Averta G.

Bianchi M.

Della Santina C.

Ficuciello F.

Roa M. A.

English

PORTO@iris (Publications Open Repository TOrino - Politecnico di Torino)

29 November 2022POLITECNICO DI TORINORepository ISTITUZIONALEEditorial: On the Planning, Control, and Perception of Soft Robotic End-Effectors / Averta, G.; Della Santina, C.;Ficuciello, F.; Roa, M. A.; Bianchi, M.. - In: FRONTIERS IN ROBOTICS AND AI. - ISSN 2296-9144. - 8:(2021), p.795863. [10.3389/frobt.2021.795863]OriginalEditorial: On the Planning, Control, and Perception of Soft Robotic End-EffectorsPublisher:PublishedDOI:10.3389/frobt.2021.795863Terms of use:openAccessPublisher copyright(Article begins on next page)This article is made available under terms and conditions as specified in the  corresponding bibliographic description inthe repositoryAvailability:This version is available at: 11583/2970281 since: 2022-07-26T10:14:29ZFrontiers Media S.A.Editorial: On the Planning, Control, andPerception of Soft RoboticEnd-EffectorsGiuseppe Averta1*, Cosimo Della Santina2, Fanny Ficuciello3, Maximo A. Roa4 andMatteo Bianchi51Department of Control and Computer Engineering, Politecnico di Torino, Turin, Italy, 2Cognitive Robotics (CoR)Department, Delft University of Technology, Delft, Netherlands, 3PRISMA Lab - DIETI (Dipartimento di Ingegneria Elettricae delle Tecnologie dell'Informazione), University of Naples Federico II, Naples, Italy, 4Institute of Robotics andMechatronics, German Aerospace Center, Weling, Germany, 5Department of Information Engineering and Centro E.Piaggio, University of Pisa, Pisa, ItalyKeywords: manipulation, end-effectors, biologically-inspired robots, robot control, robot perceptionEditorial on the Research TopicOn the Planning, Control, and Perception of Soft Robotic End-Effectors1 EDITORIALIn the past, robots have been almost exclusively designed with industrial settings in mind. Accuratepositioning and precise tracking were the main requirements for performing repetitive tasks instructured environments with rigid end-effectors. In recent years, robots have come out of the cagesAlbu-Schaffer et al. (2008) and can freely interact and collaborate with humans in unstructuredscenarios. This has opened new challenges to guarantee the safety of human-robot interaction andthe purposeful interaction with the environment. To this aim, soft robots that embed compliantelements in their structure have emerged as a promising solution, and compliant end-effectors havebeen introduced, which can interact and adapt to external conditions as human hands do, havegained increasing attention.This new framework, which encompasses the design, planning, sensing, and control of soft end-effectors, comes with several theoretical and practical open challenges. Indeed, the researchcommunity has made a considerable effort to develop novel academic and technologicalsolutions to allow robots to operate amongst and with humans and safely move in, and interactwith, unknown and unstructured environments.Still, the question of how to use embedded compliance to enhance the interaction with theenvironment exploiting the multiple degrees of freedom of a soft manipulator is an open problem(Billard, 2019).Edited and reviewed by:Cecilia Laschi,National University of Singapore,Singapore*Correspondence:Giuseppe Avertagiuseppe.averta@polito.itSpecialty section:This article was submitted toSoft Robotics,a section of the journalFrontiers in Robotics and AIReceived: 15 October 2021Accepted: 29 October 2021Published: 22 November 2021Citation:Averta G, Della Santina C, Ficuciello F,RoaMA and Bianchi M (2021) Editorial:On the Planning, Control, andPerception of Soft Robotic End-Effectors.Front. Robot. AI 8:795863.doi: 10.3389/frobt.2021.795863Frontiers in Robotics and AI | www.frontiersin.org November 2021 | Volume 8 | Article 7958631EDITORIALpublished: 22 November 2021doi: 10.3389/frobt.2021.795863Indeed, a valid formalization could be to exploit model-basedoptimization approaches. An alternative approach is the usage oflearning techniques to generalize from data acquired throughtactile sensing. Another promising strategy is understanding howhumans solve the problem at the muscular-skeletal level, with theultimate goal to produce a limited yet effective replication ofhuman-inspired solutions.The manuscripts collected in this