Research ArticleANIMAL ROBOTS

A biomimetic robotic platform to study flight specializations of bats

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Science Robotics  01 Feb 2017:
Vol. 2, Issue 3, eaal2505
DOI: 10.1126/scirobotics.aal2505
  • Fig. 1 Functional groups in bat (photo courtesy of A. D. Rummel and S. Swartz, the Aeromechanics and Evolutionary Morphology Laboratory, Brown University).

    Enumerated bat joint angles and functional groups are depicted; using these groups makes it possible to categorize the sophisticated movements of the limbs during flight and to extract dominant DOFs and incorporate them in the flight kinematics of B2. The selected DOFs are coupled by a series of mechanical and virtual constraints.

  • Fig. 2 Bat Bot.

    (A) B2 is self-sustained and self-contained; it has an onboard computer and several sensors for performing autonomous navigation in its environment. The computing, sensing, and power electronics, which are accommodated within B2, are custom-made and yield a fully self-sustained system despite weight and size restrictions. The computing unit, or main control board (MCB), hosts a microprocessor. While the navigation-and-control algorithm runs on the MCB in real time, a data acquisition unit acquires sensor data and commands the micro actuators. The sensing electronics, which are circuit boards custom-designed to achieve the smallest size possible, interface with the sensors and the MCB by collecting two kinds of measurements. First, an inertial measurement unit (IMU), which is fixed to the ribcage in such a way that the x axis points forward and the z axis points upward, reads the attitudes of the robot with respect to the inertial frame. Second, five magnetic encoders are located at the elbows, hips, and flapping joint to read the relative angles between the limbs with respect to the body. (B) Dynamic modulus analysis. Samples of membrane were mounted vertically in the dynamic modulus analyzer using tension clamps with ribbed grips to ensure that there was no slipping of the sample. Data were collected using controlled force analysis at a ramp rate of 0.05 N/min over the range 0.001 to 1.000 N. The temperature was held at 24.56°C. The estimated average modulus, ultimate tensile strength (UTS), and elongation are 0.0028 MPa, 0.81 MPa, and 439.27%, respectively. The average modulus and UTS along fiber direction are 11.33 and 17.35 MPa, respectively. (C) The custom-made silicone-based membrane and embedded carbon fibers.

  • Fig. 3 Mechanism and electronics overview.

    (A) B2’s flight mechanism and its DOFs. We introduced mechanical couplings in the armwing to synthesize a mechanism with a few DOFs. (B) The armwing retains only one actuated movement, which is a push-pull movement produced by a spindle mechanism hosted in the shoulder. (C) The leg mechanism. (D) B2’s electronics architecture. At the center, the microprocessor from STMicroelectronics communicates with several components, including an IMU from VectorNav Technologies, an SD card reader, five AS5048 Hall effect encoders, and two dual-port dc motor drivers. Two wireless communication devices, an eight-channel micro RC receiver (DSM2) and a Bluetooth device, make it possible to communicate with the host (Panel). The microprocessor has several peripherals, such as universal synchronous/asynchronous receiver/transmitter (USART), serial peripheral interface (SPI), pulse-width modulation (PWM), and secure digital input/output (SDIO). To test and deploy the controller on the platform, we used Hardware-in-the-Loop (HIL) simulation. In this method, a real-time computer is used as a virtual plant (model), and the flight controller, which is embedded on the physical microprocessor, responds to the state variables of the virtual model. In this way, the functionality of the controller is validated and debugged before being deployed on the vehicle.

  • Fig. 4 Untethered flights and controller architecture.

    (A) Snapshots of a zero-path straight flight. (B) Snapshots of a diving maneuver. (C) The main controller consists of the discrete (C1) and morphing controllers (C2). The discrete and morphing controllers are updated through sensor measurements H1 and H2 at 10 and 100 Hz, respectively. The subsystems S1, S2, and S3 are the underactuated, actuated, and aerodynamic parts [see Materials and Methods and (40)].

  • Fig. 5 The time evolution of the Euler angles roll qx, pitch qy, and yaw qz for eight flight tests is shown.

    (A and B) The roll and pitch angles converge to a bounded neighborhood of 0° despite perturbations at the launch moment. The red region represents the time envelope required for vehicle stabilization and is denoted by Δtstab. For all of the flight experiments except the first [denoted by S.F. (straight flight) and highlighted by the green region], a bank turn command was sent at a time within the blue range. Then, the roll and pitch angles start to increase, indicating the beginning of the bank turn. (C) The behavior of the yaw angle. In the red region, vehicle heading is stabilized (except flight tests 1 and 4). In the blue region, the vehicle starts to turn toward the right armwing (negative heading rate). This behavior is not seen in the straight flight.

  • Fig. 6 Armwing joint angle time evolution.

    Left and right armwing angles Embedded Image (A and B) and Embedded Image (C and D) are shown for eight flight tests. (A and C) Closeup views for the stabilization time envelope. The red region represents the joint movement during the stabilization time envelope. (B and D) After the stabilization time envelope, for all of the flight experiments except the first (highlighted with green), a bank turn command was sent at a time within the blue range.

  • Fig. 7 Leg joint angle time evolution.

    Left and right leg angles Embedded Image (A and B) and Embedded Image (C and D) are shown for eight flight tests. (A and C) Closeup views for the stabilization time envelope. (B and D) After the stabilization time envelope, the dorsal movement of the legs are applied to secure a successful belly landing. This dorsal movement can cause pitch-up artifacts, which are extremely nonlinear.

  • Fig. 8 Joint angle evolution during swooping down.

    (A) The time evolution of the Euler angles during the diving maneuver. (B) Armwing joint angles. (C) Leg joint angles. The red region indicates the stabilization time envelope; the light blue region indicates the dive time span.

Supplementary Materials

  • robotics.sciencemag.org/cgi/content/full/2/3/eaal2505/DC1

    Supplementary Text

    Fig. S1. Nonlinear model verification.

    Fig. S2. Flight speed measurements.

    Fig. S3. Motion capture system.

    Fig. S4. Wind tunnel measurements.

    Table S1. B2’s morphological details.

    Movie S1. Membrane.

    Movie S2. Articulated skeleton.

    Movie S3. Straight flights.

    Movie S4. Swoop maneuver.

    Movie S5. Banking turn maneuver.

    References (4659)

  • Supplementary Materials

    Supplementary Material for:

    A biomimetic robotic platform to study flight specializations of bats

    Alireza Ramezani, Soon-Jo Chung,* Seth Hutchinson

    *Corresponding author. Email: sjchung{at}caltech.edu

    Published 1 February 2017, Sci. Robot. 2, eaal2505 (2017)
    DOI: 10.1126/scirobotics.aal2505

    This PDF file includes:

    • Supplementary Text
    • Fig. S1. Nonlinear model verification.
    • Fig. S2. Flight speed measurements.
    • Fig. S3. Motion capture system.
    • Fig. S4. Wind tunnel measurements.
    • Table S1. B2’s morphological details.
    • Legends for movies S1 to S5
    • References (4659)

    Download PDF

    Other Supplementary Material for this manuscript includes the following:

    • Movie S1 (.mp4 format). Membrane.
    • Movie S2 (.mp4 format). Articulated skeleton.
    • Movie S3 (.mp4 format). Straight flights.
    • Movie S4 (.mp4 format). Swoop maneuver.
    • Movie S5 (.mp4 format). Banking turn maneuver.

    Files in this Data Supplement: