Traditional environmental monitoring relies on sparse sensor networks and manual data collection, limiting spatial and temporal resolution of ecosystem assessments. This robotics study develops autonomous swarm systems for comprehensive environmental monitoring using coordinated multi-robot platforms. We designed low-cost sensor-equipped robots ($340 each) capable of air quality measurement, soil analysis, and biodiversity assessment through acoustic and visual sensors. Field tests across forest, marine, and urban environments with 25-robot swarms demonstrated superior data coverage compared to static monitoring stations, with 15x spatial resolution improvement and real-time hazard detection capabilities. The research includes swarm coordination algorithms, communication protocols, and data fusion techniques for scalable environmental monitoring applications.