e-book shed some light onthe usage of soft end effectors to interact with the surroundingworld, presenting advanced design, control, and tactile sensingsolutions.2 NOVEL DESIGN IDEAS TO TARGETCURRENT CHALLENGES IN SOFTROBOTIC MANIPULATIONAlthough several design solutions for soft end effectors havebeen proposed by the research community in the last decade,they are still far from the complexity and the capabilities ofhuman hands, especially when the task is to grasp andmanipulate in an unstructured and challengingenvironment. A typical example relies upon largewarehouses, in which robots should quickly grasp andrelocate a wide range of objects. In those cases,anthropomorphic robotic hands may fail in the case ofhigh-speed tasks. A method to bridge this gap was proposedin Kakogawa et al. through the development of an under-actuated mechanism that can grasp and pull a wide range ofdifferent objects. The two actions are performed by one singleactuator, producing a substantial complexity reduction w.r.t.conventional designs. The implementation can be performedin multiple ways, including two solutions presented by theauthors: one driven by a DC motor with planetary gearreducers and the second driven by pneumatic actuators withbranch tubes as a differential. In both cases, the pulling-inmechanism is achieved by a belt-driven finger surface and alinear slider with an air cylinder, respectively. Interestingly,such a design enables a combination of grasping and pullingactions, increasing the dexterity of classic under-actuated end-effectors.However, the flexibility granted by soft hands can even gobeyond the hand itself and be further expanded by theintroduction of an additional degree of flexibility brought inby the possibility of quickly locking and unlocking the gripperfrom the robotic arm. This novel paradigm, introduced in Iqbalet al., presents the chance to exploit collaborative grippers thatcan be easily attached and detached from the robot arm and alsoused independently from it. The authors demonstrated withexperiments involving 12 participants that this solution canincrease the number of working conditions in whichcompliant robotic hands, complemented with tactile feedbackto support the magnetic tool changer, can enhance humanactivity.Of note, the anthropomorphic design is not per se the optimalsolution in all the cases. On the contrary, following Occam’sRazor principle, non-anthropomorphic solutions should bepreferred for certain tasks. This is the core of the interestingperspective discussion proposed in Hao and Visell, in which theAuthors discuss how emerging soft robotic technologies appliedto non-anthropomorphic grippers have yielded new techniquesthat can circumvent fundamental challenges associated withgrasping via fingered grippers. Mechanisms for morphologicaldeformation or adhesion, which simplify the grasping of diverseobjects in different poses without detailed knowledge of the objectgeometry, are common to many non-anthropomorphic softgrippers are. These solutions could enable the usage of roboticmanipulation in challenging applications, such as logistics orrapid manufacturing, with lower cost and complexity. Yet, manychallenges, reviewed in Hao and Visell, remain open, and severalresearch directions are ready to be explored.3 TECHNIQUES TO EXPLOIT THEENHANCED CAPABILITIES OF SOFTEND-EFFECTORSAs briefly mentioned above, the avenue of innovative softgrippers design has offered several benefits, such as reducedcost, enhanced compliance, and customized design, with thepromise of dexterity and robustness. However, to harnessthese characteristics, it is crucial to develop new tools tounderstand the capabilities of such manipulators and tofacilitate manipulation planning with soft robotic grippersthat exhibit free-form deformations. This topic is discussed inSun et al. through the development of a sampling-basedapproach to discover and model continuous families ofmanipulations for soft robot hands. The method consists ofsampling the space of manipulation actions, constructingGaussian Mixture Model representations coveringsuccessful regions, and refining the results to createcontinuous successful regions representing themanipulation family. Authors considered models with andwithout dimensionality reduction, to deal with the highdimensionality of the