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CC/Dr. Heinrich Frontzek The Bionic Learning Network of Festo

The Bionic Learning Network of Festo

Presentation by Dr. Heinrich Frontzek, Festo AG & Co. KG, Esslingen [email protected]

Impulses from nature for sustainable and human-friendly automation


Festo – Facts Festo is a global leader in automation technology and the world market leader in technical education. The objective: maximum productivity and competitive strength for customers in factory and process automation.

• 300,000 customers worldwide • 17,000 employees in 176 countries • Euro 2.3 billion in sales (2013) • Over 7 % of turnover flows into R&D • 2,900 patents worldwide • 100 product innovations per year

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Festo – competence for factory and process automation Motion Linear motion and rotation, turning, grasping, clamping Control and regulation Position, travel, force, pressure Processes Mixing, dosing, filling, separating Diagnosis Measuring, analysis, visualization

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Natural phenomena – inspiration for factory and process automation Motion Linear motion and rotation, turning, grasping, clamping Control and regulation Position, travel, force, pressure Processes Mixing, dosing, filling, separating Diagnosis Measuring, analysis, visualization

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Bionics = biology + technology: interdisciplinary learning from nature Bionics to enhance creativity. Bionics as structured process Top-down process An engineer identifies a technological problem. Together with biologists he searches for biological role models. Example: NanoForceGripper Bottom-up process A biologist discovers a biological phenomenon, which then gets technologically implemented with the help of engineers. Example: adaptive gripper 5


Bionic Learning Network – from the model to the product: “adaptive “

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Natural model Technical principle Bionic adaptation Industrial Application


The Bionic Learning Network of Festo

• Interdisciplinary core team • Specialists from the relevant departments • External development partners • Universities and institutes • Students and trainees • Private inventors

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Bionic Learning Network – objectives

• Creating networks and discerning trends in research and development

• Motivating people from various sectors to develop their ideas together with Festo

• Initiating dialogue with customers and partners

• Analysing customer feedback on innovative topics at trade fairs

• Expediting product pre-development

We want to provide impetus and initiate innovations.

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Efficiency strategies in nature Nature has ideally adapted to its surroundings throughout millions of years of evolution. Energy efficiency Animals that use their resources sparingly

gain a competitive advantage. Lightweight design A light but stable skeleton helps save

energy.

Functional integration Weight can be saved when several

functions are integrated into the one element.

Communication and learning Animals that know where and how to find

the best resources have a clear selective

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Efficiency strategies in nature Artificial Intelligence and Communication Human-Machine-Interaction Safe and intuitive • Machine-Machine-Communication • Machine Learning • Condition Monitoring • Process-safety: real-time diagnosis

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Efficiency strategies in nature Artificial Intelligence and Communication • Human-Machine-Interaction Machine-Machine-Communication

Swarm Behaviour • Machine Learning • Condition Monitoring • Process-safety: real-time diagnosis

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Efficiency strategies in nature Artificial Intelligence and Communication • Human-Machine-Interaction • Machine-Machine-Communication Machine Learning Condition Monitoring real-time diagnosis guarantees process-

safety

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Efficiency strategies in nature Energy-efficiency New materials • New kinematics • Energy recovery • Light-weight construction • Function integration

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Efficiency strategies in nature Energy-efficiency • New materials New kinematics Energy recovery • Light-weight construction • Function integration

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Efficiency strategies in nature Energy-efficiency • New materials • New kinematics • Energy recovery Light-weight construction Function integration

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SmartBird - Bird flight deciphered

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SmartBird – the fascination of bird flight One of the oldest dreams of mankind is to fly like a bird. As long ago as 1490, Leonardo da Vinci built rudimentary flapping wing models in order to come closer to achieving bird flight.

