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To ensure the motion attitude and stable contact force of massage robot working on unknown human tissue environment, this study aims to propose a robotic system for autonomous massage path planning and stable interaction control.

First, back region extraction and acupoint recognition based on deep learning is proposed, which provides a basis for determining the working area and path points of the robot. Second, to realize the standard approach and movement trajectory of the expert massage, 3D reconstruction and path planning of the massage area are performed, and normal vectors are calculated to control the normal orientation of robot-end. Finally, to cope with the soft and hard changes of human tissue state and body movement, an adaptive force tracking control strategy is presented to compensate the uncertainty of environmental position and tissue hardness online.

Improved network model can accomplish the acupoint recognition task with a large accuracy and integrate the point cloud to generate massage trajectories adapted to the shape of the human body. Experimental results show that the adaptive force tracking control can obtain a relatively smooth force, and the error is basically within ± 0.2 N during the online experiment.

This paper incorporates deep learning, 3D reconstruction and impedance control, the robot can understand the shape features of the massage area and adapt its planning massage path to carry out a stable and safe force tracking control during dynamic robot–human contact.

This paper aims to propose an electromagnetic prismatic joint with variable stiffness. The joint can absorb the sudden shocks and improve the natural dynamics of robotics. The ability of regulating the output stiffness can also be used for force control in industrial applications.

Unlike some existing designs of variable stiffness joints (VSJs) in which the stiffness regulation is implemented using the stiffness adjustment motor and mechanisms, the main structure of the electromagnetic VSJ is a permanent magnet (PM) arranged inside coaxial cylinder coils. The adjustment of input current can cause the change of magnetic force between the PM and the cylinder coils, and thus leads to the variation of output stiffness.

According to the theoretical model, the output stiffness of the electromagnetic VSJ is linearly proportional to the input current. The experiments further indicate that the current-controlled stiffness can make the stiffness variation response of this VSJ more rapid for practical applications. Due to the large damping introduced by the copper-based self-lubrication bearings, the VSJ shows good properties in motion positioning and trajectory tracking.

In summary, the electromagnetic VSJ is compact in size and light in weight. It is possible to realize the online adaptability to work conditions with dynamic load by using this VSJ.