Reliable systems for micro aerial vehicles - Design approach -

Reliable systems for micro aerial vehicles — Design approach


Editor's Note: Embedded designers must contend with a host of challenges in creating systems for harsh environments. Harsh environments present unique characteristics not only in terms of temperature extremes but also in areas including availability, security, very limited power budget, and more. In Rugged Embedded Systems, the authors present a series of papers by experts in each of the areas that can present unusually demanding requirements. A separate excerpt of the book addresses fundamental concerns in reliability and system resiliency.

Elsevier is offering this and other engineering books at a 30% discount. To use this discount, click here and use code ENGIN317 during checkout.

Adapted from Rugged Embedded Systems, Computing in Harsh Environments, by Augusto Vega. Pradip Bose, Alper Buyuktosunoglu.

CHAPTER 7. Reliable electrical systems for micro aerial vehicles and insect-scale robots: Challenges and progress (Cont.)
By X. Zhang, Washington University, St. Louis, MO, United States



Our intrepid pursuit to build an insect-scale aerial robot is driven with a mission to address a global crisis—the decline of pollinator populations in nature. Bees and other animal pollinators are responsible for the pollination of 60–80% of the world’s flowering plants and 35% of crop production, and hence the continuing decline could cost the global economy more than 200 billion dollars and spell devastating effect on human nutrition that is beyond the measure of monetary values. To these days, the exact cause of the decline remains to be determined, but its disastrous consequence calls for awareness and actions.

While the near-term remedy to this problem will certainly have to come out of the toolbox of entomologists, ecologists, and environmental scientists, as engineers and technologists, we would like to approach it with a longer-term out-of-the-box proposal by looking at the feasibility of building artificial robotic pollinators at the insect scale. We consider it a moonshot idea whose merits lie mostly in the creativity it spurs and the discovery it enables rather than its immediate practicality. It is against this backdrop that we, a team of investigators from Harvard University’s John A. Paulson School of Engineering and Applied Sciences and Department of Organismic and Evolutionary Biology and Northeastern University’s Department of Biology, conceived the project of RoboBee.


It is no coincidence that we look to nature for inspiration to build tiny autonomous flying apparatus. As we mentioned earlier in the chapter, larger-scale man-made aerial vehicles can take advantage of passive stability that is associated with a large Reynolds number, whereas smaller-sized MAVs commonly employ unsteady mechanisms such as wing flapping to sustain flight. Insects are among the most agile flying creatures on Earth, and we probably have all experienced this first hand at failed attempts to swat an evasively maneuvering fly or mosquito.

Since no existing vehicles have been demonstrated before to achieve comparable maneuverability at the insect scale, we modeled the form and functionality of RoboBee directly after the morphology of Diptera (flies), because Dipteran flight has been well-studied and documented in the past [6].


3.3.1 Fabrication

RoboBee requires mechanical components with feature sizes between micrometers and centimeters that fall between the gap of conventional machining and assembly methods and MEMS fabrication. To tackle this problem, the mechanical experts on our team developed a design and manufacturing methodology called “smart composite microstructure” (SCM), which stacks different material layers together with adhesives and applies laser-micromachining and lamination to bring them into desired shape. We are able to employ this monolithic planar process to manufacture all the electromechanical elements of the robotic fly, including flight muscles, thorax, skeleton, and wings. High stiffness-to-weight-ratio carbon fiber-reinforced composites are used for the structural elements, while polyimide film flexure hinges are used for articulation to emulate low-friction revolute joints.

3.3.2 Actuation

Now that we are able to reliably and efficiently fabricate the body of the flying robot with the SCM method, the next step is to determine the actuation scheme. Due to the lack of passive stability mechanism and the unfavorable scaling of transducers at small scale, flapping-wing flight can be quite costly energetically. After surveying [7] a variety of actuation technologies, we have identified piezoelectric ceramics technology as the most promising candidate for delivering oscillatory power to the robot, instead of rotary electromagnetic motors that are prevalent in larger classes of flying vehicles.

RoboBee’s flight muscles consist of voltage-driven piezoelectric bimorphs that generate bidirectional forces. A four-bar linkage acts as a lever arm to amplify the small displacement of the piezoelectric flight muscle. The complex flapping motion of the flies has been simplified in our implementation of the robot by using passive compliant flexures to regulate the pitch rotation. This is sufficient to mimic the wing kinematics in insect flight and generate downward propulsive force over a full stroke cycle.

Efficient actuation of the wings is achieved by exciting the piezoelectric bimorphs with sinusoidal waveforms near the resonant frequency of the coupled muscle-thorax-wing system. The thrust is modulated through amplitude modulation of the sinusoidal waveform, and a dual-actuator design is selected to independently drive each individual wing. It is worth mentioning that although the frequency of the drive waveform is modestly around 100 Hz, its amplitude can be as high as 300 V, which calls for novel power electronics architecture.

