In this paper, the design and experimental validation of a knee exoskeleton are presented. The exoskeleton can capture the negative work from the wearer’s knee motion while decreasing the muscle activities of the wearer. First, the human knee biomechanics during the normal walking is described. Then, the design of the exoskeleton is presented. The exoskeleton mainly includes a left one-way transmission mechanism, a right one-way transmission mechanism, and a front transmission mechanism. The left and right one-way transmission mechanisms are designed to capture the negative work from the wearer’s knee motion in the stance and swing phases, respectively. The front transmission mechanism is designed to transform the bidirectional rotation of the wearer’s knee joint into the generator unidirectional rotation. Additionally, the modeling and analysis of the energy harvesting of the exoskeleton is described. Finally, walking experiments are performed to validate the effectiveness of the proposed knee exoskeleton. The testing results verify that the developed knee exoskeleton can output a maximum power of 5.68 ± 0.23 W and an average power of 1.45 ± 0.13 W at a speed of 4.5 km/h in a gait cycle. The average rectus femoris and semitendinosus activities of the wearers in a gait cycle are decreased by 3.68% and 3.40%, respectively.

The frog-inspired robots with amphibious locomotion ability have greatest application prospects and practical value in the fields of resource exploration and environmental reconnaissance. Although frog-inspired robots have been of interest over many years, research on frog-inspired amphibious robots is still in its infancy. Since the locomotion mechanism is the basis for the research of frog-inspired amphibious robots, the research methods of the single motion mechanism of frogs are firstly inductive analyzed, and a reference scheme is proposed to inspire the research on the amphibious motion mechanism. Then, we collect and introduce a systematic discussion of the research status of frog-inspired robots according to the locomotion mode. The characteristics of the robots are analyzed from the aspects of design concept, structural characteristics, driving method, and motion performance. Finally, the technical challenges faced by the research on the frog-inspired robots are analyzed, and the development trend is predicted. The authors hope that this study can provide an informative reference for future research in the direction of frog-inspired amphibious robot.

This paper proposed an elastodynamic modeling method combined with independent displacement coordinates and substructure synthesis technology. Firstly, the connecting rod was discretized, and the elastodynamic control equation for each element was established. The multipoint constraint element theory, linear algebra, and singularity analysis were used to identify the globally independent displacement coordinates of the manipulator. On this basis, the elastodynamic model using the substructure synthesis for the 3-PRS parallel manipulator (PM) was developed, with its natural frequencies distribution in the regular workspace discussed. The comparison with the finite-element results showed that the maximum error of the first three-order natural frequencies was within 1.03%, which verified the correctness of the analytical model. The proposed elastodynamic model included all the kinematic constraints of the manipulator without increasing the Lagrangian multiplier. The method is computationally efficient and assesses the dynamic behaviors of the mechanism at the predesign phase.

In dynamic outdoor environments characterized by turbulent airflow and intermittent odor plumes, robotic odor plume tracking remains challenging, because existing algorithms heavily rely on manually tuning or learning from expert experience, which are hard to implement in an unknown environment. In this paper, a multi-continuous-output Takagi–Sugeno–Kang fuzzy system was designed and tuned with reinforcement learning to solve the robotic odor source localization problem in dynamic odor plumes. Based on the Lévy Taxis plume tracking controller, the proposed fuzzy system determined the parameters of the controller based on the robot’s observation and guided the robot to turn and move towards the odor source at each searching step. The trained fuzzy system was tested in simulated filament-based odor plumes dispersed by a changing wind field. The results showed that the performance of the proposed fuzzy system-based controller trained with reinforcement learning can achieve a similar success rate and higher efficiency compared with a manually tuned and well-designed fuzzy system-based controller. The fuzzy system-based plume tracking controller was also validated through real robotic experiments.

