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Pedro Batista

WP2 Single & multiple vehicle control

2nd Field Training Workshop in Underwater Robotics Intervention

Marine Robot and Dexterous Manipulatin for Enabling Multipurpose Intevention Missions

Instituto Superior Técnico Dynamical Systems and Ocean Robotics Laboratory / ISR / LARSyS

Underactuated AUV moving in a scenario where there is a fixed transponder (the target)

WP2 Single & Multiple Vehicles Control

Homing - problem statement

Design the control law such that the vehicle is driven toward a well defined neighborhood of the target


Homing – progress report (1)

Step 1 Theoretical framework

full under-actuated nonlinear dynamics of an AUV in 3-D.

set within a sensor-based framework considering an USBL acoustic positioning system

reported in a journal paper (Int. Journ. of Robust and Nonlinear Control)



Step 2 Adaptation to

Nessie

Control law adapted for Nessie’s autopilot with linear and angular velocity commands

Special care was taken tuning the gains and adapting the control law, in simulation, to avoid instability or undesired behaviors (oscillations,

control saturations, bang-bang situations, etc.)

Algorithms were simplified to 2-D (independent depth controller is provided by Nessie)



Step 3 Preliminary

Experimental validation

Experiments with Nessie during the “TRIDENT Fall School: 1st Field Training Workshop in Underwater Robotics Intervention”

Transponder position simulated in-the-loop

Integration in ROS of the control laws that were developed and tested in Matlab


Homing – experimental results (1)

Nessie Homing @ Roses, 2011/10/19, 11:03:32

Run 1

Run 2

Run 3



Step 4 Experimental

validation

Repeat trials from Roses to check repeatability

Adopt in-house built inverted USBL

Development of Body-fixed filter for the transponder position based on USBL and DVL

Successful evaluation of the control performance



Virtual transponder

Nessie Run 1 Homing @ Loch Earn, 2012/04/23, 18:34:04

Steady heading


USBL integration on Nessie

In Lab

Transponder

USBL mounted on Nessie: - Reconfigured reception array to fit with Nessie’s DVL and thrusters

Fully integrated on Nessie: - Mechanically and buoyancy - Electrically - Network - Software (ROS)



Inverted USBL

USBL Raw fixes with outlier detector

Filtered transponder position in Body frame

Nessie Run 3 Homing @ Loch Earn, 2012/04/26,12:30:26


Homing – future work

Dissemination

Transition to the simulator and the G-500 should be straightforward as it has been previously

implemented in ROS with Nessie.

Submit a joint journal paper with HWU with the experimental results.

Re-run algorithms, in a larger mission scenario, from multiple initial and interesting conditions with the transponder installed on

Delfim

Docking between two transponders

Alternatively One transponder and direction vector via acoustic modem.

Scenario

Problem: Steer the vehicle toward the final position, along the path defined by the final desired direction.


Docking – problem statement


Docking – solution overview

Docking

When the vehicle is still far away, under-actuated dynamics are considered and

the vehicle is driven faster

When the vehicle is close to the base, fully actuated dynamics and model

uncertainty are considered

Convergence is always guaranteed

Two-step solution


Docking – progress report (1)

Step 1 Theoretical framework

full under-actuated nonlinear dynamics of an AUV in 3-D.

set within a sensor-based framework considering an USBL acoustic positioning system

progress has already been presented at the 2012 ACC theoretical framework to be published in a journal paper


Docking – simulation results

The vehicle approaches the base with the correct attitude for docking operations.

Initial stage at constant surge velocity

All velocities decrease as vehicle approaches the docking position.



Step 2 Adaptation to

Nessie

Control law adapted for Nessie’s autopilot with linear and angular velocity commands

Special care was taken tuning the gains and adapting the control law, in simulation, to avoid instability or undesired behaviors (oscillations,

control saturations, bang-bang situations, etc.)

Algorithms were simplified to 2-D (independent depth controller is provided by Nessie)



Step 3 Experimental

validation

Experiments with Nessie (joint work with HWU)

Transponder position simulated in-the-loop

Inverted USBL + body-fixed filter

Direction of arrival is provided virtually in both cases

Integration in ROS of the control laws that were developed and tested in Matlab


Docking – experimental results (1)

Virtual transponder and direction of arrival

Nessie Run 4 Docking @ Loch Earn, 2012/04/24, 12:22:59

Final Docking direction: South (Yaw = 180 deg)

Docking controller

PID controller


Docking – experimental results (2)

Inverted USBL, virtual direction of arrival

USBL Raw fixes with outlier detector

Filtered transponder position in Body frame Nessie Run 4 Docking @ Loch Earn, 2012/04/26,

15:14:08

Final Docking direction: South (Yaw = 180 deg)


Docking – future work

Dissemination

Again, integration in the simulator and G-500 should be straightforward from ROS.

