Abstract

Collaborative exploration using unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has become increasingly popular in the past decade. This study addresses real-time autonomous tracking and landing of a UAV on a moving ground vehicle, which is fundamental for the UAV-UGV collaborative exploration. The method proposed in this study estimates the relative pose and velocity between a UAV and UGV, and uses model predictive control for UAV trajectory planning while considering the field of view of the camera onboard the UAV. We elaborate the hardware-in-the-loop simulator (HITL) with a physical companion computer, and confirm that the proposed method enables a UAV to land on a UGV traversing on rough terrain based on online computations in the HITL. Additionally, we present statistical analysis of the simulation results of typical and computationally demanding scenarios to elucidate the computational cost on the real machine.

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