Robotics Commons^™

Parallel Real Time Rrt*: An Rrt* Based Path Planning Process, David Yackzan

Theses and Dissertations--Mechanical Engineering

This thesis presents a new parallelized real-time path planning process. This process is an extension of the Real-Time Rapidly Exploring Random Trees* (RT-RRT*) algorithm developed by Naderi et al in 2015 [1]. The RT-RRT* algorithm was demonstrated on a simulated two-dimensional dynamic environment while finding paths to a varying target state. We demonstrate that the original algorithm is incapable of running at a sufficient rate for control of a 7-degree-of-freedom (7-DoF) robotic arm while maintaining a path planning tree in 7 dimensions. This limitation is due to the complexity of maintaining a tree in a high-dimensional space and the network …

Formation Control With Bounded Controls And Collision Avoidance: Theory And Application To Quadrotor Unmanned Air Vehicles, Zachary S. Lippay

Theses and Dissertations--Mechanical Engineering

This dissertation presents new results on multi-agent formation control and applies the new control algorithms to quadrotor unmanned air vehicles. First, this dissertation presents a formation control algorithm for double-integrator agents, where the formation is time varying and the agents’ controls satisfy a priori bounds (e.g., the controls accommodate actuator saturation). The main analytic results provide sufficient conditions such that all agents converge to the desired time-varying relative positions with one another and the leader, and have a priori bounded controls (if applicable). We also present results from rotorcraft experiments that demonstrate the algorithm with time-varying formations and bounded controls. …

On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae

Electrical and Computer Engineering Faculty Publications

Advances in machine learning technologies in recent years have facilitated developments in autonomous robotic systems. Designing these autonomous systems typically requires manually specified models of the robotic system and world when using classical control-based strategies, or time consuming and computationally expensive data-driven training when using learning-based strategies. Combination of classical control and learning-based strategies may mitigate both requirements. However, the performance of the combined control system is not obvious given that there are two separate controllers. This paper focuses on one such combination, which uses gravity-compensation together with reinforcement learning (RL). We present a study of the effects of gravity …

Toward Intelligent Welding By Building Its Digital Twin, Qiyue Wang

Theses and Dissertations--Electrical and Computer Engineering

To meet the increasing requirements for production on individualization, efficiency and quality, traditional manufacturing processes are evolving to smart manufacturing with the support from the information technology advancements including cyber-physical systems (CPS), Internet of Things (IoT), big industrial data, and artificial intelligence (AI). The pre-requirement for integrating with these advanced information technologies is to digitalize manufacturing processes such that they can be analyzed, controlled, and interacted with other digitalized components. Digital twin is developed as a general framework to do that by building the digital replicas for the physical entities. This work takes welding manufacturing as the case study to …

Autonomous Quadrotor Collision Avoidance And Destination Seeking In A Gps-Denied Environment, Thomas C. Kirven

Theses and Dissertations--Mechanical Engineering

This thesis presents a real-time autonomous guidance and control method for a quadrotor in a GPS-denied environment. The quadrotor autonomously seeks a destination while it avoids obstacles whose shape and position are initially unknown. We implement the obstacle avoidance and destination seeking methods using off-the-shelf sensors, including a vision-sensing camera. The vision-sensing camera detects the positions of points on the surface of obstacles. We use this obstacle position data and a potential-field method to generate velocity commands. We present a backstepping controller that uses the velocity commands to generate the quadrotor's control inputs. In indoor experiments, we demonstrate that the …

Virtualized Welding Based Learning Of Human Welder Behaviors For Intelligent Robotic Welding, Yukang Liu

Theses and Dissertations--Electrical and Computer Engineering

Combining human welder (with intelligence and sensing versatility) and automated welding robots (with precision and consistency) can lead to next generation intelligent welding systems. In this dissertation intelligent welding robots are developed by process modeling / control method and learning the human welder behavior.

Weld penetration and 3D weld pool surface are first accurately controlled for an automated Gas Tungsten Arc Welding (GTAW) machine. Closed-form model predictive control (MPC) algorithm is derived for real-time welding applications. Skilled welder response to 3D weld pool surface by adjusting the welding current is then modeled using Adaptive Neuro-Fuzzy Inference System (ANFIS), and compared …