Southeast University

Ke Shi

Aiguo Song

Huijun Li

Baoguo Xu

Hong Zeng

Xinyu Tang

Ye Li

Yunxia Ouyang

The present invention discloses a distributed active/passive hybrid cable drive system, including a direct current motor, a magnetorheological actuator module, and a drive gear set. The direct current motor provides power for the system, the magnetorheological actuator adjusts output, a cable is driven to move by using a reel fixedly connected to an output shaft, the power is transmitted to a tail end by using the cable along a Bowden cable, and the tail end is connected to a controlled object, to implement control. The distributed active/passive hybrid cable drive system can implement controllable force output with large torque, small inertia, and high bandwidth, and has a small volume, high efficiency, and low costs compared with a pure motor drive system.

Distributed active/passive hybrid cable drive system

A virtual scene interactive rehabilitation training robot based on a lower limb connecting rod model and force sense information and a control method thereof are disclosed. The thigh, calf and foot of a leg of a human body are equated to a three-connecting rod series-connected mechanical arm. A human body leg gravity compensation model is constructed. The leg posture of a patient is detected by Kinect. An interaction force between a limb of the patient and a rehabilitation robot is detected by a force sensor on the rehabilitation robot. Then, a progressive rehabilitation training method is designed for the model. According to a set weight reduction ratio, the motion of the rehabilitation robot is controlled by judging plantar force data.

Virtual scene interactive rehabilitation training robot based on lower limb connecting rod model and force sense information and control method thereof

A method for controlling a limb motion intention recognizing and rehabilitation training robot based on force sense information includes: acquiring data of a three-dimensional force and a three-dimensional moment by a six-dimensional force sensor held in a hand; calculating forces and moments produced by a palm, a forearm and an upper arm of a human body according to a constructed human arm model to achieve recognition of limb motion intention; fixing the six-dimensional force sensor on a rocker at an end of the three-degree-of-freedom upper limb rehabilitation training robot, acquiring motion intention of an arm of the human body according to the motion intention recognition method, and controlling the rehabilitation training robot to achieve auxiliary active training under a weak active force.

Method for controlling a limb motion intention understanding and upper limb rehabilitation training robot based on force sense information and posture information

Growing community of inventors

Nanjing, China

Ke Shi