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Embedded shape morphing for morphologically adaptive robots

Jiefeng Sun, Elisha Lerner, Brandon Tighe, Clint Middlemist, Jianguo Zhao

2023Nature Communications84 citationsDOIOpen Access PDF

Abstract

Shape-morphing robots can change their morphology to fulfill different tasks in varying environments, but existing shape-morphing capability is not embedded in a robot's body, requiring bulky supporting equipment. Here, we report an embedded shape-morphing scheme with the shape actuation, sensing, and locking, all embedded in a robot's body. We showcase this embedded scheme using three morphing robotic systems: 1) self-sensing shape-morphing grippers that can adapt to objects for adaptive grasping; 2) a quadrupedal robot that can morph its body shape for different terrestrial locomotion modes (walk, crawl, or horizontal climb); 3) an untethered robot that can morph its limbs' shape for amphibious locomotion. We also create a library of embedded morphing modules to demonstrate the versatile programmable shapes (e.g., torsion, 3D bending, surface morphing, etc.). Our embedded morphing scheme offers a promising avenue for robots to reconfigure their morphology in an embedded manner that can adapt to different environments on demand.

Topics & Concepts

MorphingComputer scienceRobotClimbArtificial intelligenceComputer visionEngineeringAerospace engineeringAdvanced Materials and MechanicsModular Robots and Swarm IntelligenceAdvanced Sensor and Energy Harvesting Materials
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