**Suping Zhao 1,2, Zhanxia Zhu 1,2,\* and Jianjun Luo1,2**


**\*** Correspondence: zhuzhanxia@nwpu.edu.cn; Tel.: +86-138-9189-8260

Received: 29 April 2019; Accepted: 20 May 2019; Published: 30 May 2019

**Abstract:** This work addresses the multitask-based trajectory-planning problem (MTTP) for space robotics, which is an emerging application of successively executing tasks in assembly of the International Space Station. The MTTP is transformed into a parameter-optimization problem, where piecewise continuous-sine functions are employed to depict the joint trajectories. An improved genetic algorithm (IGA) is developed to optimize the unknown parameters. In the IGA, each chromosome consists of three parts, namely the waypoint sequence, the sequence of the joint configurations, and a special value for the depiction of the joint trajectories. Numerical simulations, including comparisons with two other approaches, are developed to test IGA validity.

**Keywords:** space robotics; redundant; free-floating base; multiple tasks; trajectory planning; genetic algorithm
