Tingting Su

The operation of tibial fracture reduction is complex and may involve risks of iatrogenic injuries due to fatigue or insufficient experience of the surgeon. Therefore, this paper proposes a tibial fracture reduction trajectory planning method based on dynamic movement primitives (DMP) and artificial potential fields (APF) to avoid the collision between the distal and proximal fracture fragments during the reduction process and to achieve safe tibial fracture reduction. First, DMP is used to learn the motion characteristics from the orientation demonstration trajectory, generating a new orientation trajectory for the distal fracture fragment. Second, DMP with an obstacle avoidance mechanism based on APF is used to learn the motion characteristics from the position demonstration trajectory, generating a position trajectory for the distal fracture fragment with obstacle avoidance capability. Then, the position trajectory and the orientation trajectory are combined synchronously to form the reduction trajectory. Finally the aforementioned trajectory is optimized to minimize both the the sum of squared velocities and the the sum of squared accelerations of all branch chains under specific constraints, enabling the robot to perform a smooth fracture reduction. Simulations and experiments are conducted, and the results demonstrate that the proposed method can effectively perform trajectory planning for tibial fracture reduction. The proposed method can provide technical references for the trajectory planning and obstacle avoidance problems of orthopedic robots in unstructured environments.

Due to the limited size of natural orifices, continuum surgical robots used for natural orifice surgery must be miniaturized, while maintaining their load capacity. To solve this challenging problem, this article first proposes a bio-inspired extensible variable-section continuum surgical robot based on a compression spring structure to improve its stiffness and load capability. Second, the stiffness advantages of the variable-section continuum surgical robot over the constant-section continuum surgical robot and the slope magnitude’s influences on the stiffness are analyzed. Third, a kinematic model of the proposed variable-section continuum surgical robot is established based on the geometric relationship of the variable-section structure. Stiffness and kinematic verification experiments were conducted to verify the enhanced load capacity of the variable-section continuum robot and to validate the kinematic model. The average stiffness of the variable-section continuum robot is improved by at least 31.5% compared with the constant-section continuum robot. Finally, we demonstrate the motion dexterity of the variable-section continuum robot.

Robots often need to interact with environment while performing operation tasks. In this article, an interactive pick-and-place operation (PPO) trajectory planning method with adjustable interaction point is proposed for Delta robot to realize the flexible operation. First, the kinematics of Delta robot is briefly introduced. Then, by using the characteristics of Pythagorean-Hodograph (PH) curve, the interactive pick-and-place operation path (PPOP) is designed on the basis of the general PPOP. Two different scenarios, where the interaction point is inside and outside the general PPOP, are investigated and analyzed. In particular, when the interaction point is inside the general PPOP, two different options are constructed to perform the PPO, one option is that the two PH curves form a J-shaped curve, and the other option is that the two PH curves form an S-shaped curve. In addition, the motion profile of the interactive PPOP is configured. Finally, the proposed method is verified by simulations and experiments, and the results show that the proposed method can achieve smooth motion, and the trajectory shape can be adjusted locally or globally by configuring the parameters according to the actual task, so different PPO trajectories can be realized to meet the requirements of various operating environments, thus improving the flexibility of the Delta robot system.

Accurate acquisition of interactive information is crucial for the effective execution of rehabilitation training. However, due to model and sensor errors, it is difficult to obtain interactive information accurately and quickly. To overcome these challenges, a novel accurate and fast estimation method for the human–robot interaction torques (HRITs) is proposed in this article. First, the HRIT model with order adaptive adjustment ability (HMOAA) is constructed. The polynomial order of HMOAA can be adaptively adjusted based on the partial state estimation, which is more consistent with the dynamic time-varying characteristics of HRIT. Second, the Sage–Husa adaptive strong tracking Kalman filter (SHASTKF) is designed based on the modified Sage–Husa adaptive Kalman filter (SHAKF) and strong tracking Kalman filter (STKF). The SHASTKF can quickly track the abrupt HRIT changes when the subject suddenly exerts active torques in rehabilitation training. Moreover, it also has the ability to recursively estimate the noise characteristics, and can stably complete the HRIT estimation task when the noise characteristics are unknown. Finally, simulations and experiments are conducted to validate the proposed method, and the comparison results demonstrate that the proposed method has good torque estimation precision and fast tracking ability of abrupt changes in HRITs.

