Abstract-Flapping-wing robots typically include numerous nonlinear elements, such as nonlinear geometric and aerodynamic components. For an insect-sized flapping-wing micro air vehicle (FWMAV), we show that a linearized model is sufficient to predict system behavior with reasonable accuracy over a large operating range, not just locally around the linearization state. The theoretical model is verified against an identified model from a prototype robotic fly and implications for vehicle design are discussed.
Motivated by the need for torque sensing in the µNm range for experiments with insect-sized flapping-wing robots, we present the design, fabrication and testing of a custom single-axis torque sensor. The micorobots in question are too large for MEMS force/torque sensors used for smaller live insects such as fruit flies, but too small to produce torques within the dynamic range of commercially available force/torque sensors. Our sensor consists of laser-machined Invar sheets that are assembled into a three dimensional beam. A capacitive displacement sensor is used to measure displacement of a target plate when the beam rotates, and the output voltage is correlated to applied torque. Sensor bandwidth, range, and resolution are designed to match the criteria of the robotic fly experiments while remaining insensitive to off-axis loads. We present a final sensor design with a range of ±130µNm, a resolution of 4.5nNm, and bandwidth of 1kHz. I. INTRODUCTIONWithin the last decade, multiple biologically-inspired robots have been developed at the insect scale, much smaller than traditional macro-scale robots yet larger than truly microscopic technologies such as MEMS (for examples see [1], [2]). The unique scale and operating conditions of these robots mean commercially available experimental tools may not always be sufficient and thus custom designs are required. For example, the robotic fly presented in [1] required the development of a two-axis force sensor to empirically determine lift and drag forces generated by the flapping wings [3].More recent work on the robotic fly includes the use of asymmetric wing flapping motions to generate net body torques [4], where the magnitude of predicted torques is on the order of 1-10µNm. These values were obtained using a quasi-steady blade-element aerodynamic model [5] to predict aerodynamic forces and resulting body torques. To the authors' knowledge, even the most sensitive commercially available torque transducers fall short of the range, resolution and bandwidth demanded for microrobotic experiments. For instance, the Nano17 by ATI Industrial Automation (Apex, NC) offers a torque measurement capacity of 120mNm and a resolution near 16µNm, which is an order of magnitude too large for our application.There have been several published works on the development and manufacture of custom torque sensors for a variety
Abstract-The design of autonomous robots involves the development of many complex, interdependent components, including the mechanical body and its associated actuators, sensors, and algorithms to handle sensor processing, control, and high-level task planning. For the design of a robotic bee (RoboBee) it is necessary to optimize across the design space for minimum weight and power consumption to increase flight time; however, the design space of a single component is large, the interconnectedness and tradeoffs across components must be considered, and interdisciplinary collaborations cause different component design timelines.In this work, we show how the development of a hardware in the loop (HWIL) system for a flapping wing microrobot can simplify and accelerate evaluation of a large number of design choices. Specifically, we explore the design space of the visual system including sensor hardware and associated optical flow processing. We demonstrate the utility of the HWIL system in exposing trends on system performance for optical flow algorithm, field of view, sensor resolution, and frame rate.
Switching gaits in many-legged robots can present challenges due to the combinatorial nature of the gait space. In this paper we present an intrinsically safe gait switching generator that minimizes the velocity variance of all the legs in stance, allowing for smooth acceleration in legged robots. The gait switching generator is modeled as a max-plus linear discrete event system which is translated to continuous time via a reference trajectory generator.
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