A Research on Face Profile Surface Acquisition and Robot Trajectory Planning

Hu, Yan; Zhai, Jingmei; Chen, Yanbiao

doi:10.1109/iciscae48440.2019.221712

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…A Kinect 2 vision system is used to obtain facial contour information, which consists of only 1,347 feature points. Although a series of methods such as feature optimization of facial points cloud model, triangle mesh refinement and mesh model Voronoi optimization are taken to reduce error, there is a certain dimension error between the 3D reconstruction model and real face contour (Hu et al , 2019). Figure 12 shows massage trajectories on the face model, which will apply a 2.5 N contact force in the normal direction.…”

Section: Methodsmentioning

confidence: 99%

An intelligent control system for robot massaging with uncertain skin characteristics

Zhai

Zeng

2022

Self Cite

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Purpose To ensure accurate position and force control of massage robot working on human body with unknown skin characteristics, this study aims to propose a novel intelligent impedance control system. Design/methodology/approach First, a skin dynamic model (SDM) is introduced to describe force-deformation on the human body as feed-forward for force control. Then a particle swarm optimization (PSO) method combined with graph-based knowledge transfer learning (GKT) is studied, which will effectively identify personalized skin parameters. Finally, a self-tuning impedance control strategy is designed to accommodate uncertainty of skin dynamics, system delay and signal noise exist in practical applications. Findings Compared with traditional least square method, genetic algorithm and other kinds of PSO methods, combination of PSO and GKT is validated using experimental data to improve the accuracy and convergence of identification results. The force control is effective, although there are contour errors, control delay and noise problems when the robot does massage on human body. Originality/value Integrating GKT into PSO identification algorithm, and designing an adaptive impedance control algorithm. As a result, the robot can understand textural and biological attributes of its surroundings and adapt its planning activities to carry out a stable and accurate force tracking control during dynamic contacts between a robot and a human.

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Section: Methodsmentioning

confidence: 99%

An intelligent control system for robot massaging with uncertain skin characteristics

Zhai

Zeng

2022

Self Cite

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Face Detection-Based Depth Estimation by 2D and 3D Cameras: A Comparison

Parikh

Joshi

Trivedi

2022

2022 28th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

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Dynamic Path Planning Based on 3D Cloud Recognition for an Assistive Bathing Robot

Meng,

Kang,

Liu

et al. 2024

Electronics

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Assistive bathing robots have become a popular point due to their metrics, such as a humanoid working approach in the solution of elder care. However, the abilities of dynamic recognition and path planning are the key to obtain the advantages. This paper proposes a novel approach to recognize and track the dynamical human back, and path planning on it via a 3D point cloud. Firstly, the human back geometric features are recognized through coarse-to-fine alignment. The Intrinsic Shape Signature (ISS) algorithm combined with the Fast Point Feature Histogram (FPFH) and the Sample Consensus Initial Alignment (SAC-IA) algorithm are adopted to complete the coarse alignment, and the Iterative Closest Point (ICP) algorithm is applied to the fine alignment to improve the accuracy of recognition. Then, the dynamic transformation matrix between the contiguous recognized back is deduced based on spatial motion between two adjacent recognized back point clouds. The path can be planned on the tracked human back. Finally, a set of testing experiments are conducted to verify the proposed algorithm. The results show that the running time is reduced by 66.18% and 96.29% compared with the other two common algorithms, respectively.

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A Research on Face Profile Surface Acquisition and Robot Trajectory Planning

Cited by 3 publications

References 6 publications

An intelligent control system for robot massaging with uncertain skin characteristics

An intelligent control system for robot massaging with uncertain skin characteristics

Face Detection-Based Depth Estimation by 2D and 3D Cameras: A Comparison

Dynamic Path Planning Based on 3D Cloud Recognition for an Assistive Bathing Robot

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