Robotized Underwater Interventions

Abstract

Working in underwater environments poses many challenges for robotic systems. One of them is the low bandwidth and high latency of underwater acoustic communications, which limits the possibility of interaction with submerged robots. One solution is to have a tether cable to enable high speed and low latency communications, but that requires a support vessel and increases costs. For that reason, autonomous underwater robots are a very interesting solution. Several research projects have demonstrated autonomy capabilities of Underwater Vehicle Manipulator Systems (UVMS) in performing basic manipulation tasks, and, moving a step further, this chapter will present a unifying architecture for the control of an UVMS, comprehensive of all the control objectives that an UVMS should take into account, their different priorities and the typical mission phases that an UVMS has to tackle. The proposed strategy is supported both by a complete simulated execution of a test-case mission and experimental results.

Appendix

1.1 Under-Actuated Vehicles

This chapter has presented UVMS control algorithms under the assumption of fully actuated vehicle. However, in many cases the vehicles are passively stable in some d.o.f. (typically roll and/or pitch). The algorithm (16) can easily cope with this situation, by using a slightly different initialization. As an example, in lieu of (15) consider the following initial values for a vehicle with roll and pitch not actuated:

$$\begin{aligned} \begin{aligned} \varvec{\rho }_{0}&= \begin{bmatrix} \mathbf 0 _{l \times 1} \\ \mathbf 0 _{3 \times 1} \\ \omega _x \\ \omega _y \\ 0\end{bmatrix}&\mathbf Q _{0}&= \begin{bmatrix} \mathbf I _{l \times l}&\mathbf 0 _{l \times 3}&\mathbf 0 _{l \times 1}&\mathbf 0 _{l \times 1}&\mathbf 0 _{l \times 1} \\ \mathbf 0 _{3 \times l}&\mathbf I _{3 \times 3}&\mathbf 0 _{3 \times 1}&\mathbf 0 _{3 \times 1}&\mathbf 0 _{3 \times 1} \\ \mathbf 0 _{1 \times l}&\mathbf 0 _{1 \times 3}&0&0&0 \\ \mathbf 0 _{1 \times l}&\mathbf 0 _{1 \times 3}&0&0&0 \\ \mathbf 0 _{1 \times l}&\mathbf 0 _{1 \times 3}&0&0&1\end{bmatrix}. \end{aligned} \end{aligned}$$

(20)

The idea is that the solution $\varvec{\rho }$ is initialized with the actual angular velocities of the vehicle, as measured by onboard sensors. At the same time, to force the task hierarchy resolution to avoid changing these values, the corresponding diagonal values of the matrix $\mathbf Q$ are set to zero. This effectively inhibits the algorithm from changing the initial values. Note that all the tasks will properly take into account the nonactuated d.o.f. velocities due to the term $\left( \dot{\bar{\varvec{x}}}_k - \mathbf J _k \varvec{\rho }_{k-1} \right)$.