Angel Llamazares

• PhD Student. Robotics
• PhD Student at University of Alcalá

Advances in sensor fusion techniques are redefining the landscape of 3D point cloud semantic segmentation, particularly for autonomous driving applications. We propose an enhanced approach that leverages the complementary strengths of LiDAR and multi-camera systems. This study introduces two extensions to the state-of-the-art SalsaNext model [1] ba...

Accurate object detection and prediction are critical to ensure the safety and efficiency of self-driving architectures. Predicting object trajectories and occupancy enables autonomous vehicles to anticipate movements and make decisions with future information, increasing their adaptability and reducing the risk of accidents. Current State-Of-The-A...

Explaining the decision made by end-to-end autonomous driving is a difficult task. These approaches take raw sensor data and compute the decision as a black box with large deep learning models. Understanding the output of deep learning is a complex challenge due to the complicated nature of explainability; as data passes through the network, it bec...

RADARs and cameras have been present in automotives since the advent of ADAS, as they possess complementary strengths and weaknesses but have been underlooked in the context of learning-based methods. In this work, we propose a method to perform object detection in autonomous driving based on a geometrical and sequential sensor fusion of 3+1D RADAR...

In this work, we present a complete system to produce an automatic linguistic reporting about the customer activity patterns inside open malls, a mixed distribution of classical malls joined with the shops on the street. These reports can assist to design marketing campaigns by means of identifying the best places to catch the attention of customer...

In this work we present a method to estimate the activity patterns made by shoppers in open malls based on localization information and process mining techniques. We present our smart phone application for logging information from sensors and a process mining system to discover what kind of activity pattern is made by the shoppers based in the key...

The goal of this paper is to improve our previous Dynamic Obstacle Mapping (DOMap) system by means of improving the perception stage. The new system must deal with robots and people as dynamic obstacles using LIght Detection And Range (LIDAR) sensor in order to collect the surrounding information. Although robot movement can be easily tracked by an...

Working with mobile robots, prior to execute the local planning stage, they must know the environment where they are moving. For that reason the perception and mapping stages must be performed previously. This paper presents a survey in the state of the art in detection and tracking of moving obstacles ( DATMO ). The aim of what follows is to provi...

In recent years, Unmanned Ground Vehicles (UGVs) have been widely used as service robots. Unlike industrial robots, which are situated in fixed and controlled positions, UGVs work in dynamic environments, sharing the environment with other vehicles and humans. These robots should be able to move without colliding with any obstacle, assuring its int...

This paper deals with the stability analysis of a Cooperative Adaptive Cruise Control system (CACC) in a convoy of vehicles, in order to solve traffic congestion. The differences between the Adaptive Cruise Control (ACC) and its cooperative version will be studied from the string stability point of view, highlighting the advantages of adding Vehicl...

This paper deals with the stability analysis of a Cooperative Adaptive Cruise Control system (CACC) in a convoy of vehicles, in order to solve traffic congestion. The differences between the Adaptive Cruise Control (ACC) and its cooperative version will be studied from the string stability point of view, highlighting the advantages of adding Vehicl...

Traditionally, obstacle avoidance algorithms have been developed and applied successfully to mobile robots that work in controlled and static environments. But, when working in real scenarios the problem becomes complex since the scenario is dynamic and the algorithms must be enhanced in order to deal with moving objects. In this paper we propose a...

Localization and mapping in indoor environments, such as airports and hospitals, are key tasks for almost every robotic platform. Some researchers suggest the use of Range-Only (RO) sensors based on WiFi (Wireless Fidelity) technology with SLAM (Simultaneous Localization And Mapping) techniques to solve both problems. The current state of the art i...

Localization and mapping in indoor environments, such as airports and hospitals, are key tasks for almost every robotic platform. Some researchers suggest the use of RO (Range Only) sensors based on WiFi (Wireless Fidelity) technology with SLAM (Simultaneous Localization And Mapping) techniques. The current state of the art in RO SLAM is mainly foc...

