Insect-scale flying robots are currently unable to carry the power source and sensor suite required for autonomous operation. To overcome this challenge, we developed and experimentally verified a non-linear damping model of actuation-limited flapping-wing vehicles with passively rotating wing hinges. In agreement with studies on the wing dynamics of honey bees, we found that the optimal angle of the passive wing hinge in mid-stroke is about 70 ° rather than 45-50 ° as previously assumed. We further identified a narrow actuation force window in which the occurrence of a sharp resonance can be used to achieve both higher lift and efficiency. The findings from our model informed design changes to the Harvard Dual-Actuator Robobee, which resulted in a 130% increase in mean lift from ~140mg to 320mg (with a vehicle mass increase of only 5 - 8%), along with a corresponding expected payload increase of 330 - 470% (30 - 40mg to 170mg). The power consumption only increased by ~55%, making the new prototype 50% more efficient at lift production. Our model provides a greater understanding of the dynamics of this complex system, and the resulting lift and efficiency improvements are expected to bring insect-scale flying robots closer to autonomy.

This paper presents a biologically inspired, 3.2g untethered vehicle capable of both active (flapping) and passive (gliding) flight. We discuss the overall vehicle design, as well as its validation with thrust data from benchtop testing, simulation, and flight test results. The vehicle has one pair of flapping wings for thrust generation, making it a good analogue for insects of the same scale. Flight energetics and control can be thoroughly explored through the array of simulation and testing that have been implemented. Integrated electronics provide wireless communication, sensing, and basic open-loop flight control, making flight test iteration fast and providing additional dynamics data. All of the testing setups and the physical vehicle working together have created a robust development environment for future iterations on the vehicle. The successful flight of the vehicle, including the data collection from onboard sensors and an external motion capture arena, show that this platform is ideal to study flight energetics and control schemes at an insect scale.

Full autonomy remains a challenge for miniature robotic platforms due to mass and size requirements of on-board power and control electronics. This paper presents a solution to these challenges with a 2.3g autonomous legged robot. An off-the-shelf optical mouse sensor is adapted for use on the Harvard Ambulatory Microrobot (HAMR) by reducing the sensor weight by 36% and achieving a position error below 11% when suspended 3mm above a cardstock surface. The position data is combined with data from a gyroscope for feedback control of both position and orientation. A microcontroller processes the sensor data and commands a controlled gait to HAMR that is powered by a battery, a boost converter and high voltage drive electronics. Solar cells are used as an alternative source providing enough power for autonomous operation of the robot. The resulting deviation for a controlled straight-line walk using both sensors to minimize lateral deviation and angular error is only 4.6%, compared to an error of 31% in an uncontrolled, straight-line walk.

This paper presents a non-linear, dynamic model of the flexure-based transmission in the Harvard Ambulatory Microrobot (HAMR). The model is derived from first principles and has led to a more comprehensive understanding of the components in this transmission. In particular, an empirical model of the dynamic properties of the compliant Kapton flexures is developed and verified against theoretical results from beam and vibration theory. Furthermore, the fabrication of the piezoelectric bending actuators that drive the transmission is improved to match theoretical performance predictions. The transmission model is validated against experimental data taken on HAMR for the quasi-static (1–10 Hz) operating mode, and is used to redesign the transmission for improved performance in this regime. The model based redesign results in a 266% increase in the work done by the foot when compared to a previous version of HAMR. This leads to a payload capacity of 2.9g, which is ∼ 2× the robot's mass and a 114% increase. Finally, the model is validated in the dynamic regime (40–150 Hz) and the merits of a second order linear approximation are discussed.