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Tjaden Bridges

dblp:416/5231 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Legged, aerial and field robots · 77% Robot navigation and mapping · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
aerial robots
0.912025
Airflow Source Seeking on Small Quadrotors Using a Single Flow Sensor · ICRA 2025
Robotics › Robot navigation and mapping › target tracking
plume tracking
0.312025
Airflow Source Seeking on Small Quadrotors Using a Single Flow Sensor · ICRA 2025

Methods — techniques the papers use, named apart from their topics

flow sensor · 0.9cast and surge algorithm · 0.9
YearPublicationVenuePosition
2025 Airflow Source Seeking on Small Quadrotors Using a Single Flow Sensor
abstract
As environmental disasters happen more frequently and severely, seeking the source of pollutants or harmful particulates using plume tracking becomes even more important. Plume tracking on small quadrotors would allow these systems to operate around humans and fly in more confined spaces, but can be challenging due to poor sensitivity and long response times from gas sensors that fit on small quadrotors. In this work, we present an approach to complement chemical plume tracking with airflow source-seeking behavior using a custom flow sensor that can sense both airflow magnitude and direction on small quadrotors (< 100 g). We use this sensor to implement a modified version of the ‘Cast and Surge’ algorithm that takes advantage of flow direction sensing to find and navigate towards flow sources. A series of characterization experiments verified that the system can detect airflow while in flight and reorient the quadrotor toward the airflow. Several trials with random starting locations and orientations were used to show that our source-seeking algorithm can reliably find a flow source. This work aims to provide a foundation for future platforms that can use flow sensors in concert with other sensors to enable richer plume tracking data collection and source-seeking.
Lenworth Thomas, Tjaden Bridges, Sarah Bergbreiter
ICRA2