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SmartBird – Theoretical basis

• Bird flight analyzed in detail • Resource efficient lightweight construction • Function integration of propulsion and lift

in the wings achieved by active torsion • Measurement and control with intelligent

Condition Monitoring

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SmartBird – Bird flight deciphered SmartBird is an ultralight but powerful flight model with excellent aerodynamic qualities and extreme agility. With SmartBird, Festo has succeeded in deciphering the flight of birds. This bionic technology- bearer, which is inspired by the herring gull, can start, fly and land autonomously – with no additional drive mechanism.

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SmartBird – Aerodynamic lightweight design with active torsion

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SmartBird – new approaches in automation Energy-efficient and resource-friendly: The minimal use of materials and the extremely lightweight construction pave the way for efficiency in resource and energy consumption.

Process-safety ensured by Condition Monitoring: Data on SmartBird’s wing position and torsion are constantly registered during flight. Through continuous Condition Monitoring production downtimes will be reduced in the production of the future and the maintenance is facilitated.

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SmartBird – Bird flight deciphered

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The dragonfly The dragonfly can carry out highly complicated flight manoeuvres. They can accelerate rapidly, brake abruptly and turn quickly and even fly backwards. They can move in any spatial direction, hover motionless in the air, glide without flapping their wings and change between flight modes. Dragonflies can master all flight conditions of a helicopter, a plane and even a glider.

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© Flickr Christoph Alexander Martsch

© Flickr Ana_Cotta © Flickr whologwhy © Flickr donjd2 © Flickr PaulSteinJC


The dragonfly

• 6000 species • Body length 18 mm – 190 mm • Body weight 0.2 g • Weight of a wing 2 mg • Thickness of a wing 220 µm – 3 µm • Maximum speed 54 km/h • Maximum distance 1000 km

• Wings moved by direct flight muscles • At least 5 muscles per wing • 3-15 neurons control each wing

separately

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BionicOpter – technical details

• A brushless motor to drive the beat frequency of the four wings. • Each wing is individually twisted by one servo motor • One additional servo motor at the joint of each wing controls the amplitude. 9 degrees of freedom

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BionicOpter – lightweigth design and function integration

Laser-sintered polyamide

Aluminium

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Aluminium

Deep-drawn ABS terpolymer

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Aluminium

Deep-drawn ABS terpolymer

Carbon fibres and polyester membrane for the wings

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Structural Analysis of a Dragonfly Wing, Jongerius and Lentink 2001




BionicOpter – positioning of wings Inspired by quadrocopters we changed the positioning of the four wings of the BionicOpter away from a parallel position, by shifting the wings by 30°. Forces are distributed better during forward flight Wings almost touch and close a 360° circle when

hovering MAV is easier to control

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BionicOpter – vibrations Changing the frequency of an MAV with flapping wing drive can result in vibrations that decrease the energy efficiency, make the system hard to control and can even lead to damage the mechanical components when the vibrations build up. Real dragonflies only rarely move their forewings and hindwings in full synchrony (0° phase shift). highly energy consuming Real dragonflies only rarely move their forewings and hindwings in an opposing fashion (180° phase shift). Hindwing leads this movement in a phase shift of 50° to 100°, energy efficient BionicOpter: forewing leads the movement in a phase

shift

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Dragonflies of the world, Silsby 2001


BionicOpter – function integration • Sensors, actuators and mechanism along with

communication and control technology are installed within a minimum of space.

• A high-performance ARM microcontroller calculates all the parameters necessary for flight.

• The pilot only defines the direction and speed • Data on the position and the twisting of the wings are

continuously recorded and evaluated in real time . Flight safety ensured by condition monitoring on board

New approaches in automation: • More and more functions will get integrated into the smallest

space • Components will become smarter and more flexible

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BionicOpter – technical details

• A wingspan of 63 cm

• Body length of 44 cm

• Weight 175 g

• 2 LiPo cells with 7.4 V 350 mA

• 3 min to 4 min of flight time

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BionicOpter

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BionicOpter

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BionicOpter

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Thank you very much for your attention

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More info: www.festo.com/bionic

the bionic learning network of festo - ifac 2014 · the bionic learning network of festo...

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