Publication type: Conferences

Estimation of Scene Lighting Parameters and Camera Dark Current

Using Particle Filters for Autonomous Underwater Cable Tracking

A Bayesian Approach for Tracking Undersea Narrow Telecommunication Cables

Auction Like Task Allocation and Motion Coordination Strategies for Multi-Robot Transport Tasks

In this paper we present a task allocation method based on auction mechanisms that allows to find how many robots are needed to execute a task. This number is unknown and depends on several factors. There are also different types of tasks that must be executed using different skills of the robots. It is very difficult to find a correct allocation under this conditions and at present it is an open problem. We also propose two motion coordination methods to reduce the interference effect between robots. To test our system a modification of the well know foraging task has been used. This task introduces special characteristics, not directly studied in previous work, that our method try to solve.

A Multi-Robot Task Allocation Method To Regulate Working Groups Sizes

Learning by Example: Reinforcement Learning Techniques for Real Autonomous Underwater Cable Tracking

Estimation of Intensity Uncertainties for Computer Vision Applications

A Behaviour-based Control Architecture for Visually Guiding an Underwater Cable Tracker

Sonar Scan Matching by Filtering Scans using Grids of Normal Distributions

Path Planning of Autonomous Underwater Vehicles in Current Fields with Complex Spatial Variability: an A* Approach