The artificial intelligence (AI) field has encountered a turning point mainly due to advancements in machine learning, which allows systems to learn, improve, and perform a specific task through data without being explicitly programmed. Machine learning can be utilized with machining processes to improve product quality levels and productivity rates and to optimize design and process parameters. The systems for acoustic event detection and classification (AED/C) of noise events is a process consisted of feature extraction of the signals, meaning processing acoustic signals and converting them into symbolic descriptions that correspond to the various sound events present in the signals and their sources. The main objective of the AED/C systems is to develop algorithms able to recognize and classify sound events that occur in the chosen environment, giving an appropriate response to users. By utilizing the acoustic events detection and classification systems, a clear set of design requirements can be extracted based on the noise to be attenuated. A smart structure design for noise attenuation needs clear noise input for proper smart material choice, placement and active control. This paper shows a method for detection of noise events based on machinelearning algorithm that can be further used for definition of design requirements.

The space exploration activities are merging new technologies in order to develop systems challenged to achieve capabilities for high mission experience. Inspired by the numerous applications in space exploration, with the integration of shape memory alloys (SMAs), a 3D printed continuous All Terrain Grasper Transport (AT-GT) vehicle with implemented multi-locomotion grasper was created. In order to reduce failure of the mechanical system, the vehicle is equipped with SMA suspension and SMA tensioner of a pulley system with adaptable height able to achieve movement on a given trajectory and adjust to any terrain. SMA actuators provide controllable actuation based on the simplicity of their design and the shape memory effect. By using the advantages of the origami engineering, soft robotics and smart material implementation, a bio-inspired autonomous grasper was integrated on the AT-GT, capable of leaving the vehicle, grabbing an object and bringing it back to the vehicle. The concept development, the analytical models and the prototype including the benefits of the combined work of the vehicle and the grasper are presented.

Inspired by the movement of a turtle in nature, a low-budget turtle-like robot was designed and developed to operate on natural terrain. Applying affordable additive manufacturing (3D printing) leads into creating unique 3-D structure with potential of flexibility, multi-functionality and multi-movement. By implementing solar panels, the energy from the sun is used, which makes the robot self-sustainable. The robot is controlled remotely with an android application designed for the need of this work. The bio-inspired robot can play an interesting role in real-life applications, such as monitoring in hardly accessible terrain, video and data collection for environmental friendly application, animals’ observation and others. The main application of the robot is for animal observation in the zoo, so it will often need to move across not even landscape in order to allow surveillance of that area. By implementing smart materials, the movement of the turtle can be improved. This paper presents the design concepts and functionality, together with CAD model of the robot, the prototyping (hardware, control and application design) and the results from the measurements.