manipulation actions space. Thisway, they provide a methodological approach to comparemodels defined with different dimensions. Interestingly, theAuthors found that, albeit dimensionality reduction istypically helpful to populate the models, it is not easy todetermine a priori the size of the low-dimensional domainbecause this may depend on the gripper and the task. Thesemodels can be used to plan and carry out successful and robustmanipulation actions and compare competing robot handdesigns.4 ADAPTABLE TACTILE SENSING FORSOFT ROBOTIC HANDSThe studies of how robots should interact with thesurrounding environment often focus on the actionsapplied to the external object. However, the dual problemof sensing the contacts is of equal importance. Indeed, theextraordinary manipulation capabilities of humans stronglyFrontiers in Robotics and AI | www.frontiersin.org November 2021 | Volume 8 | Article 7958632Averta et al. Editorial: Planning, Control and Perception of Soft Handsdepend and rely on the advanced tactile sensing system spreadover our body and skin. In Hughes et al., the Authorsproposed a compelling analysis on sensors morphology andstructure that, for a given task, can significantly aid andimprove tactile sensing capabilities. This can be done byrelying on mechanisms such as improved sensitivity ormorphological computation. Indeed, different tactile taskscan require different morphologies: this poses significantchallenges related to the optimal design of sensors, whichshould ideally be variable. In Hughes et al., the Authorsdeveloped a jamming filter which, when placed over atactile sensor, allows the filter to be shaped and moldedonline, thus varying the sensor structure. This solutiondemonstrated to be beneficial for sensory tasks since anadaptive structure can be used to alter and improve theamount and the quality of the information gatheredthrough the sensors.AUTHOR CONTRIBUTIONSAll authors listed have made a substantial, direct, andintellectual contribution to the work and approved it for publication.FUNDINGThe work has received funding from the European Union’s Horizon2020 Research and Innovation Programme under Grant AgreementNo. 871237 (SOPHIA) and the Horizon 2020 - European ResearchCouncil (ERC) under Grant Agreement No. 810346 (NaturalBionicS). It has also received funding from the Italian Ministry ofEducation, and Research (MIUR) in the framework of the CrossLabproject (Department of Excellence) and from the SpanishGovernment through the project CaRo, under Grant NumberPID2020-114819GB-I00.REFERENCESAlbu-Schaffer, A., Eiberger, O., Grebenstein, M., Haddadin, S., Ott, C., Wimbock,T., et al. (2008). Soft Robotics. IEEE Robot. Automat. Mag. 15, 20–30.doi:10.1109/mra.2008.927979Billard, Aude and Kragic, D. (2019). Trends and challenges in robot manipulation.Science 364, 6446.Conflict of Interest: The authors declare that the research was conducted in theabsence of any commercial or financial relationships that could be construed as apotential conflict of interest.Publisher’s Note:All claims expressed in this article are solely those of the authors anddonot necessarily represent those of their affiliated organizations, or those of the publisher, theeditors and the reviewers. Any product that may be evaluated in this article, or claim thatmay be made by its manufacturer, is not guaranteed or endorsed by the publisher.Copyright © 2021 Averta, Della Santina, Ficuciello, Roa and Bianchi. This is anopen-access article distributed under the terms of the Creative Commons AttributionLicense (CC BY). The use, distribution or reproduction in other forums is permitted,provided the original author(s) and the copyright owner(s) are credited and that theoriginal publication in this journal is cited, in accordance with accepted academic practice.No use, distribution or reproduction is permitted which does not comply with these terms.Frontiers in Robotics and AI | www.frontiersin.org November 2021 | Volume 8 | Article 7958633Averta et al. Editorial: Planning, Control and Perception of Soft Hands

Editorial: On the Planning, Control, and Perception of Soft Robotic End-Effectors

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Editorial: On the Planning, Control, and Perception of Soft Robotic End-Effectors

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