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Dr. Paloma De la Puente
Universidad Politécnica de Madrid, Madrid, Spain

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Research Keywords & Expertise

0 SLAM
0 Spatial Cognition
0 sensor data processing
0 Mobile robots navigation, mapping
0 Human-robot interaction for service robotics and systems engineering

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SLAM
Human-robot interaction for service robotics and systems engineering

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Journal article
Published: 24 March 2020 in IEEE Access
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Indoor environments have abundant presence of high-level semantic information which can provide a better understanding of the environment for robots to improve the uncertainty in their pose estimate. Although semantic information has proved to be useful, there are several challenges faced by the research community to accurately perceive, extract and utilize such semantic information from the environment. In order to address these challenges, in this paper we present a lightweight and real-time visual semantic SLAM framework running on board aerial robotic platforms. This novel method combines low level visual/visual-inertial odometry (VO/VIO) along with geometrical information corresponding to planar surfaces extracted from detected semantic objects. Extracting the planar surfaces from selected semantic objects provides enhanced robustness and makes it possible to precisely improve the metric estimates rapidly, simultaneously generalizing to several object instances irrespective of their shape and size. Our graph-based approach can integrate several state of the art VO/VIO algorithms along with the state of the art object detectors in order to estimate the complete 6DoF pose of the robot while simultaneously creating a sparse semantic map of the environment. No prior knowledge of the objects is required, which is a significant advantage over other works. We test our approach on a standard RGB-D dataset comparing its performance with the state of the art SLAM algorithms. We also perform several challenging indoor experiments validating our approach in presence of distinct environmental conditions and furthermore test it on board an aerial robot.

ACS Style

Hriday Bavle; Paloma De La Puente; Jonathan P. How; Pascual Campoy. VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems. IEEE Access 2020, 8, 60704 -60718.

AMA Style

Hriday Bavle, Paloma De La Puente, Jonathan P. How, Pascual Campoy. VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems. IEEE Access. 2020; 8 (99):60704-60718.

Chicago/Turabian Style

Hriday Bavle; Paloma De La Puente; Jonathan P. How; Pascual Campoy. 2020. "VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems." IEEE Access 8, no. 99: 60704-60718.

Journal article
Published: 07 February 2020 in ACM Transactions on Human-Robot Interaction
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In this article, we present results obtained from field trials with the Hobbit robotic platform, an assistive, social service robot aiming at enabling prolonged independent living of older adults in their own homes. Our main contribution lies within the detailed results on perceived safety, usability, and acceptance from field trials with autonomous robots in real homes of older users. In these field trials, we studied how 16 older adults (75 plus) lived with autonomously interacting service robots over multiple weeks. Robots have been employed for periods of months previously in home environments for older people, and some have been tested with manipulation abilities, but this is the first time a study has tested a robot in private homes that provided the combination of manipulation abilities, autonomous navigation, and non-scheduled interaction for an extended period of time. This article aims to explore how older adults interact with such a robot in their private homes. Our results show that all users interacted with Hobbit daily, rated most functions as well working, and reported that they believe that Hobbit will be part of future elderly care. We show that Hobbit’s adaptive behavior approach towards the user increasingly eased the interaction between the users and the robot. Our trials reveal the necessity to move into actual users’ homes, as only there, we encounter real-world challenges and demonstrate issues such as misinterpretation of actions during non-scripted human-robot interaction.

ACS Style

Markus Bajones; David Fischinger; Astrid Weiss; Paloma De La Puente; Daniel Wolf; Markus Vincze; Tobias Körtner; Markus Weninger; Konstantinos Papoutsakis; Damien Michel; Ammar Qammaz; Paschalis Panteleris; Michalis Foukarakis; Ilia Adami; Danae Ioannidi; Asterios Leonidis; Margherita Antona; Antonis Argyros; Peter Mayer; Paul Panek; Håkan Eftring; Susanne Frennert. Results of Field Trials with a Mobile Service Robot for Older Adults in 16 Private Households. ACM Transactions on Human-Robot Interaction 2020, 9, 1 -27.

AMA Style

Markus Bajones, David Fischinger, Astrid Weiss, Paloma De La Puente, Daniel Wolf, Markus Vincze, Tobias Körtner, Markus Weninger, Konstantinos Papoutsakis, Damien Michel, Ammar Qammaz, Paschalis Panteleris, Michalis Foukarakis, Ilia Adami, Danae Ioannidi, Asterios Leonidis, Margherita Antona, Antonis Argyros, Peter Mayer, Paul Panek, Håkan Eftring, Susanne Frennert. Results of Field Trials with a Mobile Service Robot for Older Adults in 16 Private Households. ACM Transactions on Human-Robot Interaction. 2020; 9 (2):1-27.

