Autonomous robots have allowed automation of a wide range of environmental monitoring processes, these include spatial extension mapping, remote sensing and acquisition of environmental data. Among these applications, the acquisition of environmental data has received a growing interest because of its scientific and social importance. The collected information could be air pollution data to evaluate air quality or impacts of environmental disasters, or humidity and speed of winds data to evaluate quickly and directly climate anomalies. Motivated by fast paced advances in this priority area, this work develops and compares the most used techniques of path planning in autonomous robots under physical constraints of environmental monitoring.