The development of artificial tactile perception systems is of paramount interest in prosthetic and robotic applications. The key goal here is to develop systems with human-like capabilities, with the help of appropriate materials and signal-converting systems. When it comes to developing prosthetic wearable and implantable devices, the biggest challenge is to engineer a suitable bio-compatible material that offers high sensitivity. The sensors developed with such materials should respond to pressure and vibration selectively and generate sensory neuron-like output signal patterns. Here, we report a tactile sensor realized using the piezoelectric property of Bombyx mori silk. Silk thin film with moderate piezoelectric properties, derived from regenerated silk fibroin is used to realize the tactile sensor. The response of the sensor to finger taps of different magnitudes was significantly distinct. The as developed tactile sensor was able to detect hand wrist movements with high degree of precision.

Unmanned aerial vehicles (UAVs) have been used in many surveillance and remote sensing applications due to their capabilities of flying over large areas with sensing devices. The sensed data such as weather information or surveillance footage is usually very time sensitive, and the mission will be successful only if the data could be captured and delivered to processing centers on time. Using the data ferrying mechanism, UAVs could collect sensed data from remote areas and ferry the data to appropriate locations for offloading before the on-board storage spaces are overloaded. The data collection and offloading strategies of UAVs should be carefully determined to ensure the timely delivery of information while saving the travel costs. This paper investigates a UAV path planning problem considering realistic data ferrying situations involving data offloading time windows and communication constraints for periodic remote sensing applications. A Mixed Integer Linear Programming (MILP) problem is formulated that finds paths for UAVs with the minimal cost to meet application deadline requirements under time window and communication constraints on data collection and offloading. A genetic algorithm (GA) based approach is designed to solve this problem. Evaluation results on different input parameters show that the proposed approach could produce near-optimal solutions with much faster execution time than the brute-force approach. The scalability of the proposed approach is validated by a major test case with 120 waypoints, in which stabilized near-optimal solutions could be found within 60,000 iterations.

Many new robotic and teleoperated applications require a high degree of mobility or dexterity that is difficult to achieve with current actuator technology. Natural muscle is an actuator that has many features, including high energy density, fast speed of response, and large stroke, that are desirable for such applications. The electrostriction of polymer dielectrics with compliant electrodes can be used in electrically controllable, muscle-like actuators. These electrostrictive polymer artificial muscle (EPAM) actuators can produce strains of up to 30% and pressures of up to 1.9 MPa. The measured specific energy achieved with polyurethane and silicone polymers exceeds that of electromagnetic, electrostatic, piezoelectric, and magnetostrictive actuators. A simple model using linear elastic theory can predict EPAM actuator performance from mechanical and electrical material properties and load conditions. A spherical joint for a highly articulated (snake-like) manipulator using EPAM actuator elements has been demonstrated. A rotary motor using EPAM actuator elements has been shown to produce a specific torque of 19 mNm/g and a specific power of 0.1 W/g. An improved EPAM motor could produce greater specific power and specific torque than could electric motors.