Abstract: To fully exploit the flexibility and high-altitude perception capabilities of UGV (unmanned ground vehicle) mounted UAV (unmanned aerial vehicle), a forward exploration and companion trajectory planning approach is proposed for UAV-assisted UGV perception with active peripheral vision enhancement. In this framework, a UAV equipped with a depth camera is utilized as an agile sensing platform for the UGV. By designing a sophisticated dispatch strategy, the UAV is guided to execute environmental information perception tasks, thereby augmenting the comprehensive environmental perception capabilities of UGV. To achieve this, the unperceived environmental voxel information surrounding the UGV path is clustered and segmented into multiple information sets. Key information features are extracted to form edge clusters, which serve as a guide for precise planning. A hierarchical dispatcher is subsequently designed. Initially, an MILP (mixed-integer linear programming) model is developed to solve the maximum node coverage routing problem by time window, yielding a basic and feasible coarse global path. Subsequently, local path optimization is implemented under the guidance of edge cluster viewpoints, resulting in a series of discrete navigation points. These discrete navigation points are then utilized for trajectory optimization, generating continuous trajectories for navigation under constraints related to smoothness, safety, and dynamic feasibility. To validate the effectiveness of the proposed algorithm, experimental verification is conducted in both simulation environments and real-world scenarios. The experimental results demonstrate that the introduced UAV-UGV planning framework significantly enhances the environmental perception capabilities of UGV.