Modern approaches for exploration path planning generally do not assume any structural information regarding the operational area. Therefore, they offer good performance when the region of interest is entirely unknown. However, for some applications such as plantation forest surveying, partial information regarding the survey area is known before the exploration process. Because the region of interest consists only of the lower portions of the tree stems themselves, the ground and high-elevation sections of the environment are unimportant and do not need to be observed. Due to these unconventional conditions, existing methods favoring faster survey speeds produce suboptimal surveys as they do not try and ensure even coverage across the entire exploration volume, while methods that favor reconstruction accuracy produce excessively long survey times. This work proposes a structured exploration approach specifically for plantation forests utilizing a lawnmowing pattern to maximize coverage while minimizing re-visited regions, guiding the unmanned aerial vehicle to visit all areas. Experiments are conducted in various environments, with comparisons made to state-of-the-art exploration planners regarding survey time and coverage. Results suggest that the proposed methods produce surveys with significantly more predictable coverage and survey times at the expense of a longer survey.

Minimally invasive surgery (MIS) has been an essential tool in the surgical sector for many years due to its crucial advantages compared to open surgery. To overcome remaining limitations, teleoperated MIS experienced a strong emergence. However, the widespread usage of such systems is hindered by the enormous financial hurdle. The use of standard components and conventional tools for teleoperated MIS can facilitate integration into existing hospital workflows and can be a cost-efficient and versatile approach for research purposes. To compensate for the lack of haptic feedback, some teleoperation setups inherit a sensor system allowing them to record interaction forces and display them at the user interface. In research and in commercially available systems, different positions for the sensor can be found. In this paper, mechanical interfaces for the guidance and actuation of non-wristed and wristed standard instruments are presented. Furthermore, a method for the extracorporeal measurement of interaction forces is presented, characterized, and discussed. The overall mean relative error of the magnitude of the interaction force is 9.4%, while the overall mean absolute error of the force vector is 14.4$^{\circ }$, both below the respective human differential perception threshold. The presented measurement method is a simple, yet sufficiently accurate approach to measure interaction forces in surgical telemanipulation.

For the large redundant manipulator, due to its long working distance and large mass, the number of links (i.e., manipulator’s arms) that can be driven to move simultaneously is limited. Otherwise, the control accuracy and motion stability of the manipulator will deteriorate. Focusing on that, a weighted Newton iteration (WNI) algorithm for trajectory planning of the manipulator is firstly proposed, where the motion of the manipulator joints is controlled by a weight matrix, which is constant and related to each link’s energy consumption. To dynamically adjust the weight matrix according to kinematic constraints and acquire better energy efficiency, an adaptive WNI (AWNI) algorithm is further proposed. In AWNI, the weight matrix is adjusted in real-time during the planning process, with considerations of the kinematic constraints and the energy consumption of the manipulator. The switch of the links between the working state and the non-working state is made through the weight matrix to achieve flexible control of the manipulator motion. Two evaluation functions are established to validate the effectiveness of AWNI in energy saving and motion stability control. Taking a 6 degrees of freedom (DOF) manipulator as an example, simulation experiments on trajectory planning are carried out and the results show the effectiveness of the proposed AWNI algorithm.

Due to the efficient and flexible flight ability of bats, bat-like robots have become the focus of research in the field of bionic robots. Aerodynamic calculation is an important part of the research field of bat-like robot, which is the basis of the structure design and flight controller design of bat-like robot. However, due to the complex flight mechanism of bats, there is no mature theoretical method to calculate the flight aerodynamic force of bat-like robots. To solve this problem, this paper takes the membrane of a bat-like robot as the research object and analyzes in detail the effects of wing folding and unfolding and flexible deformation of the membrane on the chord length, passive torsion angle and relative velocity. Based on quasi-steady state model and blade element method, a set of aerodynamic calculation method for flexible deformed wing is established. In order to verify the effectiveness of the proposed method, the theoretical calculation results and the results of the fluid-structure interaction simulation are compared and analyzed under various working conditions. The two results are in good agreement under each working condition, and the errors are all within reasonable range, which proves the effectiveness of the method. This study can provide a theoretical basis for rational structure design and precise flight control of bat-like robot.

