Roll, Pitch and Yaw Torque Control for a Robotic Bee

In the last decade, the robotics community has pushed to develop increasingly small, autonomous flapping-wing robotic vehicles for a variety of civilian and military applications. The miniaturization of these vehicles has pushed the boundaries of technology in many areas, including electronics, artificial intelligence, and mechanics; as well as our understanding of biology. In particular, at the insect scale, fabrication, actuation, and flight control of a flapping-wing robot become especially challenging. This thesis addresses these challenges in the context of the “RoboBee” project, which has the goal of creating an autonomous swarm of at-scale robotic bees. A 100mg robot with a 3cm wingspan capable of generating roll, pitch and yaw torques in the range of $\pm 1\mu Nm$ by using a large, central power actuator to flap the wings and smaller control actuators to steer is presented. A dynamic model is used to predict torque generation capabilities, and custom instrumentation is developed to measure and characterize the vehicle’s control torques. Finally, controlled flight experiments are presented, and the vehicle is capable of maintaining a stable pitch and roll attitude during ascending vertical flight. This is the first successful controlled flight of a truly insect-scale flapping-wing robot.Engineering and Applied Science

IMPROVED PREDICTION OF FLAPPING WING AERIAL VEHICLE PERFORMANCE THROUGH COMPONENT INTERACTION MODELING

Flapping wing aerial vehicles offer the promise of versatile performance, however prediction of flapping wing aerial vehicle performance is a challenging task because of complex interconnectedness in vehicle functionality. To address this challenge, performance is estimated by using component-level modeling as a foundation. Experimental characterization of the drive motors, battery, and wings is performed to identify important functional characteristics and enable selection of appropriate modeling techniques. Component-level models are then generated that capture the performance of each vehicle component. Validation of each component-level model shows where errors are eliminated by capturing important dynamic functionality. System-level modeling is then performed by creating linkages between component-level models that have already been individually validated through experimental testing, leading to real-world functional constraints that are realized and correctly modeled at the system level. The result of this methodology is a system-level performance prediction that offers the ability to explore the effects of changing vehicle components as well as changing functional properties, while maintaining computational tractability. Simulated results are compared to experimental flight test data collected with an instrumented flapping wing aerial vehicle, and are shown to offer good accuracy in estimation of system-level performance properties

Feature Papers of Drones - Volume I

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 1–8 are devoted to the developments of drone design, where new concepts and modeling strategies as well as effective designs that improve drone stability and autonomy are introduced. Articles 9–16 focus on the communication aspects of drones as effective strategies for smooth deployment and efficient functioning are required. Therefore, several developments that aim to optimize performance and security are presented. In this regard, one of the most directly related topics is drone swarms, not only in terms of communication but also human-swarm interaction and their applications for science missions, surveillance, and disaster rescue operations. To conclude with the volume I related to drone improvements, articles 17–23 discusses the advancements associated with autonomous navigation, obstacle avoidance, and enhanced flight plannin