Submit a joint journal paper with Heriot-Watt with the docking experimental results.

Re-run algorithms, in a larger mission scenario, from multiple initial and interesting conditions with the transponder installed on

Delfim. The direction of arrival will be provided by Delfim.


Bottom–Following – problem statement

Design a controller to achieve smooth tracking of the bottom profile, at a fixed distance, with feed-forward preview control to help limit the actuation bandwidth.

Problem Statement

General Idea

Path to be followed generated from sensor readings (depth sensor,

look-ahead sensor)

Path-following problem converted to regulation problem by careful definition of the error space

Design appropriate controller to drive tracking error to the origin


Bottom–Following – summary

Collect sensor data to draw the bottom profile, add elevation offset to track it from a safe distance.

Sensor readings


Bottom-Following – Path generation (1)

Bottom profile is approximated by straight line segments, which compose the path to be followed.

Path Generation


Bottom-Following – Path generation (2)

Controller Design Process

Inclusion of the preview information in the error dynamics through state augmentation

Linearization and discretization of the error dynamics around several operating points

H2 controller design with gain scheduling to achieve good performance in all operating regions

D-methodology (integrators moved to the plant input) to achieve auto-trimming


Bottom-Following – controller design (1)

Integration with the Nessie AUV, in cooperation with the group from

Heriot-Watt University

First Experimental Trials

A few adaptations were made in the controller that was implemented on Nessie

The vehicle was controlled only in surge and heave, to reduce stress on the vertical thrusters (pitch control was deprecated)

Preview was not included due to the resulting loss in directionality of the error space and the low velocities practiced in the trials

Five operating regions, depending on the slope of the path


Bottom-Following – experimental setup

Generating altitude measurements from a predefined virtual path

First Trial


Bottom-Following – Trial 1: virtual path

Going away from the shore, towards the middle of the loch

Second Trial


Bottom-Following – Trial 2: real terrain

Coming back towards the shore, from the middle of the loch

Third Trial


Bottom-Following – Trial 3: real terrain

Scenario

Theoretical frameworks and solutions have been developed

On a first approach, control for single vehicles was addressed

Theoretical solutions will continue to be adapted to practice in the near future…

Very encouraging preliminary experimental results on leader-following with acoustics and with inverted USBL


Leader-Following – Preliminary results (1)


Leader-Following – Preliminary results (2)

Nessie dead-reckoning and receiving ASC position.

Ad-Hoc (based on homing controller) leader-following with inverted USBL tracking the transponder on a moving boat (ASC) and without acoustic communications.


In this workshop…

Experimental validation of all algorithms with Nessie and Delfim

Full USBL integration

Body-fixed navigation filter

Homing

Docking

Bottom-following

Leader following

Pedro Batista

WP1 Navigation and Mapping

2nd Field Training Workshop in Underwater Robotics Intervention

Marine Robot and Dexterous Manipulatin for Enabling Multipurpose Intevention Missions

Instituto Superior Técnico Dynamical Systems and Ocean Robotics Laboratory / ISR / LARSyS

Navigation For teams of vehicles

Single vehicle

Linear motion GAS

USBL, LBL

Reduced measurements

Range-based Bearings only

Range-only

Single and multiple

Bearings-only

Source localization and navigation

Relative position

USBL with biased DVL USBL with accelerometers

Absolute position

LBL with biased DVL LBL with accelerometers

Angular motion GES

Vector-based

Cooperative Magnetometer

unavailable

Angular motion GAS

USBL + Modem RG bias included

Linear motion GAS

Single-range USBL

Over 10 Journal articles: JIRS, TRO, EJC, IJC, AUTOMATICA (3), SCL (3), CEP, etc. Over 20 Conference publications: CDC, ACC, IFAC WC, ICRA, etc.

WP1 Navigation & Mapping

T1.1 Cooperative Navigation

Linear motion GAS

Relative position

USBL with biased DVL USBL with accelerometers

Absolute position

LBL with biased DVL LBL with accelerometers

Range-based

Single ranges - rich trajectories Multiple ranges

Bearings-only

USBL based Observability analysis

USBL Best with DVL!

LBL is complex to operate!

Rich trajectories required mostly. Possible easier

extension - depth measurements.

Also needs rich trajectories.

- LTI solution - Simple gain - GAS - Great performance

Sensors needed: - Magnetometer + IMU / AHRS - DVL - USBL



Body-fixed

For control purposes

Equivalent LTI solution

Simple gain

GAS

Great performance

Computationally inexpensive

Needs the ASC velocity

Earth-fixed

For geo-referencing purposes

Equivalent LTI solution

Simple gain

GAS

Great performance

Computationally inexpensive

Needs the ASC position

Practical linear motion estimation with USBL



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