This paper presents an integrated methodology and experimental validation of an autonomous framework for unmanned underwater vehicles (UUVs) merely equipped with a conventional monocular camera and a pressure sensor to accomplish high-performance autonomy. Optimal pose of the UUV is solved iteratively by Levenburg-Marquardt optimization for the Perspective-n-Point (PnP) problem. To guarantee a consistent localization system, a properly-tuned EKF with extra outlier removal approaches including applying Chi-square tests of innovations adequately removes measurement noises, mean-while provides unknown navigation state estimations. A classic adaptive controller is developed to enable autonomous mobility. Real-time experiments are designed to demonstrate underwater autonomous performance with a miniature commercial UUV, BlueROV2 Heavy.

Driven by the SARS-CoV-2 pandemic, demand for oropharyngeal swab sampling (OP-swabs) is surging. However, medical staff can easily become infected by the virus during the sampling process. In an effort to combat this, we developed a novel, intrinsically safe rigid- flexible coupling (RFC) manipulator to improve the safety and reliability of OP-swab sampling to test for COVID-19, which is presented herein. Suitable sampling areas and the necessary contact force for OP-swab sampling tasks are carefully investigated, and three typical sampling paths outlined that could be performed by a robotic system. This is followed by a detailed description of an intrinsically safe bionic micro-pneumatic actuator (MPA) that was designed and fabricated as the main component of the RFC manipulator. The developed RFC manipulator’s kinematic modeling, motion planning, and force control capacities were designed for OP-swab sampling scenarios. The system was then validated using both an oral cavity phantom and human volunteers, with comparative experiments on the swab quality of the OP-swab sampling approach conducted in both robotic and manual modes. The results indicate that fully-automated sampling based on this design would be feasible.

With the gradual maturity of the software and hardware of quadruped robots, the application scenarios of quadruped robots are increasing, such as security, rescue, exploration and other tasks. Quadruped robots are flexible and adaptive to challenging or complex environment. This study presents a large-scale quadruped robot, Pegasus II, which is a new version upgraded from the previous quadruped robot, Pegasus [1]. System design of Pegasus II is introduced, including mechanical and electronic design. Locomotion control for a special scene, L-shaped narrow corner, in which a large-scale quadruped robot is not able to traverse in a common quadrupedal mode, is demonstrated. The long body length of a large-scale quadruped robot, such as Pegasus II, incurs difficulty in traversing freely in such a narrow passage. Motivated by this issue, this study proposes an experimental implementation to realize the transition from quadrupedal mode to bipedal mode. The control framework is presented, which mainly includes trajectory optimization, whole-body control, compliance control, and joint torque estimator. Simulations and experiments are conducted to validate the performance, including gait transition, compliance control.

This article proposes a virtual leader-based coordinated controller for the nonlinear multiple autonomous underwater vehicles (multi-AUVs) with the system uncertainties. To achieve the coordinated formation, a virtual AUV is set as the leader, while the desired command is designed using the relative position between each AUV and the virtual leader. The controller is designed based on the back-stepping scheme, and the online data-based learning scheme is used for uncertainty approximation. The highlight is that compared with previous learning methods which mostly focus on stability, the learning performance index is constructed using the collected online data in this article. The index is further used in the composite update law of the neural weights. The closed-loop system stability is analyzed via the Lyapunov approach. The simulation test on the five AUVs under fixed formation shows that the proposed method can achieve higher tracking performance with improved approximation accuracy.

This paper investigates the cooperative target enclosing of multiple unicycle-type mobile robots subject to input disturbances. The objective is to make all robots orbit around a given stationary target, and maintain evenly spaced along a common circle. The network of the multirobot systems is set in a cyclic pursuit manner. A dynamic control law is developed for the cooperative target enclosing of the multirobot systems, while tackling the heterogeneous input disturbances generated by linear exogenous systems. The proposed control law requires each robot to use the relative displacement measurements with respect to the target and its neighbors. It is shown that global asymptotic stability of the closed-loop multirobot systems can be guaranteed in the presence of a large class of input disturbance signals. Finally, simulation results illustrate the effectiveness of our approach.

Energy-efficient locomotion is of primary importance for legged robot to extend operation time in practical applications. This paper presents an approach to achieve energy-efficient locomotion for a quadrupedal robot walking over challenging terrains. Firstly, we optimize the nominal stance parameters based on the analysis of leg torque distribution. Secondly, we proposed the foothold planner and the center of gravity (COG) trajectory planner working together to guide the robot to place its standing legs in an energy-saving stance posture. We have validated the effectiveness of our method on a real quadrupedal robot in experiments including autonomously walking on plain ground and climbing stairs.

This paper investigates the cooperative moving-target enclosing control problem of networked unicycle-type nonholonomic vehicles with constant linear velocities. The information of the target is only known to some of the vehicles, and the topology of the vehicle network is described by a directed graph. A dynamic control law is proposed to steer the vehicles, such that they can get close to orbiting around the target while the target is moving with a time-vary velocity. Besides, the constraint of bounded angular velocity for the vehicles can always be satisfied. The proposed control law is distributed in the sense that each vehicle only uses its own information and the information of its neighbors in the network. Finally, simulation results of an example validate the effectiveness of the proposed control law.

This paper investigates dynamic and compliant control based on joint output torque estimation for electrically actuated quadruped robots with large-reduction-ratio harmonic gear. Compared with position control, force control exhibits better performance of dynamics and compliance for the robot's interactions with complex environments. However, force control without direct feedbacks from torque sensors may come with poor tracking performance of joint compliance when the robot equipped with gears of high reduction. To solve this problem, we propose a new method to estimate joint torque from motor current and rotation velocity detected on each joint, using a more precise friction model of the harmonic gear. We also introduce a pre-stance phase to the whole cycle of leg alternating swing/stance based on hybrid force and position control to dynamically absorb feet impacts on the ground. Our controller performance is validated by standing experiment and walking experiment.