BIOINSPIRED APPROACHES TO DESIGN AND CONTROL OF MOBILE SOFT ROBOTS - PowerPoint PPT Presentation

BIOINSPIRED APPROACHES TO DESIGN AND CONTROL OF MOBILE SOFT ROBOTS Marcello Calisti, PhD The BioRobotics Institute, ShanghAI Lectures 2017 Edition, December 7 th , 2017

Bioinspired approaches to design and control soft robots What’s a soft robot? “inherently compliant and exhibit large strains in normal operations” “soft robotic manipulators are continuum robots made of soft materials that undergo continuous elastic deformation and produce motion through the generation of a smooth backbone curve” “systems that are capable of autonomous behavior, and that are primarily composed of materials with moduli (i.e. Young module) in the range of that of soft biological materials” “Soft robots/devices that can actively interact with the environment and can undergo large deformations relying on inherent or structural compliance” Laschi C, Mazzolai B, Cianchetti M. 2016 Soft robotics: technologies and systems pushing theboundaries of robot abilities. Sci. Robot. 1

Bioinspired approaches to design and control soft robots Push forward robots’ capabilities Where soft robots dare: «[…] capabilities for performing actions, such as squeezing, stretching, climbing and growing, that would not be possible with an approach to robot design based on rigid links only.» […] applications of an ability can eventually materialize in diverse fields.» Compliant/soft Diverse Ability technologies applications Used in Enable Very strong, forward looking statement, which is not completely satisfied by the current state of the art soft robots. Compliant/soft Diverse Ability technologies applications Used in Enable OR improve Laschi C, Mazzolai B, Cianchetti M. 2016 Soft robotics: technologies and systems pushing theboundaries of robot abilities. Sci. Robot. 1

Bioinspired approaches to design and control soft robots Bio-inspiration for mobile soft robots Conflictual goals Having a compliant, Exerting forces to deformable body the environment Forces and deformations should be performed at the right time and with appropriate control law By taking inspiration from soft animals “We consider belonging to soft robotics field each robot for which locomotion is enabled by deformable (due to inherent or structural compliance) components or which relies on such deformable components to increase quantitative or qualitative performance . ”

Bioinspired approaches to design and control soft robots Fundamentals of soft robot locomotion Crawling Flying • • Fixed wing Two anchor • • Peristaltic Flapping wing • Serpenting Swimming • Lift-induced Legged • Drag-induced • • Running Undulation • Walking • Jet propulsion Not bioinspired Jumping • Quasi-static rolling • • Vibration-based Ballistic jump Calisti, M., G. Picardi, and C. Laschi. "Fundamentals of soft robot locomotion." Journal of The Royal Society Interface 14.130 (2017): 20170101.

Bioinspired approaches to design and control soft robots Biological model and locomotion principle: two-anchor crawl 𝑁 : mass of the animal 𝜇 : elongation and shortening action 𝑕 : gravity acceleration 𝐺 𝑦 = 𝜈 −𝑦 𝑁𝑕 𝐺 −𝑦 = −𝜈 𝑦 𝑁𝑕 𝑆 = 𝜈 −𝑦 𝑁𝑕 − 𝜈 𝑦 𝑁𝑕 𝑆 > 0 → 𝜈 −𝑦 𝑁𝑕 > 𝜈 𝑦 𝑁𝑕 → 𝝂 −𝒚 > 𝝂 𝒚 Elongation (shortening) Adhesion mechanism mechanism

Bioinspired approaches to design and control soft robots Elongation mechanism: tendons / motors Student challenge: SoftRobotics Week 2015 Umedachi T, Vikas V, Trimmer BA. 2016 Softworms: the design and control of non-pneumatic, 3D- printed, deformable robots. Bioinspir. Biomim. 11, 25001. (doi:10.1088/1748-3190/11/2/025001)

Bioinspired approaches to design and control soft robots Legged crawler Crawling gait (not walking) Why legged? End pose Multi-gait locomotion Sliding of the frontal part of the robot Tolley, Michael T., et al. "A resilient, untethered Change of the anchor (no locomotion) soft robot." Soft Robotics 1.3 (2014): 213-223. Shepherd RF, Ilievski F, Choi W, Morin SA, Stokes Sliding of the rear part of the robot AA, Mazzeo AD, Chen X, Wang M, Whitesides GM. 2011 Multigait soft robot. Proc. Natl Acad. Sci. USA 111, 20 400 – 20 403. (doi:10.1073/pnas. Initial pose 1116564108)

Bioinspired approaches to design and control soft robots Biological model and locomotion principle: peristaltic crawl Fundamental element is still the Hydrostatic skeletons , but in peristaltic locomotion the actuation pattern is the key to obtain locomotion Waves of contraction move backward (or forward in some cases) along the body, and segments of the body lengthen and shorten in turn 5 4 3 7 2 1 6 Shortening segment Lengthening segment Anchoring segments 6 5 4 3 2 1 7

Bioinspired approaches to design and control soft robots Biological model and locomotion principle 7 6 5 3 2 1 3 2 1 4 7 6 5 4 1 7 6 4 3 2 5 4 3 2 1 7 6 5 2 1 7 5 4 3 6 5 4 3 2 1 7 6 3 2 1 6 5 4 3 2 1 7 6 5 4 7 Changing anchors 7 6 5 4 3 2 1 Propulsive actions

