Countless underwater robots seek to monitor aquatic environments while minimizing their impact on fragile ecosystems. At mm-scales, these systems can be used in a range of waterways, from shallow streams and rivers, to larger ponds and lakes, and navigate around large obstacles or through tight spaces in coral reefs, mangroves, or pipe systems. They can also be more readily used as platforms for biological study, as small-scale robots can more easily be integrated into bench-top characterization systems to verify hydrodynamic performance. Here, we present a new robotic platform, the Daniobot, a 16.5mm body length (BL) microrobotic fish that is capable of achieving top speeds of 2.84BLs−1. At 23.8mm total length (TL), Daniobot is, to the best of our knowledge, the smallest fish-inspired robot propelled by onboard actuators. We present the design, fabrication, and assembly of this robot as well as detailed position and velocity results at varying tail amplitudes and frequencies, and compare their trends to a simple analytical model. This design uses a single PZT bimorph actuator operating at 175V, enabling future untethered experiments.

Several insect species are able to locomote across the air-water interface by leveraging surface tension to remain above the water surface. A subset of these insects, such as the stonefly and waterlily beetle, flap their wings to actively move around the two dimensional surface — a locomotion strategy referred to as interfacial flight. Here, we present an insect-scale robot, the γ-bot, inspired by these interfacial fliers. The robot is comprised of a flapping-wing vehicle that generates a thrust force parallel to the water surface, and three passive legs utilize surface tension to support the body mass and maintain contact with the air-water interface. We developed and validated a simple model to characterize the drag forces acting on the vehicle and estimate the robot’s velocity. This 112 mg robot can reach maximum velocities of 0.9 ms−1(corresponding to 15 BLs−1) and can initiate both left and right turns, demonstrating high maneuverability along the air-water interface. In addition, the robot can carry an additional 419 mg, enabling future sensing, control, and power autonomous operation.

Vision is an important component of robotic perception systems due to the rich information provided by high resolution image sensors, but computer vision algorithms can be computationally expensive and ill-suited to resource-constrained robotic systems. Here, we present a mm-scale vision system capable of performing absolute pose estimation at 16.5 FPS. This novel vision system uses a commercial-off-the-shelf sensor and microcontroller unit, as well as planar light-based landmarks in the environment to simplify feature detection. We exploit the structure of the planar pose problem to reduce algorithmic complexity and improve latency and energy consumption through software-, processor-, and hardware-in-the-loop testing. The end-to-end system consumes 49 mA of current and computes absolute pose estimates within 15 mm over a number of reference trajectories.

Robots are especially useful in cold, remote, and inhospitable environments such as polar regions and extraterrestrial settings. Due to subfreezing temperatures and limited resources in these environments, robots made of ice are particularly advantageous. In this paper we demonstrate how the solid and liquid phases of water, and transitions between these phases, can be leveraged into common robot designs for modular robots, robot arms, rovers, and soft robots. We explore how robots can utilize structural elements made of ice and exploit the phase change between ice and water to augment their capabilities. Additionally, we do a scaling analysis of ice structural elements to provide insight on their performance at different length scales and ambient temperatures.

Here we present HAMR-Jr, a 22.5mm, 320mg quadrupedal microrobot. With eight independently actuated degrees of freedom, HAMR-Jr is, to our knowledge, the most mechanically dexterous legged robot at its scale and is capable of high-speed locomotion (13.91bodylengthss-1) at a variety of stride frequencies (1-200Hz) using multiple gaits. We achieved this using a design and fabrication process that is flexible, allowing scaling with minimum changes to our workflow. We further characterized HAMR-Jr's open-loop locomotion and compared it with the larger scale HAMR-VI microrobot to demonstrate the effectiveness of scaling laws in predicting running performance.

Flapping-wing micro-aerial vehicles rely on subtle changes in the kinematics of high-frequency wing flapping to produce roll, pitch, and yaw torques. To generate yaw torque, the Harvard RoboBee changes the ratio of upstroke to downstroke speed (“split-cycling”) by applying a second harmonic to the fundamental flapping signal for each wing. However, since flapping typically occurs near resonance (for efficiency), these higher harmonics are filtered out by the transmission and actuator dynamics. Therefore, reliable yaw control authority has proven elusive. We propose a method to generate yaw torque sufficient for in-flight control by using split-cycle flapping in an “iso-lift” regime, to mitigate resonant filtering by decreasing the flapping frequency and increasing the drive voltage, which produces lift identical to typical flight conditions. We model the expected torque at iso-lift conditions and apply this method to the physical RoboBee, achieving reliable, controllable yaw torque. Finally, we demonstrate yaw control with a simple heading controller, achieving a step response with a time constant an order of magnitude faster than previous attempts.

Onboard vision sensing is a current challenge in micro-scale robotics. Small flapping-wing robots such as the RoboBee present significant constraints on power, weight, and image quality for an onboard vision sensor. Here we report the integration of a 1 × 1 × 1.7 mm camera capable of video capture in flight. Inspired by gaze stabilization in insects, we designed and fabricated a one degree of freedom mechanism attached to the top of the RoboBee that achieves output angles of -41° to +60°. We perform open-loop roll maneuvers and demonstrate initial control of the gaze angle during flight. This represents the first use of a camera in free flight at this scale.

Here we present a suite of theoretical, computational, and experimental studies culminating in the first aerial and aquatic capable insect-scale robot. We develop a computational fluid dynamics (CFD) simulation to model fluid-wing interaction in air and water. From CFD and a system dynamics analysis we predict that a multi-modal flapping strategy will enable locomotion in both air and water for a single device. We validate the CFD predictions by running at-scale, robotic wing-flapping experiments. Finally, we demonstrate for the first time a flying and swimming capable flapping-wing insect-like robot.

The Harvard RoboBee was the first fly-sized vehicle to lift its own weight. This vehicle has previously demonstrated controlled flight maneuvers, but this required an array of external cameras to precisely track its trajectory. Developing flight-worthy sensors to eliminate the need for external motion capture is an area of active study. In this paper, we consider an onboard analog magnetometer. We show that the sensor meets the size, weight, and power requirements for the RoboBee and can provide feedback on angular position for pitch and yaw angle control. We show that this sensor can provide an accurate angle reading despite proximity to the piezoelectric actuators of this vehicle. This is likely because the actuators are driven by electrostatic forces rather than the electromagnetic forces that drive the electric motors of larger aircraft. This sensor provided sufficient bandwidth to enable rapid pitch angle maneuvers within 200ms on a RoboBee constrained to rotate only about its pitch axis. We also show it operating in a feedback loop to control heading angle, the first demonstration of controlling yaw orientation at this scale.