This work addresses multi-robot coordination in social human-populated environments based on a Hoplites-based framework for solving the multi-robot task allocation problem. Humans are considered in the proposed coordination mechanism by means of accounting for social costs in bid evaluations and requesting collaboration in socially blocking situations. Initially, the effect of a realistic dynamic noisy environment with varying number of static/moving humans on the behavior and performance of our method is studied through an extensive suite of experiments in a realistic high-fidelity simulator (Webots). Results show that the total traveled distance and time are increased when humans are present in the environments. Localization noise is also increased particularly for the case of static people. In the second part of the experiments, a number of problematic cases resulting in longer modified plans, blocked passages, and long waits have been investigated. A comparative study targeting human-agnostic navigation and planning, human-aware navigation without considering humans in the planning phase, and human-aware navigation and planning has been conducted. Both simulated and real robot experiments confirm the effectiveness of accounting for humans on both team and individual levels for respecting social constraints as well as achieving a better performance based on MRTA metrics.