Geometry Optimization of Heaving Axisymmetric Point Absorbers under Parametrical Constraints in Irregular Waves

The objective of this work is to identify the maximum absorbed power and optimal buoy geometry of a heaving axisymmetric point absorber for a given cost in different sea states. The cost of the wave energy converter is estimated as proportional to the displaced volume of the buoy, and the buoy geometry is described by the radius-to-draft ratio. A conservative wave-height-dependent motion constraint is introduced to prevent the buoy from jumping out of the free surface of waves. The constrained optimization problem is solved by a two-nested-loops method, within which a core fundamental optimization process employs the MATLAB function fmincon. Results show that the pretension of the mooring system should be as low as possible. Except for very small energy periods, the stiffness of both the power take-off and mooring system should also be as low as possible. A buoy with a small radius-to-draft ratio can absorb more power, but at the price of working in more energetic seas and oscillating at larger amplitudes. In addition, the method to choose the optimal buoy geometry at different sea states is provided.

Adaptive Coordinated Motion Constraint Control for Cooperative Multi-manipulator Systems

A cooperative multi-manipulator system is a nonlinear, time-varying, strong coupling system with multiple inputs and outputs. Because of external disturbance, load change and other factors, a cooperative multi-manipulator system needs to address the problems of uncertain environment interaction, feasible control methods and coordinated planning. In this study, the coordinated motion of a multi-manipulator is divided into two types: coupling and superposition motions. An adaptive coordinated motion constraint scheme is proposed for the two different motion forms. The coupled and superposition motions were investigated by coordinating a carrying task and a circle drawing task, respectively, and the effectiveness of the adaptive coordinated motion scheme was verified. Based on the adaptive kinematics constraint algorithm of the multi-manipulator, co-simulation analysis of the multi-manipulator coordinated motion is conducted. Simulation results show that the multi-manipulator preserves the coordination relationship at all points of the trajectory planning path and has a good motion effect. Finally, an experimental platform for a cooperative multi-manipulator system was built to conduct experimental research on the coordinated motion of the multi-manipulator. Experimental results show that the proposed adaptive motion constraint control scheme for cooperative multi-manipulator systems has a good coordination effect, strong adaptivity and high-control precision.

A Robotic System with Robust Remote Center Motion Constraint for Endometrial Regeneration Surgery

Surgical robots have been widely used in various surgeries in order to improve and facilitate the surgeries. However, there is no robot intended for endometrial regeneration surgery which is a new therapy to restore women’s fertility by using stem cells. Endometrial regeneration surgery requires processing endometrium and transplanting stem cells with the minimal trauma to uterus. In this paper, we introduce a surgical robotic system which consists of a dexterous hysteroscope, a supporting arm and additional novel instruments to facilitate the operations and decrease trauma to the uterus. To protect the cervix of the uterus, remote center of motion (RCM) constraint is required. First, the supporting arm and the hysteroscope are controlled separately in kinematics in order to ensure that the RCM constraint and the hysteroscope’s shape and posture are predictable. Then, a task decoupled method is used to improve the robustness of the RCM constraint. The experiments show that our method is more robust and achieves higher accuracy of RCM. Besides, the master slave control of robot with RCM constraint is also verified.

Incorporating model predictive control with fuzzy approximation for robot manipulation under remote center of motion constraint

Remote center of motion (RCM) constraint has attracted many research interests as one of the key challenges for robot-assisted minimally invasive surgery (RAMIS). Although it has been addressed by many studies, few of them treated the motion constraint with an independent workspace solution, which means they rely on the kinematics of the robot manipulator. This makes it difficult to replicate the solutions on other manipulators, which limits their population. In this paper, we propose a novel control framework by incorporating model predictive control (MPC) with the fuzzy approximation to improve the accuracy under the motion constraint. The fuzzy approximation is introduced to manage the kinematic uncertainties existing in the MPC control. Finally, simulations were performed and analyzed to validate the proposed algorithm. By comparison, the results prove that the proposed algorithm achieved success and satisfying performance in the presence of external disturbances.

High-Speed Train Tunnel Navigation Method Based on Integrated MIMU/ODO/MC Navigation

When a high-speed train is running in a tunnel, the global navigation satellite system (GNSS) signal is completely lost. Relying only on the inertial navigation system (INS) composed of Micro-electromechanical Systems (MEMS) devices leads to large navigation errors. To solve this problem, an integrated micro inertial measurement unit (MIMU), odometer (ODO), and motion constraint (MC) tunnel navigation method is proposed. This method first establishes a motion constraint model based on the installation angles of MIMU; secondly, the effect of turning on the motion constraint model and the odometer is analyzed and the use condition of the motion constraints is obtained; the installation angles of MIMU are then estimated when GNSS signal is good and the use condition of the motion constraints is met; finally, the forward speed measured by the odometer and the motion constraints are applied to suppress the error of the INS and improve the navigation accuracy in the tunnel. Based on this method, high-speed train navigation tests were carried out both in areal tunnel environment and in a case study with an artificially disconnected GNSS signal. The experimental results showed that the navigation accuracy of the train in the tunnel was significantly improved. Seamless navigation was achieved inside and outside the tunnel, which verified the effectiveness of the method.

Precise Shearer Positioning Technology Using Shearer Motion Constraint and Magnetometer Aided SINS

The key technology to realize intelligent unmanned coal mining is the strapdown inertial navigation system (SINS); however, the gradual increase of cumulative error during the working process needs to be solved. On the basis of an SINS/odometer (OD)-integrated navigation system, this paper adds magnetometer (MAG)-aided positioning and proposes an SINS/OD/MAG-integrated shearer navigation system. The velocity observation equation is obtained from the speed constraints during shearer movement, and the yaw angle observation equation is obtained from the magnetometer output. The position information of the SINS output is calibrated using these two observations. In order to improve the fault tolerance of the integrated navigation system, an adaptive federated Kalman filter is established to complete the data fusion of the SINS. Experimental results show that the positioning accuracy of the SINS/OD/MAG-integrated navigation system is 75.64% and 74.01% higher in the east and north directions, respectively, than the SINS/OD-integrated navigation system.