Tactile Aerial Grasping via High-Resolution Touch on Drones
M.A. Elahi (TU Delft - Aerospace Engineering)
Salua Hamaza – Mentor (TU Delft - Control & Simulation)
E.J.J. Smeur – Graduation committee member (TU Delft - Control & Simulation)
Alessandro Bombelli – Graduation committee member (TU Delft - Operations & Environment)
A. Bredenbeck – Mentor (TU Delft - Control & Simulation)
M.B.J. Brummelhuis – Mentor (TU Delft - Control & Simulation)
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Abstract
This thesis presents the design, development, and experimental validation of a perching drone equipped with an underactuated robotic gripper and tactile sensing for grasping onto structures. Perching extends drone endurance for applications such as long-term monitoring, while tactile sensing enables precise alignment when visual data is unreliable. A control strategy combining position-based control with tactile feedback is implemented using DIGIT tactile sensors for contact-aware adjustments. Two per-pixel inference models convert RGB images into tactile information: a sensitive contact model for binary contact detection and a depth reconstruction model that estimates surface normals, which is then used to determine the contact surface orientation. After outlier filtering, the depth model achieves a mean absolute error of 5.32° in orientation estimation. Experiments demonstrate reliable grasping with up to 12 cm of position error and successful correction of both position and orientation using simulated tactile input. These results highlight the potential of tactile-based strategies for robust aerial manipulation in uncertain environments.