The　competition　degree　and　characteristics　of　the　target　markets　based　on　a　global　vision　provide　references　for　market　entrants　and　policymakers.　This　study　describes　a　method　for　identifying　the　global　technology　innovations　market　layout　competitiveness　based　on　time　series　data　analysis.　We　map　the　time　series　data　from　30　countries　or　areas　of　the　global　industrial　robot　technology　innovations　market　through　retrieval　strategy　and　data　mining　onto　complex　networks　by　visibility　graph　algorithm.　We　analyze　the　dynamic　characteristics　by　the　VGNs’　topological　measures　after　the　development　trend　overview　and　stage　division　analyses.　We　use　cosine　similarity　to　evaluate　the　differences　and　similarities　between　countries　or　areas.　To　further　uncover　the　relationships　among　them,　a　similarity　complex　network　is　constructed　by　setting　a　link　threshold.　Seven　community　categories　as　sub-markets　are　found　through　community　division.　CN　and　US　rank　as　the　top　two　largest　industrial　robot　innovation　markets.　Most　European　countries　share　the　same　community　because　of　their　similarity　of　economic　development　brought　by　geographical　proximity　except　for　several　earlier　developed　economies　such　as　DE,　GB,　FR,　and　IT.　Some　catching-up　countries,　for　example,　IN　and　PH,　show　potential　similar　dynamic　trends　respectively　in　their　group　for　the　sharing　characteristics　probably　with　the　similar　economic　development　type　as　the　reason　behind,　whereas　RU　is　distinct　for　its　unique　economy　type.　©　2022　Elsevier　B.V.