For robotic teams to operate effectively in large-scale, unstructured outdoor environments, cooperative perception is a foundational capability. Within the broader context of sustainable environmental applications, this chapter identifies key technical challenges and outlines future research directions. Through the real-time sharing of sensor data and collaborative decision-making, robot teams can achieve outcomes that surpass those of individual agents, especially in complex and dynamic environments such as forests and agricultural landscapes. The chapter introduces a conceptual framework that structures cooperative perception into three fundamental components: information acquisition, information sharing, and environment representation building, encompassing both mapping and localisation. Recent literature highlights the pivotal role of low-level, reactive decision-making in coordinating and integrating these components. To advance understanding in this area, the chapter introduces and defines the concept of “active cooperative perception,” building on the established notion of active perception–where robots adjust their sensors and movements to optimise data collection. This concept is broadened to include not only information acquisition but also communication leading to what is termed ’active communication’. The framework presented offers a foundation for the development of robust, adaptive systems designed to address the unique challenges of outdoor robotic applications.