Robots can be used to mitigate risks in unsafe and austere settings. In recent years, explosive ordnance disposal robots have reduced the technician's time-on-target, and thus, reduce the direct risk of exposure. This article focuses on the study and development of innovative techniques as the foundational work for a new robot platform. The proposed system includes an organic electrochemical transistor device to detect the existence of explosive residues, and lead to decisions for safe-removal progress. Taurus' surgical gripper facilitates object tactile exploration, and manipulation with control precision to the millimeter range. The highly sensitive triboelectric tactile sensor could reduce intrusiveness during contact, and mitigate the risk of detonation. Haptic devices and visual displays are used to convey important signals, in order to improve the situational awareness of the teleoperator. A machine learning classifier can be used to assist the user to identify objects from tactile sampling. The integration of these methodologies allows for a sensitive approach to concealed objects that are only accessible through tactile sensing.

Robotic exploration under uncertain environments is challenging when optical information is not available. In this article, we propose an autonomous solution of exploring an unknown task space based on tactile sensing alone. We first designed a whisker sensor based on MEMS barometer devices. This sensor can acquire contact information by interacting with the environment nonintrusively. This sensor is accompanied by a planning technique to generate exploration trajectories by using mere tactile perception. This technique relies on a hybrid policy for tactile exploration, which includes a proactive informative path planner for object searching, and a reactive Hopf oscillator for contour tracing. Results indicate that the hybrid exploration policy can increase the efficiency of object discovery. Last, scene understanding was facilitated by segmenting objects and classification. A classifier was developed to recognize the object categories based on the geometric features collected by the whisker sensor. Such an approach demonstrates the whisker sensor, together with the tactile intelligence, can provide sufficiently discriminative features to distinguish objects.