Localisation of humans, objects and robots interacting on load-sensing floors

Mihai Andries 1, 2 Olivier Simonin 3, 4 François Charpillet 1
1 LARSEN - Lifelong Autonomy and interaction skills for Robots in a Sensing ENvironment
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
4 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
CITI - CITI Centre of Innovation in Telecommunications and Integration of services, Inria Grenoble - Rhône-Alpes
Abstract : Localisation, tracking and recognition of objects and humans are basic tasks that are of high value in applications of ambient intelligence. Sensing floors were introduced to address these tasks in a non-intrusive way. To recognize the humans moving on the floor, they are usually first localized, and then a set of gait features are extracted (stride length, cadence, pressure profile over a footstep). However, recognition generally fails when several people stand or walk together, preventing successful tracking. This paper presents a detection, tracking and recognition technique which uses objects' weight. It continues working even when tracking individual persons becomes impossible. Inspired by computer vision, this technique processes the floor pressure-image by segmenting the blobs containing objects, tracking them, and recognizing their contents through a mix of inference and combinatorial search. The result lists the probabilities of assignments of known objects to observed blobs. The concept was successfully validated in daily life activity scenarii, involving multi-object tracking and recognition on low resolution sensors, crossing of user trajectories, and weight ambiguity. This technique can be used to provide a probabilistic input for multi-modal object tracking and recognition systems.
Complete list of metadatas

https://hal.inria.fr/hal-01196042
Contributor : Mihai Andries <>
Submitted on : Wednesday, September 9, 2015 - 3:18:36 AM
Last modification on : Tuesday, December 18, 2018 - 4:40:22 PM
Long-term archiving on : Monday, December 28, 2015 - 10:55:34 PM

File

article.pdf
Files produced by the author(s)

Licence


Copyright

Identifiers

  • HAL Id : hal-01196042, version 1

Citation

Mihai Andries, Olivier Simonin, François Charpillet. Localisation of humans, objects and robots interacting on load-sensing floors. 2015. ⟨hal-01196042v1⟩

Share

Metrics

Record views

54

Files downloads

53