Tactile sensing and logical reasoning strategies aid a robot's ability to recognize and classify objects

The main attributes that the robot can perceive through the spatiotemporal tactile sensing method during hand grasping include thermal conductivity, thermal diffusivity, surface roughness, contact pressure, and temperature. This allows the robot to simultaneously perceive multiple attributes of the grasped object, leading to more robust and accurate object detection.

Researchers from Tsinghua University have developed a tactile sensing strategy that incorporates thermal sensations for more robust and accurate object detection. They designed a layered sensor with material detection at the surface and pressure sensitivity at the bottom, with a porous middle layer sensitive to thermal changes. They paired this sensor with an efficient cascade classification algorithm that rules out object types in order, from easy to hard. This spatiotemporal sensing and logical reasoning approach allows the robots to simultaneously perceive multi-attributes of the grasped object, including thermal conductivity, thermal diffusivity, surface roughness, contact pressure, and temperature. This method achieved a classification accuracy of 98.85% in recognizing diverse garbage objects not encountered previously.