The area of mobile robotics has developed remarkably in recent years, many researchers are motivated by the growing demand for this technology and the variety of applications. Robotics competitions foster new challenges when considering diverse application scenarios for service robotics, such as RoboCup@Home, which sets rules for autonomous and intelligent robots to be evaluated while performing tasks in domestic or public scenarios. The present work focuses on solving the problem of exploring unknown residential indoor environments. To do this, the robot must collect external and internal information through sensors, to fuse this data and interpret it efficiently, making it possible to locate itself through probabilistic algorithms, simultaneously mapping the environment, and navigate the mapped environment avoiding collisions. The work studies and tests the configuration of distance sensors (lasers, sonar and cameras) and exploration techniques, available and shared in the ROS community, to ensure that the robot is able to fully explore the residential environment in order to optimize the necessary time, distance traveled and the rotation performed. The tested exploration packages are: explore-lite, RRT-exploration and cam-exploration. The variation of sensors was crucial to understand the advantages and disadvantages of using the Lidar laser and depth cameras in different combinations. Thus, the results show that the increase in the number of sensors does not improve performance in exploration in all conditions. The work concludes that both explore-lite and RRT-exploration perform well in all proposed conditions and indicate the best sensor assemblies for each package. Thus, a package was created for the implementation of autonomous exploration in the HERA Robot