## 1 Introduction  
With the development of robotic technology, robots have been widely used as human auxiliaries in space, factories, ocean and cities [1, 2, 3, 4, 5]. In space activity, robots can forcefully deal with space junk, which is extremely important for the safety of others spacecraft. The key essence of the garbage capture mission is the trajectory tracking, in which trajectory planning is important [6, 7]. Therefore, this study mainly discusses trajectory planning strategies based on joint space of robot arm, which can better reflect the motion model based on torque [8]. The 6-DOF(degrees of freedom) dual-arm is often mounted on the satellite base to perform capture missions because the dual-arm robot is flexibility and versatility, and the space robot also floats freely to save propellant. However, the dynamic coupling between the arm and base may cause the tracking error of the end-effector [9]. In order to keep pose of base stable, a motion planning strategy for the balance arm is adopted in the trajectory planning algorithm to offset dynamic coupling by some researchers [10, 11]. However, the possible non-rank condition of the Jacobian matrix led to the singularity of the robotic motion system and make the joint angular velocity unsolved [12, 13]. [PERSON] et al. [14] proposeda nonsingular trajectory planing method for space robot based on complex position compensation structure, and the base position is stabilized at the same time. Nevertheless, the current trajectory planning strategies for space robot can produce large tracking errors and base deviation when avoiding obstacles; severe base deviation may even cause a satellite to crash or deviate from the solar-toward orbit. Therefore, [PERSON] et al. [15] first proposed a pose-feedback trajectory planning strategy based on the idea of joint angular velocity control to eliminate the tracking errors caused by the singularity-avoidance algorithm. Based on that, [PERSON] et al. [16] presented a fast obstacle-avoidance trajectory planning strategy by fixed-time stability to make the errors caused by the auxiliary algorithm converge asymptotically, but the current pose-feedback trajectory planning strategies lead to excessive joint angular velocity when the robotic arms need to avoid obstacles, which may accelerate the aging of the mechanical rotating parts. At present, an important joint angular velocity trajectory optimization strategy for robot is to use the evolutionary algorithm to optimize the algorithm parameters of trajectory planning [17; 18]. A particle swarm optimization is applied into the trajectory planning of space robot to search for the optimal motion trajectory of robot arm [11], but this method inevitably produce tracking errors of end-effector. [PERSON] et al. [19] presented a trajectory planning method based on improved genetic algorithm (IGA) to optimize the parameters, but the obtained joint angular velocity trajectory is not global optimal and the tracking errors remain. The current trajectory optimization strategies based on evolutionary algorithm are often conservative and the results often fall into the local optimal, so it is important for the IGA to find the solution closest to the global optimal. Motivated by these issues, this paper proposes a novel trajectory planning strategy for a dual-arm 6-DOF space robot with the following innovative points: (1). A novel fixed-time stability system with low input is proposed to reduce the upper bound of system input. (2). A novel dsRNA splicing evolutionary algorithm is studied to optimize the algorithm parameters, which can make fitness better. (3). The smooth joint angular velocity trajectory of the space robot arm is planned by the dsRNA splicing evolutionary algorithm-based fixed-time trajectory planning strategy to make tracking errors of end-effector converge asymptotically in fixed time. In this paper, Section 1 is Introduction. Section 2 introduces the preliminaries. Section 3 shows the motion model of space robot.