Mechanoreception for Soft Robots via Intuitive Body Cues
| Autor: | Liangliang Wang, Zheng Wang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science body deformation Biophysics 02 engineering and technology Signal 020901 industrial engineering & automation Artificial Intelligence Position (vector) Biomimetics medicine Humans Mechanical Phenomena Pneumatic actuator Stiffness Control engineering Equipment Design Robotics 021001 nanoscience & nanotechnology linear pneumatic actuator Identification (information) mechanoreception Control and Systems Engineering Control system soft-rigid hybrid gripper Robot soft robot Original Article medicine.symptom Cues 0210 nano-technology Actuator |
| Zdroj: | Soft Robotics |
| ISSN: | 2169-5180 2169-5172 |
| Popis: | Mechanoreception, the ability of robots to detect mechanical stimuli from the internal and external environments, contributes significantly to improving safety and task performance during the operation of robots in unstructured environments. Various approaches have been proposed to endow robot systems with mechanoreception. In the case of soft robots, the state-of-the-art mechanosensory solutions typically embedded dedicated deformable sensors into the soft body, giving rise to fabrication complexity and signal sophistication. In this study, we propose a novel mechanoreception scheme to enable pneumatic-driven soft robots to perceive proprioceptive movements as well as external contacts. Both internal and external mechanical parameters can be decoded from intuitive cues of body deformation and pneumatic pressure signals. In contrast to most existing solutions employing dedicated deformable sensors, the proposed approach only utilizes pressure feedback, which is typically available from the pneumatic pressure sensors incorporated in the control loop of most pneumatic soft robots. The concept was implemented and validated on a proprietary robotic gripper with a linear soft pneumatic actuator, demonstrating the capability in simultaneous detection of actuator position and external contact forceAfter the proposed approach, the gripper can achieve both active and passive mechanosensation, with demonstrated experiments in grasping force estimation, contact loss detection, object stiffness identification, and contour measurements. This approach offers an alternative route to achieving excellent internal/environmental awareness without requiring dedicated sensing modalities. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|