Chicago/Turabian Style

Markus Bajones; David Fischinger; Astrid Weiss; Paloma De La Puente; Daniel Wolf; Markus Vincze; Tobias Körtner; Markus Weninger; Konstantinos Papoutsakis; Damien Michel; Ammar Qammaz; Paschalis Panteleris; Michalis Foukarakis; Ilia Adami; Danae Ioannidi; Asterios Leonidis; Margherita Antona; Antonis Argyros; Peter Mayer; Paul Panek; Håkan Eftring; Susanne Frennert. 2020. "Results of Field Trials with a Mobile Service Robot for Older Adults in 16 Private Households." ACM Transactions on Human-Robot Interaction 9, no. 2: 1-27.

Journal article
Published: 29 August 2019 in IEEE Access
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This paper presents a system enabling a mobile robot to autonomously pick-up objects a human is pointing at from the floor. The system does not require object models and is designed to grasp unknown objects. The robot decides by itself if an object is suitable for grasping by considering measures of size, position and the environment suitability. The implementation is built on the second prototype of the home care robot Hobbit, thereby verifying that complex robotic manipulation tasks can be performed with economical hardware. The presented system was already tested in real apartments with elderly people. We highlight this by discussing the additional complexity for complete autonomous behavior in apartments compared with tests in labs.

ACS Style

Paloma De La Puente; David Fischinger; Markus Bajones; Daniel Wolf; Markus Vincze. Grasping Objects From the Floor in Assistive Robotics: Real World Implications and Lessons Learned. IEEE Access 2019, 7, 123725 -123735.

AMA Style

Paloma De La Puente, David Fischinger, Markus Bajones, Daniel Wolf, Markus Vincze. Grasping Objects From the Floor in Assistive Robotics: Real World Implications and Lessons Learned. IEEE Access. 2019; 7 (99):123725-123735.

Chicago/Turabian Style

Paloma De La Puente; David Fischinger; Markus Bajones; Daniel Wolf; Markus Vincze. 2019. "Grasping Objects From the Floor in Assistive Robotics: Real World Implications and Lessons Learned." IEEE Access 7, no. 99: 123725-123735.

Conference paper
Published: 01 February 2019 in 2019 Third IEEE International Conference on Robotic Computing (IRC)
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The localization problem, defined as the estimation of the pose of the robot in a global reference frame, is one of the fundamental aspects of mobile robotics. Even though robust localization methods do exist for many applications, it is difficult for them to work well in some challenging situations. The main contribution of this paper is the combination of information from an omnidirectional camera and a laser sensor placed on a mobile robot to locate it, assuming a 2D situation, in a predefined indoor environment by means of the Monte Carlo algorithm. For such purpose, a new observation model was included in the AMCL node of ROS in order to incorporate visual rectangular landmarks. This hybrid approach provides significant advantages for particular environments and situations.

ACS Style

Patricia Javierre; Biel Piero Alvarado; Paloma de la Puente. Particle Filter Localization Using Visual Markers Based Omnidirectional Vision and a Laser Sensor. 2019 Third IEEE International Conference on Robotic Computing (IRC) 2019, 246 -249.

AMA Style

Patricia Javierre, Biel Piero Alvarado, Paloma de la Puente. Particle Filter Localization Using Visual Markers Based Omnidirectional Vision and a Laser Sensor. 2019 Third IEEE International Conference on Robotic Computing (IRC). 2019; ():246-249.

Chicago/Turabian Style

Patricia Javierre; Biel Piero Alvarado; Paloma de la Puente. 2019. "Particle Filter Localization Using Visual Markers Based Omnidirectional Vision and a Laser Sensor." 2019 Third IEEE International Conference on Robotic Computing (IRC) , no. : 246-249.

Journal article
Published: 12 December 2018 in IEEE Access
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ACS Style

Biel Piero E. Alvarado Vasquez; Ruben Gonzalez; Fernando Matia; Paloma De La Puente. Sensor Fusion for Tour-Guide Robot Localization. IEEE Access 2018, 6, 78947 -78964.

AMA Style

Biel Piero E. Alvarado Vasquez, Ruben Gonzalez, Fernando Matia, Paloma De La Puente. Sensor Fusion for Tour-Guide Robot Localization. IEEE Access. 2018; 6 ():78947-78964.

