Overview of a new Ocean Glider Navigation System: OceanGNS

Ocean gliders are increasingly a platform of choice to close the gap between traditional ship-based observations and remote sensing from floats (e.g., Argo) and satellites. However, gliders move slowly and are strongly influenced by currents, reducing useful battery life, challenging mission planning, and increasing pilot workload. We describe a new cloud-based interactive tool to plan glider navigation called OceanGNS© (Ocean Glider Navigation System). OceanGNS integrates current forecasts and historical data to enable glider route–planning at varying scales. OceanGNS utilizes optimal route–planning by minimizing low current velocity constraints by applying a Dijkstra algorithm. The complexity of the resultant path is reduced using a Ramer-Douglas Pueckler model. Users can choose the weighting for historical and forecast data as well as bathymetry and time constraints. Bathymetry is considered using a cost function approach when shallow water is not desirable to find an optimal path that also lies in deeper water. Initial field tests with OceanGNS in the Gulf of St. Lawrence and the Labrador Sea show promising results, improving the glider speed to the destination 10–30%. We use these early tests to demonstrate the utility of OceanGNS to extend glider endurance. This paper provides an overview of the tool, the results from field trials, and a future outlook.

Underactuated USV Path Following Mechanism Based on the Cascade Method

The path following control under disturbance was studied for an underactuated unmanned surface vehicle (USV) subject to the rudder angle and velocity constraints. For this reason, a variable look-ahead integral line-of-sight (LOS) guidance law was designed on the basis of the disturbance estimation and compensation, and a cascade path following control system was created following the heading control law based on the model prediction. Firstly, the guidance law was designed using the USV three-degree-of-freedom (DOF) motion model and the LOS method, while the tracking error state was introduced to design the real-time estimation of disturbance observer and compensate for the influence of ocean current. Moreover, the stability of the system was analyzed. Secondly, sufficient attention was paid to the rudder angle and velocity constraints and the influence of system delay and other factors in the process of path following when the heading control law was designed with the USV motion response model and the model predictive control (MPC). The moving horizon optimization strategy was adopted to achieve better dynamic performance, effectively overcome the influence of model and environmental uncertainties, and further prove the stability of the control law. Thirdly, a simulation experiment was carried out to verify the effectiveness and advancement of the proposed algorithm. Fourthly, the “Sturgeon 03” USV was used in the lake test of the proposed control algorithm to prove its feasibility in the engineering practices.

Joint Motion Planning of Industrial Robot Based on Modified Cubic Hermite Interpolation with Velocity Constraint

As for industrial robots’ point-to-point joint motion planning with constrained velocity, cubic polynomial planning has the problem of discontinuous acceleration; quintic polynomial planning requires acceleration to be specified in advance, which will likely cause velocity to fluctuate largely because appropriate acceleration assigned in advance is hardly acquired. Aiming at these problems, a modified cubic Hermite interpolation for joint motion planning was proposed. In the proposed methodology, knots of cubic Hermite interpolation need to be reconfigured according to the initial knots. The formulas for how to build new knots were put forward after derivation. Using the newly-built knots instead of initial knots for cubic Hermite interpolation, joint motion planning was carried out. The purpose was that the joint planning not only satisfied the displacement and velocity constraints at the initial knots but also guaranteed C2 continuity and less velocity fluctuation. A study case was given to verify the rationality and effectiveness of the methodology. Compared with the other two planning methods, it proved that the raised problems can be solved effectively via the proposed methodology, which is beneficial to the working performance and service life of industrial robots.

Plasticity of the gastrocnemius elastic system in response to decreased work and power demand during growth

Elastic energy storage and release can enhance performance that would otherwise be limited by the force-velocity constraints of muscle. While functional influence of a biological spring depends on tuning between components of an elastic system (the muscle, spring, driven mass, and lever system), we do not know whether elastic systems systematically adapt to functional demand. To test whether altering work and power generation during maturation alters the morphology of an elastic system, we prevented growing guinea fowl (Numida Meleagris) from jumping. At maturity, we compared the jump performance of our treatment group to that of controls and measured the morphology of the gastrocnemius elastic system. We found that restricted birds jumped with lower jump power and work, yet there were no significant between-group differences in the components of the elastic system. Further, subject-specific models revealed no difference in energy storage capacity between groups, though energy storage was most sensitive to variations in muscle properties (most significantly operating length and least dependent on tendon stiffness). We conclude that the gastrocnemius elastic system in the guinea fowl displays little to no plastic response to decreased demand during growth and hypothesize that neural plasticity may explain performance variation.

Finite-time Tracking Control with Velocity Constraints for the Stochastic Rehabilitative Training Walker System Considering Different Rehabilitee Masses

This study discusses a finite-time tracking controller for a rehabilitative training walker that imposes velocity constraints. The walker was described using a stochastic model through which the rehabilitee mass can randomly change, and a velocity constraint method was proposed to control the velocity input to every omniwheel based on a model predictive algorithm. This approach is novel in that the velocity constraint information obtained from the kinematics model was used to design the tracking controller based on the stochastic dynamic model, thus successfully constraining the actual velocity of walker as per the stochastic system. The nonlinear tracking controller was built for the stochastic rehabilitative walker to make the system’s finite time stable. Also, simulation and experiment were performed, and results confirmed that the proposed tracking control method with velocity constraints is very effective, so it may enable various rehabilitees to train safely.

Quasi-velocities definition in Lagrangian multibody dynamics

Based on Lagrangian mechanics, use of velocity constraints as a special set of quasi-velocities helps derive explicit equations of motion. The equations are applicable to holonomic and nonholonomic constrained multibody systems. It is proved that in proposed quasi-spaces, the Lagrange multipliers are eliminated from equations of motion; however, it is possible to compute these multipliers once the equations of motion have been solved. The novelty of this research is employing block matrix inversion to find the analytical relations between the parameters of quasi-velocities and equations of motion. In other words, this research identifies arbitrary submatrices and their effects on equations of motion. Also, the present study aimed to provide appropriate criteria to select arbitrary parameters to avoid singularity, reduce constraints violations, and improve computational efficiency. In order to illustrate the advantage of this approach, the simulation results of a 3-link snake-like robot with nonholonomic constraints and a four-bar mechanism with holonomic constraints are presented. The effectiveness of the proposed approach is demonstrated by comparing the constraints violation at the position and velocity levels, conservation of the total energy, and computational efficiency with those obtained via the traditional methods.