Cooperative Autonomous Robotics at Sea

Transcription

1 Cooperative Robotics at Sea Andreas J. Häusler Laboratory of Robotics and Systems in Science and Engineering Instituto Superior Técnico Lisbon, Portugal MARUM, September 9, 2014

2 Introduction Cheira bem, cheira a Lisboa

3 Cooperative Robotics at Sea Andreas J. Häusler Laboratory of Robotics and Systems in Science and Engineering Instituto Superior Técnico Lisbon, Portugal MARUM, September 9, 2014

4 Introduction Technological challenges of marine science. Slide 2 of 34

5 Science in Portugal Ocean Exploration Challenges Research Topics Science & Technology in Portugal Portugal Exclusive Economic Zone (EZZ) Extended Continental Shelf: km 2, or 91% of EU territory (land) Fisheries Genetic and Living Resources Mineral/Hydrocarbon/ Oil & Gas Exploitation Offshore and Wave Energy Harvesting Maritime Logistics Slide 3 of 34

6 Science in Portugal Ocean Exploration Challenges Research Topics The Azores Triple Junction Three tectonic plates meet here. The region harbors a great variety of seamounts, active underwater volcanoes, chemosynthetic ecosystems, and extreme life forms (extremophyles). Rainbow (2300 m) Lucky Strike (1700 m) Menez Gwen (850 m) Slide 4 of 34

7 Science in Portugal Ocean Exploration Challenges Research Topics Ocean Exploration Collecting bacteria Scientific Challenges Study physical, chemical, biological, and geological phenomena in the ocean and its frontiers (with the atmosphere and the Earth s interior) Technical Challenges: Large depth (high pressure) Highly corrosive environment Lack of optical visibility Challenge of accurate navigation (no GPS) Gas collection Slide 5 of 34

8 Science in Portugal Ocean Exploration Challenges Research Topics Technological Challenges 3D marine data acquisition Georeferencing Civilian authorities Instruments and methodologies for marine scientists Signal processing and data fusion Management and dissemination of information Scientific and commercial communities Slide 6 of 34

9 Science in Portugal Ocean Exploration Challenges Research Topics Technological Challenges Classical Methods Semi- Classical Methods Modern Methods The Future Slide 7 of 34

10 Science in Portugal Ocean Exploration Challenges Research Topics Key Research Topics End Users/Mission and Adaptation Navigation Control Mapping Manipulation Underwater Environment Slide 8 of 34

11 Science in Portugal Ocean Exploration Challenges Research Topics Transition from Lab to Real World Delfim Delfim X Infante Medusa S Medusa D Underwater Optical Comms. Planner Slide 9 of 34

12 Missions for cooperative groups of autonomous vehicles. Slide 10 of 34

13 ASIMOV The ASIMOV Project (2000) GREX Co 3 -AUVs MORPH CADDY Differential G PS - Reference Station - Radio Link Radio L ink Support S hip Unit (S S H U ) Radio L ink Differential G PS - Mobile Station - Surface C raft (A S C ) Radio Link Shore Station Unit (S S T U) low baud rate acoustic communication link (emergency commands) high baud rate acoustic communication link (data) low baud rate acoustic communication link (commands/data) GI B System (buoy 1 of 4) A utonomous Underwater Vehicle (A U V) Doppler log Scanning sonar Coordinated motion control Slide 11 of 34

14 ASIMOV GREX Co 3 -AUVs MORPH CADDY The GREX Project (2009) AUV fleet performing methane gradient descent Methane plume Deep water hydrothermal vent Search for mid-water column hydrothermal vents (Azores) Slide 12 of 34

15 ASIMOV GREX Co 3 -AUVs MORPH CADDY The Co 3 -AUVs Project (2012) Diver tracking system Slide 13 of 34

16 ASIMOV GREX Co 3 -AUVs MORPH CADDY The MORPH Project (2015) Adaptive mapping Slide 14 of 34

17 ASIMOV GREX Co 3 -AUVs MORPH CADDY The CADDY Project (2017) Symbiotic link between diver and autonomous companion robots Slide 15 of 34

18 AMV Concepts Example of autonomous marine vehicles. Slide 16 of 34

19 Surface Crafts Semi- Submersibles Submersibles Surface Crafts (short-term deployment) Provide geo referencing to underwater vehicles (coordinated motion) Achieve the best ratio of payload space to overall vehicle cost () base station for joint ASV/UAV missions DELFIM X (IST, Portugal) Slide 17 of 34

20 Surface Crafts Semi- Submersibles Submersibles Surface Crafts (persistent deployment) Allow for large scale (time, area) studies of the ocean Provide permanent realtime communication link, e.g., to on-shore facility No motor noise introduced to the marine environment Stable station keeping capability in high sea states Wave Glider (Liquid Robotics, USA) Slide 18 of 34

21 Surface Crafts Semi- Submersibles Submersibles Semi-Submersibles Provide a test bed for underwater communication while being easily accessible from the surface Allow for easy fusion of underwater (e.g., bottom scans) and surface (e.g., GPS) data MEDUSA S (IST, Portugal) Slide 19 of 34

22 Surface Crafts Semi- Submersibles Submersibles Submersibles (short-term deployment) Accurate navigation, e.g., for inspection of underwater pipelines Station keeping and intervention capabilities (item recovery, turning valves, etc.) Girona 500 (UdG, Spain) Slide 20 of 34

23 Surface Crafts Semi- Submersibles Submersibles Submersibles (persistent deployment) Long endurance (up to 5 years) deployment Large scale (time, space) survey missions Uniquely capable to be deployed in ocean sampling networks (biological, optical, and acoustic) Slocum (Teledyne Webb, USA) Slide 21 of 34

