Flying Vines: Design, Modeling, and Control of a Soft Aerial Robotic Arm

TL;DR

The paper introduces Flying Vine, a soft aerial robotic arm that couples a small quadrotor with a growing inflated vine to achieve a large end effector workspace with minimal added mass. A data-driven dynamic model with an augmented state and a bilinear interpolation scheme handles time-varying vine length and pressure, followed by offline trajectory optimization using iLQR to generate end effector trajectories. Experimental results on a physical prototype demonstrate accurate end effector tracking across configurations, transitions as the vine grows, and a swinging maneuver, validating the framework for dynamic maneuvers with soft aerial manipulators. This work lays the groundwork for versatile aerial inspection and interaction tasks by delivering a lightweight, flexible manipulation solution integrated with a quadrotor platform.

Abstract

Aerial robotic arms aim to enable inspection and environment interaction in otherwise hard-to-reach areas from the air. However, many aerial manipulators feature bulky or heavy robot manipulators mounted to large, high-payload aerial vehicles. Instead, we propose an aerial robotic arm with low mass and a small stowed configuration called a "flying vine". The flying vine consists of a small, maneuverable quadrotor equipped with a soft, growing, inflated beam as the arm. This soft robot arm is underactuated, and positioning of the end effector is achieved by controlling the coupled quadrotor-vine dynamics. In this work, we present the flying vine design and a modeling and control framework for tracking desired end effector trajectories. The dynamic model leverages data-driven modeling methods and introduces bilinear interpolation to account for time-varying dynamic parameters. We use trajectory optimization to plan quadrotor controls that produce desired end effector motions. Experimental results on a physical prototype demonstrate that our framework enables the flying vine to perform high-speed end effector tracking, laying a foundation for performing dynamic maneuvers with soft aerial manipulators.

Figures (8)

• Figure 1: Images of the flying vine prototype in action. (a) Images from a video of the soft robot arm growing. (b) Composite image that overlays frames of a video in which the flying vine tracks a lemniscate path ($\infty$). (c) Images from a video of the flying vine "kicking" a beach ball.
• Figure 2: Close-up of the flying vine prototype. Micro air pumps are used to inflate the vine robot. The quadrotor has an onboard computer (UP Board) for processing commands and a microcontroller (Teensy LC) for executing vine robot commands. We mount reflective markers on the frame of the quadrotor and on the vine robot end effector, also referred to as the "tip mount," for use with a motion capture system (OptiTrack).
• Figure 3: Design details of the soft growing vine robot arm. The vine robot is fixed to the quadrotor via a clamp mounted to the underside of the quadrotor. The vine "grows" by rotation of the spool, which releases additional material that everts due to internal vine body pressure and gravity. Motor wires are routed along a plastic coil for passive wire management. The ends of the plastic coil are fixed to mounting plates, and the upper mounting plate is press-fit into the internal clamped base. Interlocking rollers keep the relative positioning between the internal spool and external tip mount fixed. The tip mount provides a rigid surface for mounting motion capture markers.
• Figure 4: High-level illustration of data flow for operating the flying vine.
• Figure 5: Example flying vine motion. We overlay the quadrotor position command (dotted), actual quadrotor position (dashed), and end effector position (solid) to show that there are offsets between these three signals that need to be modeled.