3.3.3 Maneuver

Equipped with the independently controlled dual-actuator wings, RoboBee is able to enjoy three-rotational degrees of freedom in its aerial maneuvers. Roll torque is generated by flapping one wing with larger stroke amplitude than the other, inducing differential thrust force; Pitch torque is generated by moving the mean stroke angle of both wings forward or backward to offset the thrust vector away from the center of mass, mimicking the method observed in Drosophila (fruit fly); Yaw torque is generated by cyclically modulating stroke velocity in a “split-cycle” scheme to induce an imbalanced drag force per stroke cycle.

Modulation of the thrust force and three body torques (roll, pitch, and, yaw) allows the robot to be controllable in unconstrained flight, and based on the desired wing movements, we can derive the corresponding drive signal waveforms to be generated by the power electronics. The next question is how to achieve stable flight.

3.3.4 Sensing and control

Since the dynamics of our insect-scale vehicle are fast and unstable, an active control strategy is implemented. As an initial start point, the sensing, and controller computation is performed off-board. The state of the robotic fly is sensed by an external array of motion-capture cameras. Retroreflective tracking markers are put on the RoboBee body to estimate position and orientation from the images. Desktop computers running Matlab are used to process the position and orientation information and control the bench-top signal generator and power amplifier to generate the power and control signals. A wire tether consisting of four bundled, 51-gauge copper wire is connected to the robot to send the power and control signals. Successful demonstration of unconstrained stable hovering and basic controlled flight maneuvers has been performed using this off-board configuration.

RoboBee’s tethered flight with off-board sensing and control gives us the confidence to take the next leap towards an autonomous flight with fully on-board components. However, it is by no means a straightforward migration from off-board components to on-board because the bulk size and power consumption of the off board solution simply could not fit onto the bee-sized robot. We have to rethink and redesign the entire sensing and control scheme.

Once again the inspiration comes from nature. Among all the sensory modalities natural insects employ in flight control, visual stimuli are essential for maintaining stability and avoiding obstacles. In unidirectional flight, insects use optical flow to navigate. It is the visual motion of objects, surfaces, and edges in a scene caused by the relative motion between the observer and the scene. To achieve light-weight on-board vision sensing, we select an optical flow sensor, designed, and fabricated by Centeye, as the “eyes” for RoboBee. It is used to provide the position information to the flight controller [8]. In addition to the vision sensor, an inertial measurement unit (IMU) chip is integrated to supplement the optical flow data with accelerometer and gyro scope readings. Experiments have shown that IMU enabled upright stability using the RoboBee platform [9]. With the sensors in place, we turn our attention now to the miniaturization of the central microprocessor and the piezoelectric driver system, which will be the main focus of this chapter. The goal is to pack the same computation performance and power conversion function of the bench-top equipment into a highly-integrated chip module.


We are at the final stage of assembling the on-board sensing and control system to demonstrate autonomous flight in RoboBee. It represents the culmination of years of engineering and development efforts on this research project that led to one of the world’s first functioning prototypes of an insect-scale aerial vehicle with fully on-board sensing and control.

Obviously, many future improvements of the current system are cut out for us. For example, advances in small, high-energy-density power sources could significantly increase the duration of the flight time; low power reliable bee-to-bee and bee-to-hive communication module could greatly facilitate coordination at the colony-level; and implementation of higher-level control will enable the robot to perform more sophisticated tasks and deliver more useful functionalities in general.

With this crucial proof-of-concept step, we are now closer to realizing the promising potentials of miniature aerial vehicles, such as for applications in reconnaissance, hazardous environment exploration, search-and-rescue, and assisted agriculture as our initial purpose in conceiving the RoboBee project. The ultimate goal is to use swarms of these small, agile, and potentially disposable robots for these applications to achieve better coverage of the mission and enhanced robustness to robot failure, as compared to larger, more complex individual robots.

Finally, it is worth pointing out that the endeavor to build insect-scale robots stretches well beyond the accomplishment of applicability. The greater impact of this line of work is to provide a set of new tools and methodologies for open scientific questions on flight mechanics and control strategies at the insect scale and the motivating technological context and challenge to spark ideas and drive creativity.

The next installment from this chapter describes the design of the BrainSoC, which serves as the RoboBee electronic control subsystem.

Reprinted with permission from Elsevier/Morgan Kaufmann, Copyright © 2016

Professor Zhang joined the faculty at Washington University in St. Louis in 2015. Previously, she was a postdoctoral fellow in computer science at Harvard University, where she worked on the RoboBee BrainSoC and energy-efficient computing projects. She has worked as a graduate research assistant at Cornell University studying variability-tolerant circuits. Zhang earned a doctorate in electrical and computer engineering at Cornell University in 2012. She earned a bachelor’s degree in electrical engineering at Tsinghua University in Beijing in 2006.

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