Tactile-Based Exploration, Mapping, and Navigation With Collision-Resilient Aerial Vehicles

This article introduces XPLORER, a passive deformable aerial vehicle with a spring-augmented chassis and proprioceptive state awareness, designed to endure collisions and maintain smooth contact with the environment. A fast-converging external force estimation algorithm for XPLORER is designed to leverage onboard sensors and proprioceptive data for contact detection. Using this force information, four motion primitives are proposed, including three novel tactile-based primitives—tactile-traversal, tactile-turning, and ricocheting—to aid XPLORER in navigating unknown environments. These primitives are synthesized autonomously in real time to enable efficient exploration and navigation by leveraging collisions and contacts. Experimental results demonstrate the effectiveness of our approach, highlighting the potential of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">passive</i> deformable aerial vehicles for contact-rich real-world tasks, such as nondestructive inspection, surveillance and mapping, even pursuit/evasion.

Authors

Institutions

Publication Details

Journal
IEEE/ASME Transactions on Mechatronics
Published
2025-06-16
DOI
https://doi.org/10.1109/tmech.2025.3572888
Citations
3
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
3.83

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tactile-Based Exploration, Mapping, and Navigation With Collision-Resilient Aerial Vehicles

Karishma Patnaik, Aravind Adhith Pandian Saravanakumaran, Wenlong Zhang
3 citations
IEEE/ASME Transactions on Mechatronics
Robotic Path Planning Algorithms
3.83
article

Tactile-Based Exploration, Mapping, and Navigation With Collision-Resilient Aerial Vehicles

Karishma Patnaik, Aravind Adhith Pandian Saravanakumaran, Wenlong Zhang
article en
3 citations

Abstract

This article introduces XPLORER, a passive deformable aerial vehicle with a spring-augmented chassis and proprioceptive state awareness, designed to endure collisions and maintain smooth contact with the environment. A fast-converging external force estimation algorithm for XPLORER is designed to leverage onboard sensors and proprioceptive data for contact detection. Using this force information, four motion primitives are proposed, including three novel tactile-based primitives—tactile-traversal, tactile-turning, and ricocheting—to aid XPLORER in navigating unknown environments. These primitives are synthesized autonomously in real time to enable efficient exploration and navigation by leveraging collisions and contacts. Experimental results demonstrate the effectiveness of our approach, highlighting the potential of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">passive</i> deformable aerial vehicles for contact-rich real-world tasks, such as nondestructive inspection, surveillance and mapping, even pursuit/evasion.

IEEE/ASME Transactions on MechatronicsVol. 30(4)
Arizona State University (US)
National Science Foundation, National Aeronautics and Space Administration
Climate action
Openalex Percentile: Top 6%
Robotic Path Planning Algorithms
3.83
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.