Automation/Autonomous Systems

Assessing workers' physical, cognitive and collaborative skills

A UTA computer scientist is developing a smart, robot-based system that assesses workers' physical, cognitive and collaborative skills while they perform simulated manufacturing tasks, focusing on the best ways to train and prepare workers, both with and without disabilities, for the industry of the future, where a worker has to safely and efficiently collaborate with advanced robots.

Developing an airborne network computer platform for UAVs

A UTA electrical engineering developing a networked airborne computing platform for multiple unmanned aerial systems that will enable the use of networked UAVs for civilian applications such as intelligent transportation, emergency response, infrastructure monitoring and agriculture.

Better performance of autonomous vehicles

A team of UTA electrical engineers is working to improve control of networked convoys of autonomous vehicles and those operated by humans.

Collecting data for agriculture

A team of UTA researchers is using unmanned aerial vehicles to take images of agricultural fields while collecting a large amount of data that will help farmers to know ground moisture levels and crop growth.

New approach for earlier detection of Alzheimer"s

A UTA computer scientist is using machine learning to develop a novel deep learning technique that uses algorithms that mimic the structure and function of neural networks in the brain to create a deep learning pipeline that can lead to a new convolution neural network for graph classification.

Better coordination and communication among unmanned aerial vehicles

A UTA electrical engineer is working to understand how to build networks that consider both control and communication needs would increase efficiency, reduce throughput requirements and improve network management capabilities.

Superior sensing in robots

A UTA computer scientist is working to enhance the perception capabilities of robots by processing 3D point cloud data captured from low-cost sensors.

Center for Assistive Technologies to Enhance Human Performance (iPerform)

Collaborative research between university and industry researchers to increase, maintain or improve the functional capabilities of people with disabilities and enhance the productivity of well-bodied people.

Radio Frequency and Auto Identification Labs

Research into use cases and cybersecurity of RFID systems, including healthcare applications, smart hospitals, logistics and supply chain management, and manufacturing and asset tracking.

Dynamic Networks and Control Lab

Cyber-physical systems research to dynamic network and control applications. Includes various UAV, UGV, hominoid, and control system fabrication platforms.

Guidance and Control of Autonomous Systems Lab

Multiple motion-capture cameras for UAV tracking, indoor testing and evaluation of UAVs.

Robotic Vision Lab

Computer vision applied to robotics and automation. Includes a variety of state-of-the-art machines, sensors, and robot platforms.

Human-Data Interaction Laboratory

Motion capture facility to record human behaviors such as motion, facial expression, and eye movements, and produce 3D animations.

Manufacturing Automation and Robotic Systems Lab

Resources relating to robotics, manufacturing and automation and controls.

UTA Research Institute (UTARI)

• Autonomous Systems Laboratory - High-bay testing and staging area for robotics and aerial and ground vehicles. Includes a 22-camera Vicon motion-capture camera system, ground vehicles (DR Robot Jaguars, Clearpath Husky), air vehicles (3D Robotics X-8 Multicopter, Parrot AR Drone quadcopters, DJI S1000 Octocopter with Pixhawk Autopilot) and multiple sensor packages (sonar, lidar, vision).
• Robotics Laboratory - Service robotics development and testing. Includes a mock apartment with common appliances, Willow Garage PR2 humanoid robot, and a Rethink Robotics Baxter humanoid robot with Clearpath mobile base.
• Manufacturing Automation Laboratory - Systems for automation and manufacturing process research.