Alex Goldhoorn

Searching and Tracking of Humans in Urban Environments by Humanoid Robots
PhD Thesis, Universitat Politècnica de Catalunya, 2017
PDF | BibTeX | Thesis page

Algorithms for robots to find and track people in urban environments using POMCP (reinforcement learning) and particle filters. Handles noisy sensors, dynamic obstacles, and cooperative multi-robot search.

Searching and Tracking of Humans with Cooperative Mobile Robots
Autonomous Robots, vol. 42, pp. 1-25, 2017
A. Goldhoorn, A. Garrell, R. Alquézar, A. Sanfeliu
PDF | BibTeX | DOI | Project page

Presents two different techniques for coordinated multi-robot teams for searching and tracking people. A probability map of the target person's location is maintained using two methods: one based on a reinforcement learning algorithm (POMCP) and the other based on a particle filter. The validation was accomplished with extensive simulations using up to five agents and over three hours of real-life experiments with two robots.

Searching and Tracking People in Urban Environments with Static and Dynamic Obstacles
Robotics and Autonomous Systems, 2017
A. Goldhoorn, A. Garrell, R. Alquézar, A. Sanfeliu
PDF | BibTeX | DOI | Project page

Addresses the challenge of tracking people in crowded urban environments with static and dynamic obstacles. Proposes a Highest Belief Particle Filter approach that can search and track under uncertainty in continuous space and real-time, using dynamic obstacles to improve predictions of person location.

Combining Invariant Features and the ALV Homing Method for Autonomous Robot Navigation Based on Panoramas
Journal of Intelligent and Robotic Systems, vol. 64, no. 3-4, pp. 625-649, 2011
A. Ramisa, A. Goldhoorn, D. Aldavert, R. Toledo, R. López de Màntaras
PDF | BibTeX | DOI

Presents a visual homing method that combines invariant feature descriptors with the Average Landmark Vector (ALV) approach for robust autonomous robot navigation using panoramic images. Demonstrates improved performance in the presence of noise, occlusions, and dynamic environments.

Continuous Real Time POMCP to Find-and-Follow People by a Humanoid Service Robot
IEEE-RAS International Conference on Humanoid Robots (Humanoids), Madrid, Spain, 2014
A. Goldhoorn, A. Garrell, R. Alquézar, A. Sanfeliu
PDF | BibTeX | Project page

Adapts the POMCP algorithm to work in continuous action spaces for real-time operation on humanoid service robots. Enables robots to autonomously find and follow people in indoor environments, handling partial observability and dynamic human behavior with efficient online planning.

XIM-Engine: A Software Framework to Support the Development of Interactive Applications that Uses Conscious and Unconscious Reactions in Immersive Mixed Reality
Virtual Reality International Conference (VRIC), Laval, France, 2014
P. Omedas et al. (including A. Goldhoorn)
PDF | BibTeX

Presents a software framework for developing interactive applications combining conscious and unconscious reactions in immersive mixed reality environments, integrating affective computing and bio-inspired cognitive systems.

Analysis of Methods for Playing Human Robot Hide-and-Seek in a Simple Real World Urban Environment
ROBOT 2013: First Iberian Robotics Conference, Madrid, Spain, 2013
A. Goldhoorn, A. Sanfeliu, R. Alquézar
PDF | BibTeX | DOI | Project page | Interactive Demo

Analyzes different methods for enabling robots to play hide-and-seek with humans in urban environments. Compares heuristic approaches with planning algorithms under uncertainty, evaluating their performance in real-world scenarios with dynamic obstacles and occlusions.

Comparison of MOMDP and Heuristic Methods to Play Hide-and-Seek
International Conference of the Catalan Association for Artificial Intelligence (CCIA), 2013
A. Goldhoorn, A. Sanfeliu, R. Alquézar
PDF | BibTeX | DOI

Compares Mixed Observability Markov Decision Process (MOMDP) approaches with heuristic methods for the hide-and-seek problem. Shows that MOMDP-based planners can outperform heuristics by explicitly reasoning about uncertainty and information gathering.

Solving Ambiguity in Global Localization of Autonomous Robots
M.Sc. Thesis, University of Groningen, The Netherlands
A. Goldhoorn
PDF | BibTeX | Presentation at UPF (2009)

Master's thesis addressing the challenge of resolving ambiguity in global robot localization, particularly in symmetric or repetitive environments where multiple hypotheses about the robot's position are equally likely. The work was presented at UPF Barcelona's AI department in July 2009, focusing on the Average Landmark Vector (ALV) homing method.

Using the Average Landmark Vector Method for Robot Homing
Frontiers in Artificial Intelligence and Applications, vol. 163, pp. 331-338, 2007
A. Goldhoorn, A. Ramisa, R. López de Màntaras, R. Toledo
PDF | BibTeX | Interactive Demo

Evaluates the Average Landmark Vector (ALV) method for visual robot homing using panoramic feature projections. Shows robustness to noise, occlusion, and fake features, achieving 85% success rate even with 50% of features randomly removed.

Implementation of a Simultaneous Localization and Mapping System using Growing Neural Gas
B.Sc. Thesis, University of Groningen, The Netherlands, 2006
A. Goldhoorn, H. Stadman, H. Eldering
PDF | BibTeX | Interactive Demo

Bachelor's thesis presenting a SLAM (Simultaneous Localization and Mapping) implementation using Growing Neural Gas, a self-organizing neural network approach for incremental map building and robot localization.

Porting of the IRScan Man Machine Interface from Sun Sparc to PC Linux
HBO Bachelor in ICT Graduation Project, Hanzehogeschool Groningen, The Netherlands, 2003
A. Goldhoorn
PDF | BibTeX

Industrial placement project at Thales Nederland BV, porting the Man Machine Interface of the IRScan infrared targeting system for the Goalkeeper maritime anti-missile defense system from Sun Sparc to PC Linux platform. Demonstrates cross-platform migration techniques for real-time defense systems requiring high reliability.

Oriëntatiestage: Expertensysteem voor de Juridische Faculteit (Orientation Internship: Expert System for the Faculty of Law)
HBO Bachelor in ICT Orientation Internship, Hanzehogeschool Groningen, The Netherlands, 2001-2002
A. Goldhoorn
PDF (in Dutch) | BibTeX

Development of database tools (FactEditor and RelationEditor) in Java for a legal expert system using non-monotonic logic at the University of Groningen's Legal Informatics Section. Includes design and implementation of an RMI-based client/server architecture for "the LawGame", enabling collaborative interaction with the expert system. The system uses Sybase databases to store legal facts, rules, and relations for automated legal reasoning.