SMART CABLE-DRIVEN SOFT MANIPULATION SYSTEM FOR SAFE HUMAN-MACHINE-ENVIRONMENT INTERACTIONS

Robotics made of soft materials have attracted great attentions in the recent years owing to their superior flexibility and adaptability for completing a wide range of tasks through only concise controls, and most importantly, inherent safety for interactions with humans and the environment. However, the limited power outputs of soft robots (especially manipulators), due to their actuation methods (e.g., via liquid crystal elastomer and shape memory alloy), incompatibility with sensors designed through traditional technologies (e.g., piezoresistive and capacitive mechanism), and the instability arising from their inherent softness, will inevitably hinder robust and reliable real-world applications of soft robotics. For instance, a flexible gripper would be too weak to pick off an apple without enough force exertion or break a blueberry without reliable sensors for feedback controls, or even could not complete a grasp under gravity in certain orientations due to its inherent softness. Hence, in this dissertation, the actuation mechanisms for soft robotic applications were first investigated mainly in the aspects of actuation easiness, deformation/motion mode, response time, and force exertion. Based on the overall comparison of these driving mechanisms, the cable-driven approach was chosen for the soft robot application for this study due to its wide range of selections in force and speed outputs, and easiness in realizing desired deformations and motions. To develop a high-efficiency and smart soft manipulator for the safe human-machine-environment interactions, great efforts were put into improving the dexterity of soft gripper & arm and integrating compliant sensing units based on triboelectric nanogenerator (TENG) technology with the soft robot structure. To be specific, a soft cable-driven finger actuator was designed with triangular notches to facilitate its inward bending and form a conformal enveloping profile during grasping. And two cables were embedded in the soft robot body, close to its inner and outer surfaces, respectively, to realize both inward and outward bending motions. Nonlinear finite element analysis (FEA) was utilized for the prediction of its deformation and the corresponding strain & stress distributions at different loading conditions, especially taking the cable-pulling effect into consideration. Then, another smart finger actuator was proposed based on the previous design but incorporated flexible TENG sensing units (tribo-skins on phalanges to detect contact pressures while TENG strips embedded inside the robot body to sense curvature). The assembled smart gripper could subtly perceive the environment and the induced electrical signals could be further utilized for feedback control and machine learning. Finally, a comprehensive soft robotic manipulator capable of shape morphing and stiffness variation was built. This manipulation system contained a soft omnidirectional arm, a bidirectional gripper, and a human-machine-interface (HMI) through TENG technology in the form of wearable finger patch for programmable remote control. For the soft robot parts, the bellow-shaped arm was actuated by three evenly distributed cables and equipped with stiffness tunning tubes which were filled with low-melting-point alloys (LMPAs). By applying Joule heating, the tubes would become flexible enough for the arm to deform while would get stiff to maintain the shape of the arm after cooling to room temperature. The finger actuator was enhanced through multi-material and flexible hinge designs, so as to perform bidirectional bending in a more stable and safer way. Also, to study an alternative solution for faster stiffness adjustment, a spine-inspired hybrid rod embedded in the central hole of the soft arm was proposed. Finite element analysis was mainly conducted to validate its effects on varying stiffness of the arm. This dissertation research, including designing dexterous soft cable-driven finger actuator and robotic arm, soft and self-powered TENG sensors for tactile and curvature perceptions, stiffness adjustment solutions for extending real-world application, and wearable human-machine interface for programmable remote controls of soft robotics, would help in establishing robust soft manipulation system for safer human-machine-environment interactions.