The generalized super-twisting algorithm with adaptive gains.

In this article, a novel adaptive generalized super-twisting algorithm (GSTA) is proposed for a class of systems whose perturbations and uncertain control coefficients may depend on both time and state. The proposed approach uses dynamically adapted control gains, and it is proven that this ensures global finite-time convergence. A nonsmooth strict Lyapunov function is used to obtain the conditions for global finite-time stability. A simulation and experimental case study is performed using an articulated intervention autonomous underwater vehicle (AIAUV). It is also shown that the adaptive GSTA causes the tracking errors of the AIAUV to converge to zero in finite time. In the case study, we use the singularity-robust multiple task-priority method to create a continuous trajectory for the AIAUV to follow. The simulation and experimental results validate and verify that the proposed approach is well suited for controlling an AIAUV. We also perform a comparison with the super-twisting algorithm with adaptive gains and the original GSTA to evaluate whether adding adaptive gains to the GSTA actually improves the tracking capabilities by combining the theoretical advantages afforded by the GSTA with the practical advantages afforded by adaptive gains. Based on this comparison, the adaptive GSTA yields the best tracking results overall without increasing the energy consumption, and the simulations and experiments thus indicate that adding adaptive gains to the GSTA does indeed improve the consequent tracking results and capabilities.

Experimental Verification of a Coordinated Path-Following Strategy for Underactuated Marine Vehicles.

This work presents the results of an experimental verification of a coordinated path following strategy for underactuated marine vehicles. The coordinated path following strategy is presented, and is then experimentally verified using three autonomous underwater vehicles. The vehicles are required to coordinate their motion along spatially separated straight-line paths to obtain a desired formation. The vehicles are steered to the paths using an integral line-of-sight guidance approach that allows the vehicles to reject constant ocean currents. Simultaneously, the coordination is achieved by adjusting the velocity based on the along-path distance. First, simulation results are presented, which serve as benchmarks for the experimental results. Furthermore, the simulations are used to show the effect of changing different parameters. The simulation results are performed using high-fidelity hardware simulation models. The results obtained from experiments in the harbor of Porto are then presented and compared with the results of the simulation.

Path Following, Obstacle Detection and Obstacle Avoidance for Thrusted Underwater Snake Robots.

The use of unmanned underwater vehicles is steadily increasing for a variety of applications such as mapping, monitoring, inspection and intervention within several research fields and industries, e.g., oceanography, marine biology, military, and oil and gas. Particularly interesting types of unmanned underwater vehicles are bio-inspired robots such as underwater snake robots (USRs). Due to their flexible and slender body, these versatile robots are highly maneuverable and have better access capabilities than more conventional remotely operated vehicles (ROVs). Moreover, the long and slender body allows for energy-efficient transit over long distances similar to torpedo-shaped autonomous underwater vehicles (AUVs). In addition, USRs are capable of performing light intervention tasks, thereby providing intervention capabilities which exceed those of AUVs and inspection class ROVs. USRs may also propel themselves using energy-efficient motion patterns inspired by their biological counterparts. They can thereby increase the propulsion efficiency during transit and maneuvering, which is among the great challenges for autonomous underwater vehicles. In this paper, a control system for path following, and algorithms for obstacle detection and avoidance, are presented for a USR with thrusters attached at the tail module. The position of the obstacles is detected using a single camera in the head module of the USR and a developed computer vision algorithm. For the proposed control concept the robot joints are used for directional control while the thrusters are used for forward propulsion. The USR circumvents obstacles by following a circular path around them before converging back to the main straight line path when this is safe. Experimental results that validate the proposed methods are also presented.

Planar maneuvering control of underwater snake robots using virtual holonomic constraints.

This paper investigates the problem of planar maneuvering control for bio-inspired underwater snake robots that are exposed to unknown ocean currents. The control objective is to make a neutrally buoyant snake robot which is subject to hydrodynamic forces and ocean currents converge to a desired planar path and traverse the path with a desired velocity. The proposed feedback control strategy enforces virtual constraints which encode biologically inspired gaits on the snake robot configuration. The virtual constraints, parametrized by states of dynamic compensators, are used to regulate the orientation and forward speed of the snake robot. A two-state ocean current observer based on relative velocity sensors is proposed. It enables the robot to follow the path in the presence of unknown constant ocean currents. The efficacy of the proposed control algorithm for several biologically inspired gaits is verified both in simulations for different path geometries and in experiments.

Experimental investigation of efficient locomotion of underwater snake robots for lateral undulation and eel-like motion patterns.

Underwater snake robots offer many interesting capabilities for underwater operations. The long and slender structure of such robots provide superior capabilities for access through narrow openings and within confined areas. This is interesting for inspection and monitoring operations, for instance within the subsea oil and gas industry and within marine archeology. In addition, underwater snake robots can provide both inspection and intervention capabilities and are thus interesting candidates for the next generation inspection and intervention AUVs. Furthermore, bioinspired locomotion through oscillatory gaits, like lateral undulation and eel-like motion, is interesting from an energy efficiency point of view. Increasing the motion efficiency in terms of the achieved forward speed by improving the method of propulsion is a key issue for underwater robots. Moreover, energy efficiency is one of the main challenges for long-term autonomy of these systems. In this study, we will consider both these two aspects of efficiency. This paper considers the energy efficiency of swimming snake robots by presenting and experimentally investigating fundamental properties of the velocity and the power consumption of an underwater snake robot for both lateral undulation and eel-like motion patterns. In particular, we investigate the relationship between the parameters of the gait patterns, the forward velocity and the energy consumption for different motion patterns. The simulation and experimental results are seen to support the theoretical findings.

Path following control of planar snake robots using virtual holonomic constraints: theory and experiments.

This paper considers path following control of planar snake robots using virtual holonomic constraints. In order to present a model-based path following control design for the snake robot, we first derive the Euler-Lagrange equations of motion of the system. Subsequently, we define geometric relations among the generalized coordinates of the system, using the method of virtual holonomic constraints. These appropriately defined constraints shape the geometry of a constraint manifold for the system, which is a submanifold of the configuration space of the robot. Furthermore, we show that the constraint manifold can be made invariant by a suitable choice of feedback. In particular, we analytically design a smooth feedback control law to exponentially stabilize the constraint manifold. We show that enforcing the appropriately defined virtual holonomic constraints for the configuration variables implies that the robot converges to and follows a desired geometric path. Numerical simulations and experimental results are presented to validate the theoretical approach.

Adaptive feed-forward hysteresis compensation for piezoelectric actuators.

Piezoelectric actuators are often employed for high-resolution positioning tasks. Hysteresis and creep nonlinearities inherent in such actuators deteriorate positioning accuracy. An online adaptive nonlinear hysteresis compensation scheme for the case of symmetric hysteretic responses and certain periodic reference trajectories is presented. The method has low complexity and is well suited for real-time implementation. Experimental results are presented in order to verify the method, and it is seen that the error due to hysteresis is reduced by more than 90% compared to when assuming a linear response.