swarming autonomous systems for offshore oil spill...

SWARMING AUTONOMOUS SYSTEMS FOR OFFSHORE OIL SPILL RECOVERY AND CLEAN-UP

Richard Mensah [2129347M]

MSc Mechatronics Engineering

Supervisor : Mr Garrie Mushet

University of Glasgow, charity number SC004401

Oil spillage into the marine environment either intentionally or unintentionally has

been known to cause serious damage to biological life and the marine

ecosystem. This MSc dissertation was to develop and test a control system for

an autonomous swarming system optimized for use in an emergency offshore oil

spill clean-up.

The objectives for the control system were:

Autonomous and decentralised coverage of spill site

Internal collision prevention within swarm

Obstacle avoidance

𝑢 = 𝑣 ∅

2−

1

4𝑚𝐶𝑑𝜌 𝑢2𝐴 +

𝑐𝑜𝑠∅

2𝑚𝐶𝑇𝜌𝑛

2𝐷4

𝑣 =− 𝑢 ∅

2−

1

4𝑚𝐶𝑑𝜌 𝑣2𝐴 +

𝑠𝑖𝑛∅

2𝑚𝐶𝑇𝜌𝑛

2𝐷4

∅ = −1

6𝐼𝑧𝜌𝐶𝑝𝑡 𝜖1𝐿 + 𝑦 𝜖2 − 𝜖1 ∅2 +

1

𝐼𝑧

1

2𝜌𝐶𝐿𝐴𝑟𝑉

2 (𝑂𝐶𝑃 + 𝑂𝐶𝐺)sin𝜋

2

𝛿𝑎𝑡𝑡𝑎𝑐𝑘𝛿𝑠𝑡𝑎𝑙𝑙

The control system was built on the Artificial Potential Field and an

extended version of the Multi-resolution Navigation Of Mobile

Robots Algorithm. Results from simulation are displayed in Figures

3 - 6.

Fig1 Concept Robot

Fig3 Path of Single Robot moving around an obstacle with goal at coordinate (9,9)

Fig4 Path of a single robot cleaning an 80mX80m oil field

Fig5 Paths of two robots cleaning an 80mX80m oil field

Fig6 Paths of four robots cleaning an 80mX80m oil field with obstacles

Mathematical model of robot

Conclusion

• There is an equal task sharing among the swarm independent of

the initial positions of the robots

• Task does not need to be explicitly assigned to the robots as the

robots are able to plan themselves online.

• The swarm is able to access the entire field without any prior

knowledge of the field. The only information needed is an origin

Important Features of the control system

The control system meets the objectives defined for the project. It

can be adapted for swarming autonomous systems in complete

coverage applications such as oil spill cleaning, large area lawn

mowing and large space floor cleaning

𝜕𝑈𝑅 = −𝐾𝑎𝑡𝑡 𝑥 − 𝑥0 + 𝑦 − 𝑦0 𝑖 + 𝐾𝑟𝑒𝑝1

𝑥−

1

𝑥0𝑏

1

𝜌𝑥

2

+1

𝑦−

1

𝑦0𝑏

1

𝜌𝑦

2

𝑖

𝜕𝑈𝑎𝑡𝑡 = −𝐾𝑎𝑡𝑡 𝑥 − 𝑥0 + 𝑦 − 𝑦0 𝑖

𝜕𝑈𝑅𝑒𝑝 = 𝐾𝑟𝑒𝑝1

𝑥−

1

𝑥0𝑏

1

𝜌𝑥

2

+1

𝑦−

1

𝑦0𝑏

1

𝜌𝑦

2

𝑖 𝑖𝑓 𝜌 ≤ 𝜌0

)𝑇ℎ𝑟𝑢𝑠𝑡𝑒𝑟 𝐹𝑜𝑟𝑐𝑒( 𝐹 ) = 𝐹𝑔 ∗ 𝑎𝑏𝑠(𝜕𝑈𝑎𝑡𝑡

∅𝑅 = 𝑡𝑎𝑛−1𝑖𝑚𝑎𝑔 𝜕𝑈𝑅𝑟𝑒𝑎𝑙 𝜕𝑈𝑅

𝑀𝑜𝑚𝑒𝑛𝑡 (𝑀) =

𝑀𝑔 ∗ ∅𝑅 − ∅ 𝑖𝑓 ∅𝑅 > ∅ && ∅𝑅 − ∅ ≤ 180

−𝑀𝑔 ∗ 360 − ∅𝑅 − ∅ 𝑖𝑓 ∅𝑅 > ∅ && ∅𝑅 − ∅ > 180

−𝑀𝑔 ∗ 360 − ∅𝑅 − ∅ 𝑖𝑓 ∅𝑅 < ∅ && ∅𝑅 − ∅ > 180

𝑀𝑔 ∗ ∅𝑅 − ∅ 𝑖𝑓 ∅𝑅 < ∅ && ∅𝑅 − ∅ ≤ 180

Rudder

The Artificial Potential Field