Before revision:  To improve the efficiency of deep reinforcement learning (DRL) based methods for robot manipulator trajectory planning in random working environment.
After revision: (This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.) To improve the efficiency of deep reinforcement learning (DRL) based methods for robot manipulator trajectory planning in random working environment.