UNDERWATER DRONES CONTROL TOWER UNDERWATER DRONES CONTROL TOWER

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 0m 4000 m 8145 m deepest fish (snailfish) found ALVIN (USA) 100 m 8400 m Puerto Rico trench Depths for divers 500 m 1000 m Depths for submarines MIR (Russia) Nautile (France) Sentry HROV (USA) (deepest point in the Atlantic Ocean) 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 (Curver beaked whale) 7000 m Jiaolong (China) Area: 361,000,000 km2 (71% of Earth surface) (Deepest point in the Pacific Ocean) Mariana Trench reached by: Bathyscaph Trieste on 23.1.1960. Kaiko ROV on 24.3.1995. lost in 2003 Nereus HROV on 31.5.2009. lost in 2012 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

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

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