Simulation of a Tilt-Rotor Uav with a Cable-Driven Gripper for High-Precision Physical Interaction

Performing tasks at high altitudes can be inconvenient and unsafe for humans. Unmanned aerial vehicles (UAVs) with physical interaction capabilities are on hand to address these issues. Our previous work introduced one such UAV: a multi-rotor with a pair of tilting rotors and a novel, cable-driven, front-mounted gripper, which improved position accuracy during interaction tasks. However, the UAV could only interact with vertical surfaces, and its control performance was limited by a simple pilot-assisted position controller during interaction. This paper advances that work by developing an improved version of our UAV. The modified design includes two pairs of tilt-rotors, which can tilt simultaneously to angle the drone body, allowing interaction with non-vertical targets at specific angles. We develop a simulation package that accurately replicates our new UAV design's physical characteristics and dynamics, including the cable-driven gripper. This simulation package provides a virtual testbed for designing and evaluating advanced interaction control algorithms, minimizing the risks, costs, and time of physical prototyping. We demonstrate its utility by safely testing autonomous control strategies, including force control, in a tree-grasping scenario. We also give insights into hyperparameter selections, challenges faced, and current limitations while developing such a versatile package that involves simulating elastic components such as cables, springs, and soft finger pads. We open-source our simulation package for the community's benefit at https://tinyurl.com/ypwzje2a.

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Publication Details

Published
2025-05-14
DOI
https://doi.org/10.1109/icuas65942.2025.11007871
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Simulation of a Tilt-Rotor Uav with a Cable-Driven Gripper for High-Precision Physical Interaction

Efe Camci, Joshua Taylor, Nursultan Imanberdiyev, Y Chen
Robotic Mechanisms and Dynamics
article

Simulation of a Tilt-Rotor Uav with a Cable-Driven Gripper for High-Precision Physical Interaction

Efe Camci, Joshua Taylor, Nursultan Imanberdiyev, Y Chen
article en

Abstract

Performing tasks at high altitudes can be inconvenient and unsafe for humans. Unmanned aerial vehicles (UAVs) with physical interaction capabilities are on hand to address these issues. Our previous work introduced one such UAV: a multi-rotor with a pair of tilting rotors and a novel, cable-driven, front-mounted gripper, which improved position accuracy during interaction tasks. However, the UAV could only interact with vertical surfaces, and its control performance was limited by a simple pilot-assisted position controller during interaction. This paper advances that work by developing an improved version of our UAV. The modified design includes two pairs of tilt-rotors, which can tilt simultaneously to angle the drone body, allowing interaction with non-vertical targets at specific angles. We develop a simulation package that accurately replicates our new UAV design's physical characteristics and dynamics, including the cable-driven gripper. This simulation package provides a virtual testbed for designing and evaluating advanced interaction control algorithms, minimizing the risks, costs, and time of physical prototyping. We demonstrate its utility by safely testing autonomous control strategies, including force control, in a tree-grasping scenario. We also give insights into hyperparameter selections, challenges faced, and current limitations while developing such a versatile package that involves simulating elastic components such as cables, springs, and soft finger pads. We open-source our simulation package for the community's benefit at https://tinyurl.com/ypwzje2a.

Agency for Science, Technology and Research (SG), National University of Singapore (SG), Singapore Polytechnic (SG), Institute for Infocomm Research (SG)
National Research Foundation Singapore
Affordable and clean energy
Openalex Percentile: Top 87%
Robotic Mechanisms and Dynamics
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