Skip to Main content Skip to Navigation
Theses

Decision-making algorithms for autonomous robots

Abstract : The autonomy of robots heavily relies on their ability to make decisions based on the information provided by their sensors. In this dissertation, decision-making in robotics is modeled as continuous state and action markov decision process. This choice allows modeling of uncertainty on the results of the actions chosen by the robots. The new learning algorithms proposed in this thesis focus on producing policies which can be used online at a low computational cost. They are applied to real-world problems in the RoboCup context, an international robotic competition held annually. In those problems, humanoid robots have to choose either the direction and power of kicks in order to maximize the probability of scoring a goal or the parameters of a walk engine to move towards a kickable position.
Document type :
Theses
Complete list of metadatas

Cited literature [43 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-01684198
Contributor : Abes Star :  Contact
Submitted on : Monday, January 15, 2018 - 12:07:27 PM
Last modification on : Friday, August 21, 2020 - 4:40:51 AM
Long-term archiving on: : Monday, May 7, 2018 - 12:30:43 PM

File

HOFER_LUDOVIC_2017.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-01684198, version 1

Collections

Citation

Ludovic Hofer. Decision-making algorithms for autonomous robots. Robotics [cs.RO]. Université de Bordeaux, 2017. English. ⟨NNT : 2017BORD0770⟩. ⟨tel-01684198⟩

Share

Metrics

Record views

727

Files downloads

2856