The paper aims to propose a magnetic actuated capsule microrobotic system, which is composed of a magnetically actuated microrobot with a screw jet mechanism, a driving system, and a positioning system. The magnetically actuated microrobot embedded an O-ring magnet as an actuator has potential for achieving a particular task, such as medical diagnose or drug delivery. The driving system composes of a three axes Helmholtz coils to generate a rotational magnetic field for controlling the magnetically actuated microrobot to realize the basic motion in pipe, e.g., forward/backward motion and upward/downward motion. The positioning system is used to detect the pose of the magnetically actuated microrobot in pipe. We will discuss the shape of the Helmholtz coils and the magnetic field around the O-ring magnet to obtain an optimal performance of the magnetically actuated microrobot. The experimental result indicated that the microrobot with screw jet motion has a flexible movement in pipe by adjusting the rotational magnetic field plane and the magnetic field changing frequency.

In this paper, a single leg platform for quadruped robots is designed based on the motivation of high-speed locomotion. The leg is designed for lightweight and low inertia with a structure of three joints by imitating quadruped animals. Because high acceleration and extensive loadings will be involved on the legs during the high-speed locomotion, the trade-off between the leg mass and strength is specifically designed and evaluated with the finite element analysis. Moreover, quadruped animals usually increase stride frequency and decrease contact time as the locomotion speed increases, while maintaining the swing duration during trot gait. Inspired by this phenomenon, the foot-end trajectory for quadruped robots with a high-speed trot gait is proposed. The gait trajectory is planned for swing and stance phase; thus the robot can keep its stability with adjustable trajectories while following a specific gait pattern. Especially for the swing phase, the proposed trajectory can minimize the maximum acceleration of legs and ensure the continuity of position, speed, and acceleration. Then, based on the kinematics analysis, the proposed trajectory is compared with the trajectory of Bézier curve for the power consumption. Finally, a simulation with Webots software is carried out for verifying the motion stability with two trajectory planning schemes respectively. Moreover, a motion capture device is used for evaluating the tracking accuracy of two schemes for obtaining an optimal gait trajectory suitable for high-speed trot gait.

This paper proposes a new robotic rehabilitation training platform that is motivated by the requirement for adjusting the training strategy and intensity in a patient-specific manner. The platform is implemented for tele-rehabilitation and is comprised of a haptic device operated by therapists, a lightweight exoskeleton worn by patients and a visually shared model. Through the visually shared model, the motion of the therapist and patient are measured and mapped to the motion of the corresponding object. Thus, the force generated by the therapist can be transferred to the patient for delivering training, while real-time force feedback with high transparency can be provided to the therapist so they know the amount of force being applied to patients in real time. In particular, both assistive therapy in the early stages and resistive therapy in the later stages of stroke can be performed. The home-use exoskeleton device is specifically designed to be light-weight and compliant for safety. The patient-exoskeleton and therapist-haptic interaction performance is evaluated by observing the muscle activities and interaction force. Two volunteers were requested to imitate the process of the therapist-in-the-loop training to evaluate the proposed platform.

According to the neuro-rehabilitation theory, compared with unilateral training, bilateral training is proven to be an effective method for hemiparesis, which affects the most part of stroke patients. In this study, a novel bilateral rehabilitation training system, which incorporates a lightweight exoskeleton device worn on the affected limb; a haptic device (Phantom Premium), which is used for generating a desired tactile feedback for the affected limb; and a VR (virtual reality) graphic interface, has been developed. The use of VR technology during rehabilitation can provide goal directed tasks with rewards and motivate the patient to undertake extended rehabilitation. This paper is mainly focused on elbow joint training, and other independent joints can be trained by easily changing the VR training interface. The haptic device is adopted to enable patients to use their own decision making abilities with a tactical feedback. Integrated with a VR-based graphic interface, the goal-oriented task can help to gradually recovery their motor function with a coordinative motion between two limbs. In particular, the proposed system can accelerate neural plasticity and motor recovery in those patients with little muscle strength by using the exoskeleton device. The exoskeleton device can provide from relatively high joint impedance to near-zero impedance, and can provide a partial assist as the patient requires.

Given that the current microrobot cannot achieve fixed-point and quantitative drug application in the gastrointestinal (GI) tract, a targeted drug delivery microrobot is proposed, and its principle and characteristics are studied. Through the control of an external magnetic field, it can actively move to the affected area to realize the targeted drug delivery function. The microrobot has a cam structure connected with a radially magnetized permanent magnet, which can realize two movement modes: movement and targeted drug delivery. Firstly, the magnetic actuated capsule microrobotic system (MACMS) is analyzed. Secondly, the dynamic model and quantitative drug delivery model of the targeted drug delivery microrobot driven by the spiral jet structure are established, and the motion characteristics of the targeted drug delivery microrobot are simulated and analyzed by the method of Computational Fluid Dynamics (CFD). Finally, the whole process of the targeted drug delivery task of the microrobot is simulated. The results show that the targeted drug delivery microrobot can realize basic movements such as forward, backward, fixed-point parking and drug delivery through external magnetic field control, which lays the foundation for gastrointestinal diagnosis and treatment.

To explore the positioning tracking problem of capsule endoscopy, the advantages of magnetic positioning technology as a solution are highlighted. Considering that the capsule robot is small and cannot have enough built-in driving and positioning tracking devices, new technical means are needed to solve this problem. Therefore, we propose a prediction method based on the BP neural network model to locate the position of the robot in the magnetic field. To evaluate the accuracy of a BP neural network model with three hidden layers, the predicted results of the model, the results of the nonlinear algorithm, and the actual coordinate points were compared to determine whether it could accurately predict the actual coordinate points. We set the criterion for correct localization as the Euclidean distance between the predicted coordinate point and the actual coordinate point being less than 0.01 mm, and obtained the localization rates of the nonlinear localization algorithm and the neural network prediction method as 46.7% and 95.2%, respectively. By comparing the results, it is found that the positioning accuracy predicted by the BP neural network is higher and has higher accuracy. This shows that the prediction accuracy of the algorithm is more optimized, which can meet the real-time and positioning accuracy requirements of the capsule endoscope.