Tactile Odometry in Aerial Physical Interaction

Aerial robots are well-established technologies in environments characterized by reliable GNSS signals and favorable conditions for navigation based on cameras or LiDARs. However, their robustness is significantly challenged whenever ambient lighting is insufficient, GNSS signals are blocked, and range measurements are corrupted, for example, in underground, dark, or foggy environments. There, conventional navigation methods solely based on computer vision are very limited. This work proposes a completely novel approach to Aerial Tactile Odometry for pose estimation of aerial robots exploiting contact to precisely determine the system’s pose. By employing a compliant end-effector design with onboard tactile information by means of a trackball, we infer the complete UAV’s pose with respect to the environment, and the path traveled during contact. Through a large set of experiments, the proposed method shows centimeter-level accuracy for various relative orientations between the environment and the robot as well as for different trajectories. Akin to conventional dead-reckoning odometry methods in wheeled robotics, this method provides a valuable additional source of pose estimation, increasing the robustness of aerial robots – especially aerial manipulators – in the real world.

Authors

Institutions

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802497
Citations
2
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.66
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tactile Odometry in Aerial Physical Interaction

Salua Hamaza, Micha Schuster, Michael Beitelschmidt, Anton Bredenbeck
2 citations
Robot Manipulation and Learning
0.66
article

Tactile Odometry in Aerial Physical Interaction

Salua Hamaza, Micha Schuster, Michael Beitelschmidt, Anton Bredenbeck
article en
2 citations

Abstract

Aerial robots are well-established technologies in environments characterized by reliable GNSS signals and favorable conditions for navigation based on cameras or LiDARs. However, their robustness is significantly challenged whenever ambient lighting is insufficient, GNSS signals are blocked, and range measurements are corrupted, for example, in underground, dark, or foggy environments. There, conventional navigation methods solely based on computer vision are very limited. This work proposes a completely novel approach to Aerial Tactile Odometry for pose estimation of aerial robots exploiting contact to precisely determine the system’s pose. By employing a compliant end-effector design with onboard tactile information by means of a trackball, we infer the complete UAV’s pose with respect to the environment, and the path traveled during contact. Through a large set of experiments, the proposed method shows centimeter-level accuracy for various relative orientations between the environment and the robot as well as for different trajectories. Akin to conventional dead-reckoning odometry methods in wheeled robotics, this method provides a valuable additional source of pose estimation, increasing the robustness of aerial robots – especially aerial manipulators – in the real world.

Technische Universität Dresden (DE), Delft University of Technology (NL)
Openalex Percentile: Top 28%
Robot Manipulation and Learning
0.66
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.