UNDERWATER DRONES CONTROL TOWER

UNDERWATER DRONES CONTROL TOWERAdnan Tahirovic - Kemal Delic

ARCHITECTURE, DESIGN, ENGINEERING

Talk outline - why and how uwr is important ? + Underwater World Explained+ Technology Challenges and Future Developments+ Architecture, Design, Engineering Introduced+ Control Tower Architecture : Conceptual View+ Cloud Based Analytics : Design View+ Mapping the Sea Bottom - Navigation+ Intelligent Underwater Drone Design : Swarming+ Live Demo : Navigation+ Algorithm Explained+ Future Explored

Underwater World ExplainedHidden Face of Oceans

Oceans in numbersDepth of Ignorance - Level of Dependency

LIVING SPECIES

91% still unknown, 13% only catalogued

RESOURCES

90% of transportation , 20% of animal proteins

PHYSICAL WORLD

71% Earth surface water, 93% of heat stored

80% of volcanic activities under water

Eight challenges - unknowns + Thermal - temperature anomalies, impacting life on earth + Geological - cobalt, platinum etc found in proximity of volcanoes+ Genetic - new molecules for drugs learned from deep sea creatures + Ecological - destruction of habitats+ Climate - likely impact of human activities+ Hydrodynamic - Golf Stream 15% lower circulation + Chemical - seas and oceans may become toxic or sterile + Physical - rise of the sea level, 60% megapolis on the coast

Map of unknown worldsNobody knows for sure what

might be below seabed where,

how much it is worth

Strategic future exploration

Always preceded by map

creation

New moleculesDiscoveries of new drugs and

materials

Species living in extreme

conditions, no sunlight, huge

pressure and cold

Gulf stream changeClimate Change

Might be caused by

Changes in ocean

Streams ?

Last 3 centuries

Underwater World stratified

Into the abyss0 m100 m

500 m

1000 m

2000 m

10350 m

4000 m 8145 m deepest fish (snailfish) found

7000 m11000 m Mariana Trench(Deepest point in the Pacific Ocean)

6500 m

3000 m

6000 mABISMO ROV (Japan)

8400 m Puerto Rico trench(deepest point in the Atlantic Ocean)

Maximal dive for whales(Curver beaked whale)

ALVIN (USA)

Depths for divers

Depths for submarines

MIR (Russia) Nautile (France) Sentry HROV (USA)

Shinkai 6500 (Japan)

Jason ROV (USA)

Jiaolong (China)Mariana Trench reached by: Bathyscaph Trieste on 23.1.1960.Kaiko ROV on 24.3.1995. lost in 2003Nereus HROV on 31.5.2009. lost in 2012Deepsea challenger on 26.3.2012.

97% of ocean depths are less than 6000m

Area: 361,000,000 km2 (71% of Earth surface)

Technology Challenges and Future DevelopmentsLast week in Croatia ..

Breaking The Surface 2018

10 Years anniversary workshop

Game changing technologies that have the potential to significantly enhance capabilities of systems and

transform how we will use future systems

✓ Quantum computing, neuromorphic (brain inspired computing), …✓ Microelectronics, (components built of molecules), … ✓ Robotics, Soft reconfigurable robotics, ….✓ Nanomaterials, advanced materials,….✓ Genetics, ….✓ “Big data” , …✓ Alternative energy sources, ✓ Artificial intelligence, machine learning, …. ✓ Modeling and simulation, ....

Ec subucultron project http://www.subcultron.eu/Venice - Laguna

Health Monitoring

Architecture, Design, Engineering Introduced

Control Tower Architecture : Conceptual View

Control Tower Architecture : Conceptual View

CT: Cloud Based Analytics : Design View

Intelligent Underwater Drone Design : concept

Vision dl explained Picture

Recognition

Olfaction with DL NNOdor Recognition

Intelligent Underwater Drone Design

Deep dive follows ..

A possible mission: Coverage path planning (CPp)• Monitoring• Surveillance• Hazard detection• Planetary exploration• Rescue• Cleaning• De-mining• Fire extinguishing• Agricultural spraying

Tahirovic Adnan and Alessandro Astolfi. "A convergent solution to the multi-vehicle coverage problem." American Control Conference (ACC), 2013. IEEE, 2013.

CPp Algorithm Explained• Unconstrained environment• Fully-connected swarm

CPp Algorithm Explained

CPp Algorithm Explained Partially-connected swarm

CPp Algorithm Explained

Tahirovic Adnan, et al. "A receding horizon scheme for constrained multi-vehicle coverage problems." Systems, Man, and Cybernetics (SMC), 2016 IEEE International Conference on. IEEE, 2016.

CPp Algorithm Simulation

CPp Algorithm Features• Simple!!!• Cooperative!!! • Scalable!!!• Robust!!!• Adaptive???

All necessary features of swarm intelligence obtained via simple agent’s rules.

Rapidly Exploring Random Trees

Rapidly exploring random vines

Tahirovic Adnan, and Mina Ferizbegovic. "Rapidly-Exploring Random Vines (RRV) for Motion Planning in Configuration Spaces with Narrow Passages." 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018.

Rapidly exploring random vines

Rapidly exploring random vines

Rapidly exploring random vines

Rapidly exploring random vines

Key takeaways + Shift from ROV/AUV devices to the entire ecosystem+ The rise of multi-modal systems : flying, sailing, diving+ Big Data collections waiting for better analytics+ Security nearly non-existent+ Biology inspired sensory and communication systems

+ Ocean explorations will be even more important in the future and AI approaches and ML methods will play crucial role - from intelligent swarm edge devices to elaborate analytics in the cloud

Back up slides

• Monitoring of Bosnian lakes• Health monitoring of Venetian Lagoon• Monitoring of fishponds in Norway• Monitoring underwater cables

Future explored - what’s next?