Bioinspired approaches to design and control soft robots Biological model and locomotion principle 𝜀𝑛 : a small portion of the body mass 𝑕 : gravity acceleration 𝜈 𝑦 𝜀𝑛𝑕 < 𝜈 −𝑦 𝜀𝑛𝑕 𝜈 𝑦 : static friction coefficient (forward direction) 𝜈 −𝑦 : dynamic friction coefficient (backward direction) Coupled contraction/ elongation (1-n) n No anisotropic friction 𝜈 𝑦 𝜀𝑛𝑕𝑜 < 𝜈 −𝑦 𝜀𝑛𝑕(1 − 𝑜) required 𝜈 𝑦 𝑜 < 𝜈 −𝑦 (1 − 𝑜) 𝜈 −𝑦 𝑜 < 𝜈 𝑦 + 𝜈 −𝑦 Daltorio KA, Boxerbaum AS, Horchler AD, Shaw KM, Chiel HJ, Quinn RD. 2013 Efficient worm-like locomotion: slip and control of soft-bodied peristaltic robots. Bioinspir. Biomim. 8, 35003.

Bioinspired approaches to design and control soft robots Robotic model: focus on anchors and elongations Daltorio KA, Boxerbaum AS, Horchler AD, Shaw KM, Chiel HJ, Quinn RD. 2013 Efficient worm-like locomotion: slip and control of soft-bodied peristaltic robots. Bioinspir. Biomim. 8, 35003.(doi:10.1088/1748-3182/8/3/035003)

Bioinspired approaches to design and control soft robots Soft components exploitation Underactuation Material or structures distribute the action of the actuator, so that the need of several actuations is not needed. Moreover, underactuation could be exploited to embed control in the mechanisms. Work in harsh conditions Resilience to damages Adaptability to the environment

Bioinspired approaches to design and control soft robots Biological model and locomotion principle: running/hopping Spring-loaded inverted pendulum (SLIP) 𝑛 : point mass of the system 𝑚 0 : rest lenght of the leg (𝑦, 𝑧) : position of the mass 𝑦 𝑢 : foot position at touchdown 𝑕 : gravity acceleration Geyer, Hartmut, Andre Seyfarth, and Reinhard Blickhan. "Compliant leg behaviour explains basic dynamics of walking and running." Proceedings of the Royal Society of London B: Biological Sciences 273.1603 (2006): 2861- 2867. Stance phase: (𝑦 − 𝑦 𝑢 ) 𝑚 0 𝑦 − 𝑦 𝑢 2 + 𝑧 2 𝑛𝑦 = 𝑙 𝑚 0 − 𝑦 − 𝑦 𝑢 2 + 𝑧 2 = 𝑙(𝑦 − 𝑦 𝑢 ) 𝑦 − 𝑦 𝑢 2 + 𝑧 2 − 1 𝑚 0 𝑛𝑧 = 𝑙𝑧 𝑦 − 𝑦 𝑢 2 + 𝑧 2 − 1 − 𝑕 Elastic leg

Bioinspired approaches to design and control soft robots Biological model and locomotion principle Parameters which guarantee stable locomotion in humans: Self-stabilization of running Seyfarth, Andre, et al. "A movement criterion for running." Journal of biomechanics 35.5 (2002): 649-655.

Bioinspired approaches to design and control soft robots Soft components exploitation: energy efficiency Compliance on leg Compliance on body Rigidly attached load Elastically attached load The load (backpack) and the Decoupling the oscillation of carrier oscillate of the same the load with the oscillation of amplitude. the carrier. Rome, Lawrence C., Louis Flynn, and Taeseung D. Yoo. "Biomechanics: Rubber bands reduce the cost of carrying loads." Nature 444.7122 (2006): 1023.

Bioinspired approaches to design and control soft robots Soft components exploitation: energy efficiency Metabolic cost: 640 W→ 600 W Equivalent weight carried: 27 kg→ 21.7 kg 27Kg: fixed or suspended Rome, Lawrence C., Louis Flynn, and Taeseung D. Yoo. "Biomechanics: Rubber bands reduce the cost of carrying loads." Nature 444.7122 (2006): 1023.

Bioinspired approaches to design and control soft robots Soft components exploitation: energy efficiency 𝑌 1 = 1 − 𝐶 1 + 𝐶 2 𝑌 1 − 𝐿 1 + 𝐿 2 𝑌 1 + 𝐶 2 𝑌 2 + 𝐿 2 𝑌 2 + 𝐶 1 𝑀 (𝑢) + 𝐿 1 𝑀(𝑢) − 𝑕 𝑁 1 𝑌 2 = 1 −𝐶 2 𝑌 2 − 𝐿 2 𝑌 2 + 𝐶 2 𝑌 1 + 𝐿 1 𝑌 1 − 𝑕 𝑁 2 𝑀(𝑢) = 𝐵𝑡𝑗𝑜(𝜕𝑢) Double-mass coupled-oscillator 𝑳 𝟑 = 𝝏 𝟑 𝑵 𝟑 Ackerman, Jeffrey, and Justin Seipel. "Energy efficiency of legged robot locomotion with elastically suspended loads." IEEE Transactions on Robotics 29.2 (2013): 321-330. average positive power of locomotion

Bioinspired approaches to design and control soft robots Soft components exploitation: energy efficiency

Bioinspired approaches to design and control soft robots Soft components exploitation: behavioral diversity Compliance Compliance Shape- on leg on body changing body