Modular robots have the advantage of self-assembling into a large and complex structure to travel through territories beyond an individual robot’s capacity. A swarm of mobile robots is combined through mechanical interconnection and joint actuation to achieve a linked or articular configuration. In this paper, to enhance the perception, actuation and docking capacity of modular robots, a parallel mechanism-based docking system and onboard visual perception system are proposed in the design of a novel compact self-assembling mobile modular robot (SMMRob). Each module is self-contained, with a sensing or joint function. The robot modules can dock with each other based on relative positioning, which employs the visual perception of passive markers or active infrared signals in different localizations. Performance experiments were conducted to evaluate the robot module. Docking experiments were performed, along with an analysis of the success and failure results. The self-assembly of snake-like and quadruped robots was achieved in response to different environments, including an obstacle, gap or stair, and experiments were performed on self-assembly into a snake-like structure.

The use of a generalized sidelobe canceler (GSC) can significantly improve the lateral resolution of medical ultrasound systems, but the contrast improvement isn’t satisfactory. Thus a new Eigenspace-based generalized sidelobe canceler (EBGSC) approach is proposed for medical ultrasound imaging, which can improve both the lateral resolution and contrast of the system. The weight vector of the EBGSC is obtained by projecting the GSC weight vector onto a vector subspace constructed from the eigenstructure of the covariance matrix, and using the new weight vector instead of the GSC ones leads to reduced sidelobe level and improved contrast. Simulated and experimental data are used to evaluate the performance of the proposed method. The Field II software is applied to obtain the simulated echo data of scattering points and circular cysts. Imaging of scattering points show that EBGSC has the same full width at half maximum (FWHM) as GSC, while the lateral resolution improves by 35.3% and 52.7% compared with synthetic aperture (SA) and delay-and-sum (DS), respectively. Compared with GSC, SA and DS, EBGSC improves the peak sidelobe level (PSL) by 23.55, 33.11 and 50.38 dB, respectively. Also the cyst contrast increase by EBGSC was calculated as 16.77, 12.43 and 26.73 dB, when compared with GSC, SA and DS, respectively. Finally, an experiment is conducted on the basis of the complete echo data collected by a medical ultrasonic imaging system. Results show that the proposed method can produce better lateral resolution and contrast than non-adaptive beamformers.

Soft linear actuators have strong deformation ability and good environmental adaptability, which have been widely used in soft robot design. However, little work has focused on designing soft linear actuators with balanced performances, featuring fast driving speed, large output displacement, being lightweight, and miniaturization. Herein, we present a novel soft linear actuator design based on the Kresling origami structure. By driving the Kresling tubes with a servo motor, the soft linear actuator has good compliance and strong environmental adaptability and can achieve a driving speed, large driving force, and high control precision comparable to the traditional electrical motor. The analytical models of the Kresling tubes and the whole actuator are respectively derived to analyze the mechanical properties, determine the optimal geometry of the Kresling tube, and evaluate the driving performance of the whole actuator. The actuator prototype is fabricated by 3D printing, and the actual driving performance is tested. It is shown that the prototype can achieve a maximum output displacement of 18.9 mm without payload or 16 mm under a payload of 30 N. Finally, as a case study, the soft linear actuator is applied to a crawling robot, where the maximum moving speed of 28 mm/s is reached.

Multi-agent differential games usually include tracking policies and escaping policies. To obtain the proper policies in unknown environments, agents can learn through reinforcement learning. This typically requires a large amount of interaction with the environment, which is time-consuming and inefficient. However, if one can obtain an estimated model based on some prior knowledge, the control policy can be obtained based on suboptimal knowledge. Although there exists an error between the estimated model and the environment, the suboptimal guided policy will avoid unnecessary exploration; thus, the learning process can be significantly accelerated. Facing the problem of tracking policy optimization for multiple pursuers, this study proposed a new form of fuzzy actor–critic learning algorithm based on suboptimal knowledge (SK-FACL). In the SK-FACL, the information about the environment that can be obtained is abstracted as an estimated model, and the suboptimal guided policy is calculated based on the Apollonius circle. The guided policy is combined with the fuzzy actor–critic learning algorithm, improving the learning efficiency. Considering the ground game of two pursuers and one evader, the experimental results verified the advantages of the SK-FACL in reducing tracking error, adapting model error and adapting to sudden changes made by the evader compared with pure knowledge control and the pure fuzzy actor–critic learning algorithm.

A broadband generalized sidelobe canceler (Broadband-GSC) application for near-field beamforming is proposed. This approach is implemented in the wavelet domain. Broadband-GSC provides a set of complex, adapted apodization weights for each wavelet subband. The proposed method constrains interference and noise signal to improve the lateral resolution with only one single emission. Performance of the proposed beamforming is tested on simulated data obtained with Field II. Experiments have proved that the new beamforming can significantly increase the image quality compared with delay-and-sum (DAS) and synthetic aperture (SA). Imaging of scattering points show that Broadband-GSC improves the lateral resolution by 43.2% and 58.0% compared with SA and DAS, respectively. Meanwhile，Broadband-GSC reduces the peak sidelobe level by 11.6 dB and 26.4 dB compared with SA and DAS, respectively. Plane wave emission experiment indicates that Broadband-GSC can improve the lateral resolution by 44.2% compared with DAS. Furthermore, the new beamforming introduces the possibility for higher frame-rate and higher investigation depth with increased lateral resolution.

For adaptive ultrasound imaging, a reliable estimation of the covariance matrix has a decisive influence on the performance of beamformers. In this paper, we propose a new cross subaperture averaging generalized sidelobe canceler approach (GSC-CROSS) for medical ultrasound imaging, which uses the cross-covariance matrix instead of the traditional covariance matrix estimation. By using the more stable and accurate estimation of the covariance matrix, GSC-CROSS performs well in both lateral resolution and contrast. Experiments are conducted based on the simulated echo data of scattering points and a cyst target. Beamforming responses of scattering points show that GSC-CROSS can improve the lateral resolution by 76.9%, 68.8%, and 17.1% compared with delay-and-sum (DS), synthetic aperture (SA), and the traditional generalized sidelobe canceler (GSC), respectively. Also, imaging of the cyst target shows that compared with DS, SA, and GSC, the contrast increases by 101%, 32.6%, and 63.5%, respectively. Finally, the actual echo data collected from a medical ultrasonic imaging system is applied to reconstruct the image. Results show that the proposed method has a good performance on lateral resolution and contrast. Both the simulated and experimental data demonstrate the effectiveness of the proposed method.