Purpose
In the future, large space truss structures will be likely to require on-orbit assembly. One of the several proposed methods includes cooperative assembly performed by pressure-suited astronauts during extravehicular activity (EVA) and space robots. An intelligent planning method was presented to generate optimal assembly tasks.
Design/methodology/approach
Firstly, the inherent hierarchical nature of truss structures allows assembly sequences to be considered from strut level and structural volume element (SVE) level. Then, a serial assembly strategy in human-robot environment was applied. Furthermore, a two-level planning algorithm was presented. At the first-level planning, one ant colony algorithm for assembly sequence planning was improved to adopt assembly direction and time as heuristic information and did not consider assembly tasks. And, at the second-level planning, another novel colony algorithm for assembly task planning mainly considered results of the first-level planning, human-robot interactive information, serial assembly strategy and assembly task distributions.
Findings
The proposed two-level planning algorithm is very effective for solving the human and robot cooperative assembly of large space truss structures.
Research limitations/implications
In this paper, the case study is based on the following assumptions: each tetrahedron is assembled by two astronauts; each pentahedron is assembled by three astronauts.
Practical implications
A case illustrates the results of the two-level planning. From this case study, because of geometrical symmetry nature of large space truss structures, the optimal assembly sequences are not only one.
Originality/value
The improved ant colony algorithm can deal with the assembly sequence and task planning in human-robot environment more effectively.
Lightweight nodal parts for large space truss structures enabled by SLM: modelling, manufacturing, and testing
