2010 ◽  
Vol 108-111 ◽  
pp. 1141-1146
Author(s):  
Jie Yan ◽  
Dao Xiong Gong

The Strength Pareto Evolutionary Algorithm (SPEA) is adopted to find time-jerk synthetic optimal trajectory of a hexapod robot in the joint space. In order to get the optimal trajectory, cubic splines are employed and derived under the constraint condition of via points to assure overall continuity of velocity and acceleration. Taken both the execution time and minimax approach of jerk as objectives, and expressed the kinematics constraints as upper bounds on the absolute values of velocity and acceleration, the mathematic model of time-jerk synthetic optimal trajectory planning is built. Finally, SPEA is adopted to optimize the stair-climbing trajectory of a hexapod robot, the simulation results show that this method can solve the trajectory planning problem effectively, and the stair-climbing trajectory can meet the contradictory objective functions of high speed and low robot vibration well.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Ting Wang ◽  
Zhijie Xin ◽  
Hongbin Miao ◽  
Huang Zhang ◽  
Zhenya Chen ◽  
...  

Robot will be used in the grinding industry widely to liberate human beings from harsh environments. In the grinding process, optimal trajectory planning will not only improve the processing quality but also improve the machining efficiency. The aims of this study are to propose a new algorithm and verify its efficiency in achieving the optimal trajectory planning of the grinding robot. An objective function has been defined terms of both time and jerk. Improved whale optimization algorithm (IWOA) is proposed based on whale optimization algorithm (WOA) and differential evolution algorithm (DE). Mutation operation and selection operation of DE are imitated in the part of initialization to process the population initialized by WOA, and then, the search tasks of WOA are performed. Motion with a constant velocity of the end-effector is considered during fine grinding. The continuity of acceleration and velocity will be achieved by minimizing jerk, and at the same time, smooth robot movement can be obtained. Cubic spline interpolation is implemented. A six-axis industrial robot is used for this research. Results show that optimal trajectory planning based on IWOA is more efficient than others. This method presented in this paper may have some indirect significance in robot business.


Author(s):  
J V Miro ◽  
A S White

A near-optimal solution to the path-unconstrained time-optimal trajectory planning problem is described in this paper. While traditional trajectory planning strategies are entirely based on kinematic considerations, manipulator dynamics are usually neglected altogether. The strategy presented in this work has two distinguishing features. Firstly, the trajectory planning problem is reformulated as an optimal control problem, which is in turn solved using Pontryagin's maximum/minimum principle. This approach merges the traditional division of trajectory planning followed by trajectory tracking into one process. Secondly, the feedback form compensates for the dynamic approximation errors derived from linearization and the fundamental parameter uncertainty of the dynamic equations of motion. This approach can cope with flexible robots as well as rigid links. The terminal phase of the motion is controlled by a feedforward controller to reduce chatter vibrations. Results from simulations and an on-line implementation to a general-purpose open-chain industrial manipulator, the CRS A251, confirm the validity of the approach and show that maximizing the capabilities of the device can lead to an overall improvement in the manipulator time response of up to 24 per cent, while retaining an acceptable overshoot and steady state error regime.


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