ABSYNTHE, which stands for Abstraction, Synthesis, and Integration of Information for Human-Robot Teams, is an interdisciplinary project which aims to develop basic concepts and structures for the abstraction of partial views of the environment and the actions and intentions of teams, as well as the integration of this information into situation as...

On October 25th 2012 DARPA anounced the DARPA Robotics Challenge (DRC) kick off. The DRC is part of the US Department of Defense’s strategic plan to conduct humanitarian, disaster relief and related operations. The DRC particularly aims to promoting innovation in robotic technology (software and hardware) to improve the capability of ground robotic...

This paper presents different techniques to achieve the tasks proposed in the DARPA (Defense Advanced Research Projects Agency) VRC (Virtual Robotics Challenge), which entails the recognition of objects, the robot localization and the mapping of the simulated environments in the Challenge. Data acquisition relies on several sensors such as a stereo...

The goal of this paper is to solve the problem of dynamic obstacle avoidance for a mobile platform by using the stochastic optimal control framework to compute paths that are optimal in terms of safety and energy efficiency under constraints. We propose a three-dimensional extension of the Bayesian Occupancy Filter (BOF) (Coué et al. Int. J. Rob. R...

There are several algorithms to avoid local obstacles for mobile robots. Usually, these algorithms use only the information provided by range sensors. The goal of this paper is to compare some of these algorithms, from classic to modern ones, in order to evaluate the strengths and weakness of each one.

This paper presents the results of a set of extensive experiments carried out under both daytime and nighttime real traffic conditions. The data were captured using an enhanced or extended Floating Car Data system (xFCD) that includes a stereo vision sensor for detecting the local traffic ahead. The collected information is then used to propose a n...

The framework of this paper is robot localization inside buildings by means of wireless localization systems. Such kind of systems make use of the Wireless Fidelity (WiFi) signal strength sensors which are becoming more and more useful in the localization stage of several robotic platforms. Robot localization is usually made up of two phases: train...

This paper presents a complete traffic sign recognition system, including the steps of detection, recognition and tracking. The Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM), and is able to recognize up to one hundred of t...

This paper describes a new approach for improving the estimation of the global position of a vehicle in complex urban environments by means of visual odometry and map fusion. The visual odometry system is based on the compensation of the heterodasticity in the 3D input data using a weighted nonlinear least squares based system. RANdom SAmple Consen...

This paper presents the results of a set of extensive experiments carried out in daytime and nighttime conditions in real traffic using an enhanced or extended Floating Car Data system (xFCD) that includes a stereo vision sensor for detecting the local traffic ahead. The detection component implies the use of previously monocular approaches develop...

Mapping techniques based on Wireless Range-Only Sensors (WROS) consist of locating the beacons using measurements of distance only. In this work we use WROS working at 2.4GHz band (same as WiFi, Wireless Fidelity), which has the disadvantage of being affected by a high noise. The goal of this paper is to study a noisy range-only sensor and its appl...

In this paper we present a technique to build 3D maps of the environment using a 2D laser scanner combined with a robot’s action model. This paper demonstrates that it is possible to build 3D maps in a cheap way using an angled 2D laser. We introduce a scan matching method to minimize the odometer errors of the robotics platform and a calibration m...

This work presents a general framework for people indoor activity recognition. Firstly, a Wireless Fidelity (WiFi) localization system implemented as a Fuzzy Rule-based Classifier (FRBC) is used to obtain an approximate position at the level of discrete zones (office, corridor, meeting room, etc). Secondly, a Fuzzy Finite State Machine (FFSM) is us...

The goal of this paper is to study a noisy WiFi range-only sensor and its application in the development of localization and mapping systems. Moreover, the paper shows several localization and mapping techniques to be compared. These techniques have been applied successfully with other technologies, like ultra-wide band (UWB), but we demonstrate th...