The lower extremity rehabilitation exoskeleton is mainly used to help patients with movement disorders complete rehabilitation training. For the human-machine interaction problem of the lower limb rehabilitation exoskeleton, a fuzzy radial-based impedance (RBF-FVI) controller is proposed in this study. A six degree of freedom (DOF) lower extremity rehabilitation exoskeleton was developed, and the human-machine coupling dynamics model was established. To realize the compliance control of the human-machine coupling system, a novel RBF-FVI controller is designed, which includes an inner-loop fuzzy position control module and an outer-loop impedance control module. The inner-loop fuzzy position control module is mainly used to achieve the tracking control of the desired training trajectory and position adjustment amount. The outer-loop impedance control module regulates the impedance parameters and compensates for the uncertainty terms. The superiority of the proposed controller in trajectory following is verified through simulation and comparison tests. The hardware test of the human-machine coupling system was carried out, and the test results showed that the subject and the exoskeleton system could realize a coordinated and smooth movement.

Joint actuators with a compact size and high power density are necessary for robots with rotating joints, making the hydraulic actuator (HyA) an ideal actuator candidate. This paper presents a joint HyA with the following characteristics: compact installation size of 70 mm × 92.5 mm × 145 mm, low weight of 1.93 kg, high output torque of 742.2 Nm/531.09 Nm in two directions under 210 bar, high torque to weight ratio of 265.5 Nm/kg, low internal leakage of about 9 mL/min, zero external leakage, low starting pressure of 0.26 MPa/0.39 MPa in two directions, and a large rotation angle of 135 degrees. Compared with HyAs that have been applied in robot joints, the HyA proposed in this paper can greatly reduce the joint weight, reduce the joint size, and ensure the control performance of the joint movement.

In addition, a dynamic model of the HyA is established. Based on this, some dynamic design suggestions are given. Furthermore, a simple position and torque control algorithm for the HyA is proposed. Finally, some experiments are carried out to verify the performance of the HyA.

Transbronchial lung biopsy is an effective and less-invasive treatment for the early diagnosis of lung cancer. However, the limited dexterity of existing endoscopic instruments and the complexity of bronchial access prevent the application of such procedures mainly for biopsy and diagnosis. This paper proposes a flexible robot for transbronchial lung biopsy with a cable-driven mechanism-based flexible manipulator. The robotic system of transbronchial lung biopsy is presented in detail, including the snake-bone end effector, the flexible catheters and the actuation unit. The kinematic analysis of the snake-bone end effector is conducted for the master-slave control. The experimental results show that the end effector reaches the target nodule through a narrow and tortuous pathway in a bronchial model. In conclusion, the proposed robotic system contributes to the field of advanced endoscopic surgery with high flexibility and controllability.

The identification of nonlinear terms existing in the dynamic model of real-world mechanical systems such as robotic manipulators is a challenging modeling problem. The main aim of this research is not only to identify the unknown parameters of the nonlinear terms but also to verify their existence in the model. Generally, if the structure of the model is provided, the parameters of the nonlinear terms can be identified using different numerical approaches or evolutionary algorithms. However, finding a non-zero coefficient does not guarantee the existence of the nonlinear term or vice versa. Therefore, in this study, a meticulous investigation and statistical verification are carried out to ensure the reliability of the identification process. First, the simulation data are generated using the white-box model of a direct current motor that includes some of the nonlinear terms. Second, the particle swarm optimization (PSO) algorithm is applied to identify the unknown parameters of the model among many possible configurations. Then, to evaluate the results of the algorithm, statistical hypothesis and confidence interval tests are implemented. Finally, the reliability of the PSO algorithm is investigated using experimental data acquired from the UR5 manipulator. To compare the results of the PSO algorithm, the nonlinear least squares errors (NLSE) estimation algorithm is applied to identify the unknown parameters of the nonlinear models. The result shows that the PSO algorithm has higher identification accuracy than the NLSE estimation algorithm, and the model with identified parameters using the PSO algorithm accurately calculates the output torques of the joints of the manipulator.