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This study focuses on designing and developing a mathematically based quadcopter rotational dynamics simulation framework for testing reinforcement learning (RL) algorithms in many flexible configurations. The design of the simulation…
Successful implementation of active learning strategies in the engineering classroom -- and in particular in certain subjects which are highly technological in nature such as, for instance, rocket engines and space propulsion -- means…
Perception modules are integral in many modern autonomous systems, but their accuracy can be subject to the vagaries of the environment. In this paper, we propose a learning-based approach that can automatically characterize the error of a…
The adoption of Uncrewed Aerial Vehicles (UAVs) for last-mile deliveries will affect the energy productivity of package delivery and require new methods to understand the associated energy consumption and greenhouse gas (GHG) emissions.…
This paper presents a new framework to use images as the inputs for the controller to have autonomous flight, considering the noisy indoor environment and uncertainties. A new Proportional-Integral-Derivative-Accelerated (PIDA) control with…
Robotic research over the last decades have lead us to different architectures to automatically synthesise discrete event controllers and implement these motion and task plans in real-world robot scenarios. However, these architectures…
With inspiration from arthropods' exoskeletons, we designed a simple, easily manufactured, semi-rigid structure with flexible joints that can passively damp impact energy. This exoskeleton fuses the protective shell to the main robot…
Although robotics courses are well established in higher education, the courses often focus on theory and sometimes lack the systematic coverage of the techniques involved in developing, deploying, and applying software to real hardware.…
Nano-UAV teams offer great agility yet face severe navigation challenges due to constrained onboard sensing, communication, and computation. Existing approaches rely on high-resolution vision or compute-intensive planners, rendering them…
Feedback is critical in education. This Innovative Practice Full Paper reports lessons learned from improving the quality of feedback in a semi-capstone software engineering course, with particular focus on how to deliver productive…
Aggressive time-optimal control of quadcopters poses a significant challenge in the field of robotics. The state-of-the-art approach leverages reinforcement learning (RL) to train optimal neural policies. However, a critical hurdle is the…
A novel autonomous chunk-based aerial additive manufacturing framework is presented, supported with experimental demonstration advancing aerial 3D printing. An optimization-based decomposition algorithm transforms structures into…
We consider a quadcopter operating in a turbulent windy environment. The turbulent environment may be imposed on a quadcopter by structures, landscapes, terrains and most importantly by the unique physical phenomena in the lower atmosphere.…
This paper addresses the problem of guiding a quadrotor through a predefined sequence of waypoints in cluttered environments, aiming to minimize the flight time while avoiding collisions. Previous approaches either suffer from prolonged…
This paper describes the process and challenges behind the design and development of a micro-gravity enabling aerial robot. The vehicle, designed to provide at minimum 4 seconds of micro-gravity at an accuracy of .001 g's, is designed with…
Lowering the barriers to computer programming requires understanding how to scaffold learning. Parsons problems, which require learners to drag-and-drop blocks of code into the correct order and indentation, are proving to be beneficial for…
Designing robust controllers for precise trajectory tracking with quadrotors is challenging due to nonlinear dynamics and underactuation, and becomes harder with flexible cable-suspended payloads that add degrees of freedom and hybrid…
Obstacle avoidance is a fundamental vision-based task essential for enabling quadrotors to perform advanced applications. When planning the trajectory, existing approaches both on optimization and learning typically regard quadrotor as a…
This paper develops and experimentally evaluates a navigation function for quadrotor formation flight that is resilient to abrupt quadrotor failures and other obstacles. The navigation function is based on modeling healthy quadrotors as…
Traditional learning approaches proposed for controlling quadrotors or helicopters have focused on improving performance for specific trajectories by iteratively improving upon a nominal controller, for example learning from demonstrations,…