IMU-Based Shape Sensing of Field-Ready Vine Robots for Urban Search and Rescue

Soft, growing vine robots have shown promise for navigating confined and cluttered spaces, making them well-suited for deployment in urban search and rescue scenarios following structural collapses. These robots grow from the tip, allowing them to maneuver through narrow voids and unstable rubble without disturbing their surroundings. Localizing the tip of the robot, and thus trapped survivors, is a challenge due to underground conditions. Shape sensing is one solution to localization without requiring line-of-sight visibility or using GPS. This work presents a method for shape estimation of vine robots using inertial measurement units (IMUs) along the robot’s body. We quantified the accuracy of IMUs with and without the presence of magnetic interference. The maximum error in IMU orientation is 9° about one axis, which occurs in the presence of time-varying magnetic interference. Additionally, we conducted a drift test to determine how drift affects individual IMUs over the span of 18 minutes. Three IMUs out of 18 showed significant drift and their data was not used in shape sensing estimates. When passively steering the robot through angles ranging from 0° to 90°, we found that our newly proposed circular arc model performs comparably to a previously developed passive steering model. The maximum tip position error in this experiment for the circular arc model was 14.7%. An active steering test was conducted in which series pouch motor pressure was varied from 0-2.15 PSI. The maximum tip position error from the circular arc model in this experiment was 20.5%. Future work is recommended to improve the test setup and further test the capabilities of the system. Improving the circular arc model length estimation should improve its accuracy.