Design and Validation of a Soft Robotic Finger with Event-based Tactile Sensing Capability

  • Omar Fuad Faris

Student thesis: Master's Thesis


Equipping soft robotic grippers with sensing and perception capabilities faces significant challenges due to their high compliance and flexibility, limiting their ability to successfully interact with the environment. In this work, we propose a novel sensorized soft robotic finger that is designed based on the bioinspired Fin-Ray Effect® and integrates a neuromorphic event based camera for tactile sensing. A pattern of markers is embedded inside the finger such that the finger deformation is sensed by the camera. The behavior of the finger, which shows fingertip and envelope grasping modes, is studied and analyzed through a Finite Element Analysis solver and the difference in the camera response to each grasping mode is investigated. The feasibility of the design and sensing approach is demonstrated by showing its ability to detect slip by two different approaches at a temporal resolution between 500μs and 5ms. Moreover, accurate classification of the grasping mode is achieved by processing the event-based camera output. Our results show that this combination of the neuromorphic vision based sensor and the novel finger design presents a new approach that has potential to overcome significant challenges of the tactile sensing problem of soft robots by enabling complete sensorization of the finger using a single camera without negatively affecting the finger compliance and design. Employing such finger in robotic grippers has the potential to enhance high-speed automated pick and place operations in food and logistics industries by providing safe, adaptive, and precise grasping for handling a wide category of objects.
Date of AwardJul 2021
Original languageAmerican English


  • Tactile sensing
  • Soft robots
  • Neuromorphic vision-based sensor
  • Event-based camera.

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