Computer vision as an entire field has a wide and diverse range of applications. The specific application for this project was in the realm of dance, notably ballet and choreography. This project was proof-of-concept for a choreography assistance tool used to recognize and record dance movements demonstrated by a choreographer. Keeping the commercial arena in mind, the Kinect from Microsoft was chosen as the imaging hardware, and a pilot set chosen to verify recognition feasibility. Before implementing a classifier, all training and test data was transformed to a more applicable representation scheme to only pass the important aspects to the classifier to distinguish moves for the pilot set. In addition, several classification algorithms using the Nearest Neighbor (NN) and Support Vector Machine (SVM) methods were tested and compared from a single dictionary as well as on several different subjects. The results were promising given the framework of the project, and several new expansions of this work are proposed.

Mobile robots are often proposed as a favorable substitute to human correspondence in emergency response, disaster relief, and environmental monitoring scenarios. In this work, the next iteration of the Aquapod is proposed as a method to facilitate collection of subsurface liquid samples in order to assess toxicity levels in a body of water. This amphibious small form-factor robot is equipped with a buoyancy control unit, detachable fluidic sampling unit, and a wide range of sensing and processing capabilities. The robot was designed to move and collect water samples to a maximum depth of ten meters. Its unique form of tumbling locomotion results in a versatile platform that can be used in both terrestrial and aquatic environments leveraging its high mobility-to-size ratio.

In this paper we introduce tumbling, a relatively unexplored method of locomotion in which the robot utilizes net body rotations while ambulating. Tumbling for mobile robots is attractive in that it can enable increased mobility on smaller scales, often while reducing hardware requirements. As motivation for this interesting form of locomotion we provide a geometric analysis of a vertical step climbing task, one that tumbling robots perform well with respect to their size and complexity. In addition to our analysis we present results of a hardware experiment with a tumbling robot performing the task for varying combinations of frictional coefficients at the step and ground.