The self-aligning capability of an exoskeleton is important to ensure wearing comfort, and the delicate motion ability of the exoskeleton is essential for motion assistance. Designing a self-aligning exoskeleton that offers improved wearing comfort and enhanced motion-assistance functions remains a challenge. This paper proposes a novel spatial self-aligning mechanism for a knee exoskeleton to enable simultaneous assistance in the flexion and extension (FE) of the knee joint and the internal and external rotation (IER) of the hip joint. Additionally, considering the misalignment of the human-robot joint axes, a kinematic model of the knee exoskeleton is established and analyzed to demonstrate the kinematic compatibility of the exoskeleton. Furthermore, a global torque manipulability (GTM) index is proposed to evaluate the effects of dimensional parameters on the exoskeleton’s performance, and then the knee exoskeleton is optimized according to the GTM index. Finally, experiments are conducted to validate the performance of the proposed exoskeleton. The experimental results show that during knee FE and hip IER, the proposed exoskeleton exhibits lower interaction forces and torques than existing exoskeletons.

The development of robotic hand that can imitate human movements has always been an important research topic. In this paper, a linkage-driven underactuated three-finger hand is proposed to imitate the flexion/extension (f/e) and abduction/adduction (a/a) motions of human hand. The robotic hand has three identical underactuated fingers, each of which contains an underactuated planar linkage, a spherical four-bar mechanism, and a set of bevel gears. The spherical four-bar mechanism is designed to provide 2-degree-of-freedom actuation, driving the f/e and a/a motions of the proximal joint simultaneously. Based on screw theory, the kinematic model of the spherical mechanism is established, and the maximum available workspace index (MAW) of the spherical mechanism is proposed to evaluate the workspace with the same adduction and abduction angle ranges. The effects of the parameters of the spherical mechanism on the MAW and the transmission efficiency are obtained, and the parameters of the spherical mechanism are optimized. The optimization results show that the MAW of the spherical mechanism can be increased by up to 3.5 times. Finally, experiments are carried out to show the proposed robotic hand can perform simultaneous adaptive grasping and in-hand manipulation. Note to Practitioners —The robotic hand is of great significance for replacing workers in heavy, repetitive, and unsafe working environments. Uncertain environments in non-manufacturing fields, such as industries for pick-and-place, sorting, palletizing, assembly and other operations, marine development, and medical service, require that robotic hands can operate tasks like human hands. Inspired by the human hand with the f/e and a/a motions, a linkage-driven underactuated three-finger hand is proposed in this paper to imitate the functions of the human hand. Due to its underactuated characteristics and a/a function, the designed robotic hand is more dexterous and economical. The effects of the design parameters of the spherical mechanism on the MAW and the transmission efficiency are analyzed, and the parameters of the spherical mechanism are optimized to improve the performance of the robotic hand. This approach can be used in other industrial applications related to the robotic hand or the spherical mechanism.

It has been nearly 60 years since the introduction of the Gough–Stewart manipulator (GSM). With the advantages of superior load capacity and high precision, the GSM still plays an important role in many fields. However, the GSM has limitations such as a small workspace and complex singularities. To overcome these problems, a novel kinematically redundant parallel robot is designed with three redundant actuators added on the basis of the GSM. First, the structure of the proposed robot is introduced, and the kinematics of the proposed robot is established. Second, the workspaces of the proposed robot are analyzed, and the results show that the position workspace volume and the maximum torsion and orientation angles of the proposed robot can be improved effectively. Third, the singularities of the proposed robot and the GSM are compared based on the Jacobian matrices. Finally, the multi-parameter, multi-objective optimization is used to optimize the geometric parameters of the proposed robot, and an experimental prototype of the proposed robot is designed based on the optimization results.

In this paper, a Pythagorean-Hodograph (PH) curve-based pick-and-place operation trajectory planning method for Delta parallel robots is proposed, which realizes the flexible control of pick-and-place operations to meet the requirements of various practical scenarios. First, according to the geometric relationship of pick-and-place operation path, different pick-and-place operations are classified. Then trajectory planning is carried out for different situations, respectively, and in each case, the different polynomial motion laws adopted by the linear motion segment and the curved motion segment are solved. Trajectory optimization is performed with the motion period as optimization objective. The proposed method is easier to implement, and at the same time satisfies the safety, optimization, mobility, and stability of the robot; that is, the proposed method realizes obstacle avoidance, optimal time, flexible control of the robot trajectory, and stable motion. Simulations and experiments verify the effectiveness of the method proposed in this paper. The proposed method can not only realize the fast, accurate, and safe operation in intelligent manufacturing fields such as rapid classification, palletizing, grasping, warehousing, etc., but its research route can also provide a reference for trajectory planning of intelligent vehicles in logistics system.