Seeing by Touch: Evaluation of a Soft Biologically-Inspired Artificial Fingertip in Real-Time Active Touch

Effective tactile sensing for artificial platforms remains an open issue in robotics. This study investigates the performance of a soft biologically-inspired artificial fingertip in active exploration tasks. The fingertip sensor replicates the mechanisms within human skin and offers a robust solution that can be used both for tactile sensing and gripping/manipulating objects. The softness of the optical sensor's contact surface also allows safer interactions with objects. High-level tactile features such as edges are extrapolated from the sensor's output and the information is used to generate a tactile image. The work presented in this paper aims to investigate and evaluate this artificial fingertip for 2D shape reconstruction. The sensor was mounted on a robot arm to allow autonomous exploration of different objects. The sensor and a number of human participants were then tested for their abilities to track the raised perimeters of different planar objects and compared. By observing the technique and accuracy of the human subjects, simple but effective parameters were determined in order to evaluate the artificial system's performance. The results prove the capability of the sensor in such active exploration tasks, with a comparable performance to the human subjects despite it using tactile data alone whereas the human participants were also able to use proprioceptive cues.