Chicago/Turabian Style

Biel Piero E. Alvarado Vasquez; Ruben Gonzalez; Fernando Matia; Paloma De La Puente. 2018. "Sensor Fusion for Tour-Guide Robot Localization." IEEE Access 6, no. : 78947-78964.

Mini review article
Published: 30 November 2018 in Frontiers in Neurorobotics
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What does transparency mean in a shared autonomy framework? Different ways of understanding system transparency in human-robot interaction can be found in the state of the art. In one of the most common interpretations of the term, transparency is the observability and predictability of the system behavior, the understanding of what the system is doing, why, and what it will do next. Since the main methods to improve this kind of transparency are based on interface design and training, transparency is usually considered a property of such interfaces, while natural language explanations are a popular way to achieve transparent interfaces. Mechanical transparency is the robot capacity to follow human movements without human-perceptible resistive forces. Transparency improves system performance, helping reduce human errors, and builds trust in the system. One of the principles of user-centered design is to keep the user aware of the state of the system: a transparent design is a user-centered design. This article presents a review of the definitions and methods to improve transparency for applications with different interaction requirements and autonomy degrees, in order to clarify the role of transparency in shared autonomy, as well as to identify research gaps and potential future developments.

ACS Style

Victoria Alonso; Paloma de la Puente. System Transparency in Shared Autonomy: A Mini Review. Frontiers in Neurorobotics 2018, 12, 83 .

AMA Style

Victoria Alonso, Paloma de la Puente. System Transparency in Shared Autonomy: A Mini Review. Frontiers in Neurorobotics. 2018; 12 ():83.

Chicago/Turabian Style

Victoria Alonso; Paloma de la Puente. 2018. "System Transparency in Shared Autonomy: A Mini Review." Frontiers in Neurorobotics 12, no. : 83.

Conference paper
Published: 01 October 2018 in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Navigation in unknown indoor environments with fast collision avoidance capabilities is an ongoing research topic. Traditional motion planning algorithms rely on precise maps of the environment, where re-adapting a generated path can be highly demanding in terms of computational cost. In this paper, we present a fast reactive navigation algorithm using Deep Reinforcement Learning applied to multi rotor aerial robots. Taking as input the 2D-laser range measurements and the relative position of the aerial robot with respect to the desired goal, the proposed algorithm is successfully trained in a Gazebo-based simulation scenario by adopting an artificial potential field formulation. A thorough evaluation of the trained agent has been carried out both in simulated and real indoor scenarios, showing the appropriate reactive navigation behavior of the agent in the presence of static and dynamic obstacles.

ACS Style

Carlos Sampedro; Hriday Bavle; Alejandro Rodriguez-Ramos; Paloma de la Puente; Pascual Campoy. Laser-Based Reactive Navigation for Multirotor Aerial Robots using Deep Reinforcement Learning. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018, 1024 -1031.

AMA Style

Carlos Sampedro, Hriday Bavle, Alejandro Rodriguez-Ramos, Paloma de la Puente, Pascual Campoy. Laser-Based Reactive Navigation for Multirotor Aerial Robots using Deep Reinforcement Learning. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2018; ():1024-1031.

Chicago/Turabian Style

Carlos Sampedro; Hriday Bavle; Alejandro Rodriguez-Ramos; Paloma de la Puente; Pascual Campoy. 2018. "Laser-Based Reactive Navigation for Multirotor Aerial Robots using Deep Reinforcement Learning." 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , no. : 1024-1031.

Conference paper
Published: 01 October 2018 in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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In this paper we propose a particle filter localization approach, based on stereo visual odometry (VO) and semantic information from indoor environments, for mini-aerial robots. The prediction stage of the particle filter is performed using the 3D pose of the aerial robot estimated by the stereo VO algorithm. This predicted 3D pose is updated using inertial as well as semantic measurements. The algorithm processes semantic measurements in two phases; firstly, a pre-trained deep learning (DL) based object detector is used for real time object detections in the RGB spectrum. Secondly, from the corresponding 3D point clouds of the detected objects, we segment their dominant horizontal plane and estimate their relative position, also augmenting a prior map with new detections. The augmented map is then used in order to obtain a drift free pose estimate of the aerial robot. We validate our approach in several real flight experiments where we compare it against ground truth and a state of the art visual SLAM approach.

ACS Style

Hriday Bavle; Stephan Manthe; Paloma de la Puente; Alejandro Rodriguez-Ramos; Carlos Sampedro; Pascual Campoy. Stereo Visual Odometry and Semantics based Localization of Aerial Robots in Indoor Environments. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2018, 1018 -1023.

