Haptic teleoperation of a multirotor aerial robot using path planning with human intention estimation
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ORIGINAL RESEARCH PAPER
Haptic teleoperation of a multirotor aerial robot using path planning with human intention estimation Xiaolei Hou1 Received: 18 December 2018 / Accepted: 11 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Classical haptic teleoperation systems heavily rely on operators’ intelligence and efforts in aerial robot navigation tasks, thereby posing significantly users’ workloads. In this paper, a novel shared control scheme is presented facilitating a multirotor aerial robot haptic teleoperation system that exhibits autonomous navigation capability. A hidden Markov model filter is proposed to identify the intention state of operator based on human inputs from haptic master device, which is subsequently adopted to derive goal position for a heuristic sampling based local path planner. The human inputs are considered as commanded velocity for a trajectory servo controller to drive the robot along the planned path. In addition, vehicle velocity is perceived by the user via haptic feedback on master device to enhance situation awareness and navigation safety of the user. An experimental study was conducted in a simulated and a physical environment, and the results verify the effectiveness of the novel scheme in safe navigation of aerial robots. A user study was carried out between a classical haptic teleoperation system and the proposed approach in the identical simulated complex environment. The flight data and task load index (TLX) are acquired and analyzed. Compared with the conventional haptic teleoperation scheme, the proposed scheme exhibits superior performance in safe and fast navigation of the multirotor vehicle, and is also of low task and cognitive loads. Keywords Teleoperation · Hidden Markov model · Human intention · Path planning
1 Introduction Bilateral teleoperation system has been an active research topic for over half a century since the development of the initial mechanical master-slave system in 1948 [1] for handling radioactive materials. The early studies underpinned teleoperation systems with the emphasis on the manipulator teleoperation systems till late eighties [2]. Over the past few years, mobile robot teleoperation and navigation tasks have aroused increasing attention [3–5]. Since the introduction of the virtual environmental impedance [3,6] in the late 1990s, research results achieved from manipulator teleoperation systems began to be transferred into the research of mobile robot teleoperation systems. With the early work demonstrating the effectiveness of the force feedback in facilitating navigation tasks for the teleoperation of terrestrial wheeled robots [7–9], bilateral haptic/force feedback teleop-
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Xiaolei Hou [email protected] School of Automation, Northwestern Polytechnical University, Xi’an, China
eration of mobile robots starts to evolve into a new research focus in the robotics community [10–15]. Collision and obstacle avoidance is of crucial importance to mobile robot teleoperation systems, requiring significa
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