Recently unmanned aerial vehicles (UAV) have been widely deployed in various real-world scenarios such as disaster rescue and package delivery. Many of these working environments are unstructured with uncertain and dynamic obstacles. UAV collision frequently happens. An UAV with high agility is highly desired to adjust its motions to adapt to these environmental dynamics. However, UAV agility is restricted by its battery power output; particularly, an UAV's power system cannot be aware of its actual power need in motion planning while the need is dynamically changing as the environment and UAV condition vary. It is difficult to accurately and timely align the power supply with power needs in motion plannings. This mismatching will lead to an insufficient power supply to an UAV and cause delayed motion adjustments, largely increasing the risk of collisions with obstacles and therefore undermine UAV agility. To improve UAV agility, a novel intelligent power solution, Agility-Enhanced Power Supply (AEPS), was developed to proactively prepare appropriate amount powers at the right timing to support motion planning with enhanced agility. This method builds a bridge between the physical power system and UAV planning. With agility-enhanced motion planning, the safety of UAV in complex working environment will be enhanced. To evaluate AEPS effectiveness, missions of "patrol missions for community security" with unexpected obstacles were adopted; the power supply is realized by hybrid integration of fuel cell, battery, and capacitor. The effectiveness of AEPS in improving UAV agility was validated by the successful and timely power supply, improved task success rate and system safety, and reduced mission duration.
翻译:最近无人驾驶航空飞行器(无人驾驶飞行器)被广泛部署在各种现实世界情景中,例如灾难救援和包裹交付等,其中许多工作环境没有固定和动态障碍,因此难以准确、及时地将电力供应与电力需求与动态规划联系起来。这种不匹配将会导致电力供应不足给无人驾驶航空飞行器,并导致延迟运动调整,这在很大程度上增加了与障碍碰撞的风险,从而破坏了无人驾驶航空飞行器的机动性。然而,无人驾驶航空飞行器的机动性受到其电池动力输出的限制;特别是,无人驾驶航空飞行器的动力系统无法意识到其在机动规划中的实际电力需求,而随着环境和无人驾驶飞行器状况的变异,这种需要正在动态变化中发生动态变化。 很难准确、及时地将电力供应与动力需求与动态规划中的动力需求挂钩。 这一方法将在实际电力系统与无人驾驶航空飞行器的电力供应需求之间架桥接桥,从而大大增加了与这些障碍的碰撞风险,从而削弱了UAVA的机动性安全性。