  
Jong Ho Kim ◽  
Kyunghwan Choi ◽  
In Gwun Jang

Trajectory planning for a redundant manipulator is a classic problem. However, because it is difficult to precisely evaluate its maximum performance, an optimization method has been typically used. In this study, a novel time-optimal trajectory planning method for a redundant manipulator is proposed using the model predictive control (MPC) augmented by the maximum performance evaluation (MPE). First, the optimization formulation is expressed to evaluate the maximum performance of the distributed-actuation-mechanism-based three-revolute-joint manipulator (DAM-3R), which has a high level of redundancy, and the joint-actuation-mechanism-based three-revolute-joint manipulator (JAM-3R) for comparison. The optimization is conducted by linking the multibody dynamics analysis module and the optimization module. For time-optimal trajectory planning, the MPC problem is then formulated using mathematical performance models for the DAM-3R and JAM-3R based on the MPE results, which are considered as the upper bound of the manipulator performance at each end-effector position. To verify the proposed method, a point-to-point task with no predefined path is investigated. The simulation results show that the working time of the DAM-3R is 19.1% less than that of the JAM-3R. Moreover, the energy consumption for the DAM-3R is 45.0% lower than that for the JAM-3R by optimally utilizing the higher redundancy of the DAM-3R. Thus, it can be concluded that the proposed method is effective for time-optimal trajectory planning for redundant manipulators.


2021 ◽  
Vol 13 (7) ◽  
pp. 168781402110346
Author(s):  
Yunyue Zhang ◽  
Zhiyi Sun ◽  
Qianlai Sun ◽  
Yin Wang ◽  
Xiaosong Li ◽  
...  

Due to the fact that intelligent algorithms such as Particle Swarm Optimization (PSO) and Differential Evolution (DE) are susceptible to local optima and the efficiency of solving an optimal solution is low when solving the optimal trajectory, this paper uses the Sequential Quadratic Programming (SQP) algorithm for the optimal trajectory planning of a hydraulic robotic excavator. To achieve high efficiency and stationarity during the operation of the hydraulic robotic excavator, the trade-off between the time and jerk is considered. Cubic splines were used to interpolate in joint space, and the optimal time-jerk trajectory was obtained using the SQP with joint angular velocity, angular acceleration, and jerk as constraints. The optimal angle curves of each joint were obtained, and the optimal time-jerk trajectory planning of the excavator was realized. Experimental results show that the SQP method under the same weight is more efficient in solving the optimal solution and the optimal excavating trajectory is smoother, and each joint can reach the target point with smaller angular velocity, and acceleration change, which avoids the impact of each joint during operation and conserves working time. Finally, the excavator autonomous operation becomes more stable and efficient.


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