In this work, we propose a distributed control scheme for multi-robot systems in the presence of multiple constraints using control barrier functions. The proposed scheme expands previous work where only one single constraint can be handled. Here we show how to transform multiple constraints to a collective one using a smoothly approximated minimum function. Additionally, human-in-the-loop control is also incorporated seamlessly to our control design, both through the nominal control in the optimization objective as well as a safety condition in the constraints. Possible failure regions are identified and a suitable fix is proposed. Two types of human-in- the-loop scenarios are tested on real multi-robot systems with multiple constraints, including collision avoidance, connectivity maintenance, and arena range limits.