Soft Robotics Education

Abstract Robotics education poses a significant challenge because it involves a number of different technological components and disciplines. So far, most of the existing teaching approaches focus on robots with fixed morphologies and rigid structures, which cover only subsets of the entire spectrum of related knowledge. From this perspective, this article explores an application of soft robotics research for robotics education and discusses the challenges and perspectives. We argue that the use of soft materials is crucial for understanding and teaching of a variety of topics related to intelligent adaptive systems. Along with the conceptual discussion, we introduce how the concept can be implemented into practical educational programs and report the latest concrete achievements in our lecture series.

[1]  R. Pfeifer,et al.  Self-Organization, Embodiment, and Biologically Inspired Robotics , 2007, Science.

[2]  Fumiya Iida,et al.  The challenges ahead for bio-inspired 'soft' robotics , 2012, CACM.

[3]  Kuldeep Rawat,et al.  A hands-on laboratory based approach to undergraduate robotics education , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[4]  B. Finio,et al.  Air-powered soft robots for K-12 classrooms , 2013, 2013 IEEE Integrated STEM Education Conference (ISEC).

[5]  Robin R. Murphy.  "Competing" for a robotics education , 2001, IEEE Robotics Autom. Mag..

[6]  Ian D. Walker,et al.  Soft robotics: Biological inspiration, state of the art, and future research , 2008 .

[7]  Hironari Taniguchi,et al.  Flexible Artificial Muscle Actuator Using Coiled Shape Memory Alloy Wires , 2013 .

[8]  Fumiya Iida,et al.  An Energy-Efficient Hopping Robot Based on Free Vibration of a Curved Beam , 2014, IEEE/ASME Transactions on Mechatronics.

[9]  Mohammad Mahdi Kheirikhah,et al.  A Review of Shape Memory Alloy Actuators in Robotics , 2010, RoboCup.

[10]  Rolf Pfeifer,et al.  Morphological Computation - Connecting Brain, Body, and Environment , 2006, Australian Conference on Artificial Intelligence.

[11]  Fumiya Iida,et al.  Robotic body extension based on Hot Melt Adhesives , 2012, 2012 IEEE International Conference on Robotics and Automation.

[12]  Fumiya Iida,et al.  Robotics education: A case study in soft-bodied locomotion , 2013, 2013 IEEE Workshop on Advanced Robotics and its Social Impacts.

[13]  Heinrich M. Jaeger,et al.  Universal robotic gripper based on the jamming of granular material , 2010, Proceedings of the National Academy of Sciences.

[14]  Yutaka Nakamura,et al.  Bacteria-inspired underactuated mobile robot based on a biological fluctuation , 2012, Adapt. Behav..

[15]  Surya Girinatha Nurzaman,et al.  Guided Self-Organization in a Dynamic Embodied System Based on Attractor Selection Mechanism , 2014, Entropy.

[16]  Fumiya Iida,et al.  Minimalistic Models of an Energy-Efficient Vertical-Hopping Robot , 2014, IEEE Trans. Ind. Electron..

[17]  R. Mayer.  Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. , 2004, The American psychologist.

[18]  Akio Ishiguro,et al.  Soft Robotics [TC Spotlight] , 2013, IEEE Robotics & Automation Magazine.

[19]  Cecilia Laschi,et al.  Soft robotics: a bioinspired evolution in robotics. , 2013, Trends in biotechnology.

[20]  Kiyoshi Nagai.  Learning while doing: practical robotics education , 2001, IEEE Robotics Autom. Mag..

[21]  Barry Trimmer,et al.  Soft robots , 2013, Current Biology.

[22]  LipsonHod,et al.  Challenges and Opportunities for Design, Simulation, and Fabrication of Soft Robots , 2014 .

[23]  J. Bruner.  The act of discovery. , 1961 .

[24]  Fumiya Iida,et al.  Active Sensing System with In Situ Adjustable Sensor Morphology , 2013, PloS one.