24 Surface Crafts Semi- Submersibles Submersibles Sea floor vehicles Sea floor intervention (taking samples, deploying stationary sensors) High accuracy mapping capabilities Very low sediment particle dispersal CMOVE (MARUM, Germany) Slide 22 of 34

25 Go-To-Formation Maneuver and Framework. Slide 23 of 34

26 Deconfliction Problem Setting Go-To- Formation Maneuver Main Features Framework Vehicle Model Example: Bathymetrybased Why do we need to plan? Efficient algorithms for multiple vehicle path planning are crucial for cooperative control systems Should take into account vehicle dynamics, mission parameters and external influences to allow for accurate tracking Usually allows to specify optimization criteria such as minimum energy usage Example: Go-To-Formation maneuver Slide 24 of 34

27 Go-To-Formation Maneuver Deconfliction Problem Setting Go-To- Formation Maneuver Main Features Framework Vehicle Model Example: Bathymetrybased Current An initial formation pattern must be established before mission start Deploying the vehicles in formation is arbitrarily hard can t be driven to target positions separately (same reason)) Slide 25 of 34

28 Go-To-Formation Maneuver Deconfliction Problem Setting Go-To- Formation Maneuver Main Features Framework Vehicle Model Example: Bathymetrybased Need to drive the vehicles to the initial formation in a concerted manner Ensure simultaneous arrival at equal speeds on temporally deconflicted trajectories Establish collision avoidance through maintaining a spatial clearance Slide 26 of 34

29 Deconfliction Problem Setting Go-To- Formation Maneuver Main Features Framework Vehicle Model Example: Bathymetrybased Main Features Vision: Groups of autonomous vehicles freely roaming the oceans Objectives: Acquire data on an unprecedented scale; detect and monitor episodic events; inspect critical infrastructure on permanent basis Requirement: a mission that can be properly executed with minimal energy expenditure Challenges: Simultaneous planning for several vehicles; possibly heterogeneous team configuration; inter-vehicle and obstacle collision avoidance; spatial team configuration; Slide 27 of 34

30 Planner Deconfliction Problem Setting Go-To- Formation Maneuver Main Features Framework Vehicle Model Example: Bathymetrybased Mission Specifications Pre- Planner Bathymetric Data Pre- Planner AMV Data Environmental Constraints Safety Distance Communication Constraint Cost Criterion Desired Trajectory Coordinated Initial Curves Paths Initial State & Input Final State & Input Dynamics Current Obstacles Projection Operator based Newton method for Trajectory Optimization (PRONTO) Expected Energy Trajectories Supervising Mission Operator Coordinated Trajectory Tracking Controller Slide 28 of 34

31 Deconfliction Problem Setting Go-To- Formation Maneuver Main Features Framework Vehicle Model Example: Bathymetrybased Seafloor Information Excitation Cost Map Map Map,,,, Map Preprocessing Generated A This normalized is could a 443-by-843 from simply version the be seafloor meter the of the inversion of map excitation the D. using of João the map a de normalized Fisher Castro generated information seamount excitation the matrix in the based Azores previous map. Before Here, measure being region step. a useful nonlinear of (i.e., the to related Atlantic the cost optimizer, to Ocean. the = norm Map the of seafloor resolution the, terrain map is used is gradient. needs 1 meter. and to The resolution a) have its was gradient downscaled information to 10-by-10 extracted, meter which squares. then is mapped from 0,1 into 10,20 to ensure that the Euclidean distance b) normalized is an admissible and and consistent heuristic for A *. c) treated in an appropriate manner to form a cost map. Slide 29 of 34

32 Deconfliction Problem Setting Go-To- Formation Maneuver Main Features Framework Vehicle Model Example: Bathymetrybased Bathymetry Based PRONTO Trajectory Generator Data Load Bathymetry Load Poses Simulation Pre-Processing Run Pre-Planner Sensitivity Optimize Run PRONTO Formation Simulate PRONTO Mock-Up V A. Häusler et al., LARSyS Slide 30 of 34

33 Contribution and references. Slide 31 of 34

34 Contribution References Contribution Explicitly incorporated nonlinear vessel dynamics Four-quadrant thruster model for energy consumption and propulsion calculation Using a descent method for solving constrained continuous-time optimal control problems Pre-planners for collision avoidance and terrain-based trajectory generation Slide 32 of 34

35 Contribution References References Häusler, A. J., Saccon, A., Hauser, J., Pascoal, A. M., and Aguiar, A. P. (2014) Energy-Optimal for Multiple with Collision Avoidance. IEEE Transactions on Control Systems Technology, submitted. Häusler, A. J., Saccon, A., Hauser, J., Pascoal, A. M., and Aguiar, A. P. (2013) Four- Quadrant Propeller Modeling: A Low-Order Harmonic Approximation in Proceedings of the 9 th IFAC Conference on Control Applications in Systems (CAMS). Häusler, A. J., Saccon, A., Pascoal, A. M., Hauser, J., and Aguiar, A. P. (2013) Cooperative AUV using Terrain Information in Proceedings of the OCEANS '13 MTS/IEEE Bergen. Häusler, A. J., Saccon, A., Aguiar, A. P., Hauser, J., and Pascoal, A. M. (2012) Cooperative for Multiple in Proceedings of the 9 th IFAC Conference on Manoeuvring and Control of Craft (MCMC 2012). Slide 33 of 34

36 Thank you! Research supported in part by project MORPH of the EU FP7 (grant agreement no , and by the FCT Program PEst-OE/EEI/LA0009/2011. The work of A. Häusler was supported by a Ph.D. scholarship of the FCT under grant number SFRH/BD/68941/2010. Slide 34 of 34