Trajectory planning in parallel kinematic manipulators using a constrained multi-objective evolutionary algorithm

By Chun-Ta Chen, Hoang-Vuong Pham. 2012

64 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/90ed4fca805f4bf3ddacaf9f7be90e1a0b81654e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Kay Chen Tan
2. Renato Vidoni
3. Paolo Boscariol
4. Alessandro Gasparetto
5. Albano Lanzutti

In Control and Systems Engineering

1. Paolo Boscariol
2. Renato Vidoni
3. Albano Lanzutti
4. Kay Chen Tan
5. Alessandro Gasparetto
6. Jing J. Liang
7. Yaochu Jin
8. Ran Cheng

Citations in the corpus

• Path Planning and Trajectory Planning Algorithms: A General Overview (2015, methodology): “Also in [22] a constrained multi-objective genetic algorithm (MOGA) based technique is proposed to address this problem for a general motor-driven parallel kinematic manipulator.”
• A Survey on Evolutionary Constrained Multiobjective Optimization (2023, methodology): “In order to solve the trajectory optimization problem of a motor-driven parallel robot, the constrained multiobjective genetic algorithm (MOGA) was used by Chen and Pham [164].”