Abstract
Ever increasing autonomy of machines and the need to interact with them creates challenges to ensure safe operation. Recent technical and commercial interest in increasing autonomy of vehicles has led to the integration of more sensors and actuators inside the vehicle, making them more like robots. For interaction with semi-autonomous cars, the use of these sensors could help to create new safety mechanisms. This work explores the concept of using motion tracking (i.e. skeletal tracking) data gathered from the driver whilst driving to learn to classify the manoeuvre being performed. A kernel-based classifier is trained with empirically selected features based on data gathered from a Kinect V2 sensor in a controlled environment. This method shows that skeletal tracking data can be used in a driving scenario to classify manoeuvres and sets a background for further work.
Original language | English |
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Title of host publication | Towards Autonomous Robotic Systems |
Subtitle of host publication | 18th Annual Conference, TAROS 2017, Guildford, UK, July 19–21, 2017, Proceedings |
Publisher | Springer London |
Pages | 475-483 |
Number of pages | 9 |
ISBN (Electronic) | 9783319641072 |
ISBN (Print) | 9783319641065 |
DOIs | |
Publication status | Published - 20 Jul 2017 |
Event | 18th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2017 - Guildford, United Kingdom Duration: 19 Jul 2017 → 21 Jul 2017 |
Publication series
Name | Lecture Notes in Computer Science (Lecture notes in Artificial Intelligence) |
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Publisher | Springer |
Volume | 10454 |
ISSN (Print) | 0302-9743 |
Conference
Conference | 18th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2017 |
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Country/Territory | United Kingdom |
City | Guildford |
Period | 19/07/17 → 21/07/17 |
Bibliographical note
Best poster prize sponsored by UK-RAS NetworkResearch Groups and Themes
- Brain and Behaviour
- Cognitive Science
- Visual Perception
Keywords
- Classification
- Driver actions
- HRI
- Machine learning
- Semi-autonomous
- vehicles
- Vehicles
Fingerprint
Dive into the research topics of 'Drivers’ Manoeuvre Classification for Safe HRI'. Together they form a unique fingerprint.Prizes
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Erwin Lopez - ‘Best Poster Price’ at the TAROS 2017, 18th Towards Autonomous Robotic Systems (TAROS) Conference.
López Pulgarín, E. J. (Recipient), Leonards, U. (Recipient) & Herrmann, G. (Recipient), Jul 2017
Prize: Prizes, Medals, Awards and Grants