Dylan Wallace
I'm Dylan Wallace, an undergraduate in Electrical Engineering at the University of Nevada, Las Vegas. I am currently performing undergraduate research at UNLV's Drones and Autonomous Systems Lab. My research interests include networking, computer vision, and machine learning for autonomous systems, specifically humanoid robotics. Outside of my research I enjoy traveling, politics, and music. My hobbies include 3D printing & modeling, hobby electronics, and custom PC building.
IEEE 2nd General Meeting
03/07/19
Spring Break Trip
03/15/19-03/24/19
UPCOMING EVENTS
IEEE Eagle Workshop
03/14/19
MY LATEST RESEARCH
Augmenting a miniature humanoid platform with a low-cost networked computer vision framework
Miniature humanoids are becoming an increasingly common platform for humanoid robotics research and education. However, the prohibitively high cost of advanced platforms such as the ROBOTIS-OP2 drives many educators and small research institutions toward cheaper options such as the ROBOTIS-Mini. While these platforms have versatility in full-body motion, they often lack computational power and vision capabilities. This paper presents the augmentation of the ROBOTIS-Mini with a camera, local processor, and networked system for computer vision. This augmented platform is referred to as Mini-CV. The Mini-CV system provides an ultra low-cost solution for computer vision that reduces the need for high on-board computational power and provides an advanced framework for networked control. A study of the latency in the system is presented and compared to that of the ROBOTIS-OP2, a popular miniature humanoid that retails for more than 20× the price of our augmented system. The results demonstrate the viability of the Mini-CV as an ultra low-cost alternative to more expensive miniature humanoid platforms.
Toward deep space humanoid robotics inspired by the NASA Space Robotics Challenge
This paper presents the initial work toward deep space robotic applications. Humanoid robots as astronauts can experience gravity differences, hazardous environmental conditions, extreme latency communications, and lack of energy sources while on deep space missions. Such constraints provide a challenge in the development of software, hardware, and experiments for space humanoid robots. This paper demonstrates the preliminary work for deep space robotics through the two qualification tasks specified by NASA's Space Robotics Challenge. The tasks are implemented in both the SRC simulator using IHMC ROS APIs, and with a physical humanoid robot, DRCHubo. The main objective is to testify the fundamental vision capability and maneuverability for deep space missions. This paper serves as a reference for future research in the field of deep space robotics.