# Task-Oriented Motion Planning of a Space Manipulator under Multiple Constraints
## 7 Conclusions  
In this paper, the task planning algorithm of the manipulator was modeled according to the HTN theory. Through the profile analysis of the typical tasks of the space manip  
Figure 11: Position and velocity curve of joints and end-effector.  
Figure 10: Position and velocity curves of joints and end-effector.  
ulator, the motion planning algorithm design of the task-oriented multi-constraint space manipulator was completed, and a typical application of the manipulator and cabin assembly was verified and simulated. On the basis of reasonable modeling and sufficient verification, aiming at the motion of the manipulator under multiple constraints, the target pose can be kept unchanged and the multi-stage trajectory can be automatically optimized to meet the task requirements.  
By analyzing the simulation results, the following conclusions can be obtained:  
1. When there is no task planning function, the direct movement of the manipulator will interfere, the manual adjustment will be inefficient, and the path will not be optimal.
2. The designed algorithm can solve many constraints; the planning efficiency is high, the path is the shortest, and the target pose is consistent.  
This study provides the following innovations and contributions:  
1. Combined with the characteristics of a space manipulator control system and various on-orbit service tasks, a two-tier framework of task planning for a complex on-orbit environment is proposed.
2. The idea of hierarchical task network is used to deal with the analysis and disassembly of complex tasks of a manipulator. Combined with the working characteristics of the space manipulator, state matrix, state mask and related algorithms are proposed, the operator expressions of three typical original tasks of space manipulator are presented, and the hierarchical task network planner for a space manipulator is realized.
3. Based on the improved A* algorithm, a task middle-point planning method is proposed, which enables the space manipulator to consider a variety of constraints at the same time in the complex obstacle environment, complete the task with the optimal resource allocation, reduce the operation loss of the mechanism and ensure the reliability of the mechanism.  
The conflict between the simplifications of closed-world hypotheses in planning and the complex and changeable real-world situations has become a major problem in the field of robot research. At present, the working environment of robots tends to be complex and dynamic. Incomplete and uncertain information of the surrounding environment often leads to difficulties in the process of robot performing tasks. An effective and reasonable way to deal with this problem is to combine the method of artificial intelligence with robot control based on planning. This is an important research direction for this technology in the future.  
Conceptualization, C.L. and G.C.; methodology, C.L.; software, P.X.; validation, P.X. and D.P.; formal analysis, X.Z.; investigation, C.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.