There is increasing interest in the use of soft materials in robotic applications ranging from wearable devices to soft grippers. While soft structures provide a number of favorable properties to robotic systems, sensing of large deformable soft structures is still a considerable challenge; sensors must not inhibit the mechanical properties of the soft body, and the potential infinite degree-of-freedom deformations mean that there is an intrinsically limited resolution of the sensing receptors. An approach to address these challenges using a conductive thermoplastic elastomer is proposed. This allows sensory strain information to be gained from deforming structures without disturbing the dynamics of the system enabling coverage of large soft surfaces. In this article, a theoretical framework is developed, which provides a set of design principles to optimize and characterize sensor implementation, allowing maximum information about location, posture, and shape of the object to be determined. The proposed approach has been tested experimentally for the case study of the universal gripper; investigating how a sensorized gripper can allow a robot to identify grasped objects to enable improved gripping and manipulation performance. © Copyright 2018, Mary Ann Liebert, Inc., publishers 2018.