论文标题
通过多个空中机器人的人类意识的物理人类机器人协作运输和操纵
Human-Aware Physical Human-Robot Collaborative Transportation and Manipulation with Multiple Aerial Robots
论文作者
论文摘要
人类机器人互动将在各个行业和日常任务中发挥重要作用，使机器人能够与人类有效合作并减少其身体工作量。现有的人类机器人互动的大多数方法都集中在人与单个地面或空中机器人之间的协作上。近年来，在考虑多个空中机器人时，该研究领域的进展很少，这些机器人提供了多功能性和机动性。本文提出了一种新颖的方法，用于使用多个空中机器人进行人体机器人协作运输以及对电缆悬浮有效载荷的操纵。所提出的方法可以使运输的物体和人工之间的平稳而直观的相互作用。同时，我们通过利用多机器人运输系统的内部冗余来考虑操作过程中的距离限制。我们方法的关键要素是（a）不依赖任何力传感器的协作有效载荷外部扳手估计器； （b）人类机器人协作运输和操纵的6D入学控制器； （c）一种人类感知力的分布，可利用内部系统冗余，以确保执行其他任务，而不会影响有效载荷轨迹跟踪或交互质量。我们通过广泛的模拟和现实世界实验来验证该方法。其中包括机器人团队协助人类运输和操纵负载的情况，或者人类帮助机器人团队在环境中导航。据我们所知，我们首次在实验中证明了我们的方法使四肢团队能够与人进行物理合作，以在所有6个DOF中操纵所有6 DOF的有效载荷，以合作的人类机器人运输和操纵任务。
Human-robot interaction will play an essential role in various industries and daily tasks, enabling robots to effectively collaborate with humans and reduce their physical workload. Most of the existing approaches for physical human-robot interaction focus on collaboration between a human and a single ground or aerial robot. In recent years, very little progress has been made in this research area when considering multiple aerial robots, which offer increased versatility and mobility. This paper proposes a novel approach for physical human-robot collaborative transportation and manipulation of a cable-suspended payload with multiple aerial robots. The proposed method enables smooth and intuitive interaction between the transported objects and a human worker. In the same time, we consider distance constraints during the operations by exploiting the internal redundancy of the multi-robot transportation system. The key elements of our approach are (a) a collaborative payload external wrench estimator that does not rely on any force sensor; (b) a 6D admittance controller for human-aerial-robot collaborative transportation and manipulation; (c) a human-aware force distribution that exploits the internal system redundancy to guarantee the execution of additional tasks such inter-human-robot separation without affecting the payload trajectory tracking or quality of interaction. We validate the approach through extensive simulation and real-world experiments. These include scenarios where the robot team assists the human in transporting and manipulating a load, or where the human helps the robot team navigate the environment. We experimentally demonstrate for the first time, to the best of our knowledge, that our approach enables a quadrotor team to physically collaborate with a human in manipulating a payload in all 6 DoF in collaborative human-robot transportation and manipulation tasks.
