UNDERWATER DRONES CONTROL TOWER UNDERWATER DRONES CONTROL TOWER Adnan 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 Explained

Hidden Face of Oceans Oceans in numbers

Depth 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 worlds

Nobody knows for sure what might be below seabed where, how much it is worth

Strategic future exploration

Always preceded by map creation New molecules

Discoveries of new drugs and materials

Species living in extreme conditions, no sunlight, huge pressure and cold

Gulf stream change

Climate Change

Might be caused by

Changes in ocean

Streams ?

Last 3 centuries Underwater World stratified

Into the abyss

0 m 4000 m ALVIN (USA) 8145 m deepest fish (snailfish) found 100 m 8400 m Puerto Rico trench Depths for divers Sentry HROV (USA) (deepest point in the Atlantic Ocean) 500 m MIR (Russia) Nautile (France)

1000 m Depths for submarines 6000 m 97% of ocean depths are less than 6000m ABISMO ROV (Japan) 2000 m Shinkai 6500 (Japan) 6500 m 10350 m Jason ROV (USA)

11000 m Mariana Trench 3000 m Maximal dive for whales 7000 m Jiaolong (China) (Deepest point in the Pacific Ocean) (Curver beaked whale) Mariana Trench reached by: Bathyscaph Trieste on 23.1.1960. Kaiko ROV on 24.3.1995. lost in 2003 2 Nereus HROV on 31.5.2009. lost in 2012 Area: 361,000,000 km (71% of Earth surface) Deepsea challenger on 26.3.2012. Technology Challenges and Future Developments

Last 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 NN

Odor 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 Future explored - what’s next? • Monitoring of Bosnian lakes • Health monitoring of Venetian Lagoon • Monitoring of fishponds in Norway • Monitoring underwater cables