Haptic teleoperation of a multirotor aerial robot using path planning with human intention estimation

Hou, Xiaolei

doi:10.1007/s11370-020-00339-2

Cited by 8 publications

(7 citation statements)

References 32 publications

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“…One of the main applications of teleoperation devices is drone control [ 26 ]. Due to their versatility, teleoperation devices can contribute to both military and healthcare [ 25 , 27 ], including environmental [ 28 ], and as a real-time monitoring mechanism [ 29 ]. Another interesting application of teleoperation is surgical systems, making possible minimally invasive human telesurgery over long distances [ 30 , 31 ].…”

Section: Related Workmentioning

confidence: 99%

Semi-Remote Gait Assistance Interface: A Joystick with Visual Feedback Capabilities for Therapists

Gomez-Vargas

et al. 2021

Sensors

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The constant growth of pathologies affecting human mobility has led to developing of different assistive devices to provide physical and cognitive assistance. Smart walkers are a particular type of these devices since they integrate navigation systems, path-following algorithms, and user interaction modules to ensure natural and intuitive interaction. Although these functionalities are often implemented in rehabilitation scenarios, there is a need to actively involve the healthcare professionals in the interaction loop while guaranteeing safety for them and patients. This work presents the validation of two visual feedback strategies for the teleoperation of a simulated robotic walker during an assisted navigation task. For this purpose, a group of 14 clinicians from the rehabilitation area formed the validation group. A simple path-following task was proposed, and the feedback strategies were assessed through the kinematic estimation error (KTE) and a usability survey. A KTE of 0.28 m was obtained for the feedback strategy on the joystick. Additionally, significant differences were found through a Mann–Whitney–Wilcoxon test for the perception of behavior and confidence towards the joystick according to the modes of interaction (p-values of 0.04 and 0.01, respectively). The use of visual feedback with this tool contributes to research areas such as remote management of therapies and monitoring rehabilitation of people’s mobility.

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Section: Related Workmentioning

confidence: 99%

Semi-Remote Gait Assistance Interface: A Joystick with Visual Feedback Capabilities for Therapists

Gomez-Vargas

et al. 2021

Sensors

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“…The above two methods are local obstacle avoidance strategies. In addition, the shared teleoperation scheme with active obstacle avoidance strategy is a third solution, which fully combines human high-level decision making and machine autonomy, which greatly reduces the operating burden of the human [3,[17][18][19][20][21]. Here, trajectory planning is added for vehicle autonomous navigation to achieve obstacle avoidance.…”

Section: Introductionmentioning

confidence: 99%

“…Current studies on trajectory generation roughly include graph search, random sampling, potential field, curve interpolation, and optimal control methods [22,23]. In [19], trajectory generation based on random sampling is adopted to assist the human to operate the vehicle to achieve obstacle-free movement, but the hidden state number in HMM only divides the working space of the aerial robot into 12 equal parts, without giving a reasonable explanation and calculation as to why it is 12 parts. Moreover, in the process of path planning, RRT planning algorithm is adopted, which is unable to deal with complex constraints, and its generated motion state is blind, leading to instability of the final solution-meaning the solution is usually not optimal.…”

Section: Introductionmentioning

confidence: 99%

“…It is mentioned in an earlier study that several "move and wait" cycles were used to process communication delay compensation. It is also shown that predictor display can greatly improve the handling performance of master-slave systems, and the target position generation is an important part of bilateral shared teleoperation control schemes with trajectory generation [19]. Based on the above considerations, the manipulative force of the human is sampled in this paper, mapping it to the vehicle speed, which is combined with the communication delay in the teleoperation system, together constituting the target position of the vehicle at the next moment.…”

Section: Introductionmentioning

confidence: 99%

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Unified Human Intention Recognition and Heuristic-Based Trajectory Generation for Haptic Teleoperation of Non-Holonomic Vehicles

Zhang

Zhao

et al. 2023

Machines

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In this paper, a novel bilateral shared control approach is proposed to address the issue of strong dependence on the human, and the resulting burden of manipulation, in classical haptic teleoperation systems for vehicle navigation. A Hidden Markov Model (HMM) is utilized to handle the Human Intention Recognition (HIR), according to the force input by the human—including the HMM solution, i.e., Baum–Welch algorithm, and HMM decoding, i.e., Viterbi algorithm—and the communication delay in teleoperation systems is added to generate a temporary goal. Afterwards, a heuristic and sampling method for online generation of splicing trajectory based on the goal is proposed innovatively, ensuring the vehicle can move feasibly after the change in human intention is detected. Once the trajectory is available, the vehicle velocity is then converted to joystick position information as the haptic cue of the human, which enhances the telepresence. The shared teleoperation control framework is verified in the simulation environment, where its excellent performance in the complex environment is evaluated, and its feasibility is confirmed. The experimental results show that the proposed method can achieve simple and efficient navigation in a complex environment, and can also give a certain situational awareness to the human.

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“…The fuzzy control method is used to establish an obstacle avoidance system to judge the distance between the obstacle and the robot. Test results show that the system has high environmental awareness, and has good path planning performance (Hou X., 2020).…”

Section: Introductionmentioning

confidence: 99%

Application of Big Data Analysis in Path Planning of Intelligent Picking Robot

Zhao¹,

Stoyanets²,

Li³

2021

INMATEH

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In order to solve the problem of autonomous movement of intelligent picking robot, a method for big data analysis is proposed. The data collected by laser ranging sensor, CCD camera and electronic compass are analyzed to determine the current robot position and heading. The walking route for the robot is preset of the orchard. The sign for the digital tube is installed, so the coordinates for the sign are known. Electronic compass is used to determine the heading angle of robot. The CCD camera captures the sign image, and adopts the methods of image graying, image segmentation, image corrosion and image thinning to extract the digital tube image data on the sign. Fuzzy control method is used to identify digital tube numbers on the ground sign, and CCD camera scans whether there are obstacles in front of the road at the same time. The laser ranging sensor completes two tasks: ① detecting the sign distance and direction angle of the distance, and calculating the current position and heading angle of the robot through the coordinates of the sign; (2) detect the distance from obstacles, and start the obstacle avoidance system when it is less than 1m. The path planning system of picking robot based on big data analysis relies on a variety of sensors, and has a strong ability to perceive orchard environment, and it has high ability of path planning.

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Haptic teleoperation of a multirotor aerial robot using path planning with human intention estimation

Cited by 8 publications

References 32 publications

Semi-Remote Gait Assistance Interface: A Joystick with Visual Feedback Capabilities for Therapists

Semi-Remote Gait Assistance Interface: A Joystick with Visual Feedback Capabilities for Therapists

Unified Human Intention Recognition and Heuristic-Based Trajectory Generation for Haptic Teleoperation of Non-Holonomic Vehicles

Application of Big Data Analysis in Path Planning of Intelligent Picking Robot

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