We establish an efficient minimum-time cooperative task planning algorithm for robots and operators to serve clients. This problem is an extension of the multiple traveling salesman problem and the vehicle routing problem with synchronization constraints, but it is more difficult due to the cooperative tasks of the robots and operators. To find the exact minimum-time task plan with a small tree size, we propose an efficient branch-and-bound with a good initial tree and keen complementary heuristics. Our algorithm is also effective as an approximate algorithm for the many clients problem within the capacity of the computer used. The efficiency of our algorithm is revealed via case studies: telemedical service robots and planetary exploration robots.