AMA Style

Hriday Bavle, Stephan Manthe, Paloma de la Puente, Alejandro Rodriguez-Ramos, Carlos Sampedro, Pascual Campoy. Stereo Visual Odometry and Semantics based Localization of Aerial Robots in Indoor Environments. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2018; ():1018-1023.

Chicago/Turabian Style

Hriday Bavle; Stephan Manthe; Paloma de la Puente; Alejandro Rodriguez-Ramos; Carlos Sampedro; Pascual Campoy. 2018. "Stereo Visual Odometry and Semantics based Localization of Aerial Robots in Indoor Environments." 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , no. : 1018-1023.

Journal article
Published: 06 September 2018 in Aerospace
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This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor environments. The objective is to present a flight altitude estimation algorithm, replacing the conventional sensors such as laser altimeters, barometers, or accelerometers, which have several limitations when used individually. Our proposed algorithm includes two stages: in the first stage, a fast clustering of the measured 3D point cloud data is performed, along with the segmentation of the clustered data into horizontal planes. In the second stage, these segmented horizontal planes are mapped based on the vertical distance with respect to the point cloud sensor frame of reference, in order to provide a robust flight altitude estimation even in presence of several static as well as dynamic ground obstacles. We validate our approach using the IROS 2011 Kinect dataset available in the literature, estimating the altitude of the RGB-D camera using the provided 3D point clouds. We further validate our approach using a point cloud sensor on board a UAV, by means of several autonomous real flights, closing its altitude control loop using the flight altitude estimated by our proposed method, in presence of several different static as well as dynamic ground obstacles. In addition, the implementation of our approach has been integrated in our open-source software framework for aerial robotics called Aerostack.

ACS Style

Hriday Bavle; Jose Luis Sanchez-Lopez; Paloma De La Puente; Alejandro Rodriguez-Ramos; Carlos Sampedro; Pascual Campoy. Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors. Aerospace 2018, 5, 94 .

AMA Style

Hriday Bavle, Jose Luis Sanchez-Lopez, Paloma De La Puente, Alejandro Rodriguez-Ramos, Carlos Sampedro, Pascual Campoy. Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors. Aerospace. 2018; 5 (3):94.

Chicago/Turabian Style

Hriday Bavle; Jose Luis Sanchez-Lopez; Paloma De La Puente; Alejandro Rodriguez-Ramos; Carlos Sampedro; Pascual Campoy. 2018. "Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors." Aerospace 5, no. 3: 94.

Article
Published: 03 July 2018 in Journal of Intelligent & Robotic Systems
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The use of multi-rotor UAVs in industrial and civil applications has been extensively encouraged by the rapid innovation in all the technologies involved. In particular, deep learning techniques for motion control have recently taken a major qualitative step, since the successful application of Deep Q-Learning to the continuous action domain in Atari-like games. Based on these ideas, Deep Deterministic Policy Gradients (DDPG) algorithm was able to provide outstanding results with continuous state and action domains, which are a requirement in most of the robotics-related tasks. In this context, the research community is lacking the integration of realistic simulation systems with the reinforcement learning paradigm, enabling the application of deep reinforcement learning algorithms to the robotics field. In this paper, a versatile Gazebo-based reinforcement learning framework has been designed and validated with a continuous UAV landing task. The UAV landing maneuver on a moving platform has been solved by means of the novel DDPG algorithm, which has been integrated in our reinforcement learning framework. Several experiments have been performed in a wide variety of conditions for both simulated and real flights, demonstrating the generality of the approach. As an indirect result, a powerful work flow for robotics has been validated, where robots can learn in simulation and perform properly in real operation environments. To the best of the authors knowledge, this is the first work that addresses the continuous UAV landing maneuver on a moving platform by means of a state-of-the-art deep reinforcement learning algorithm, trained in simulation and tested in real flights.

ACS Style

Alejandro Rodriguez-Ramos; Carlos Sampedro; Hriday Bavle; Paloma de la Puente; Pascual Campoy. A Deep Reinforcement Learning Strategy for UAV Autonomous Landing on a Moving Platform. Journal of Intelligent & Robotic Systems 2018, 93, 351 -366.

AMA Style

Alejandro Rodriguez-Ramos, Carlos Sampedro, Hriday Bavle, Paloma de la Puente, Pascual Campoy. A Deep Reinforcement Learning Strategy for UAV Autonomous Landing on a Moving Platform. Journal of Intelligent & Robotic Systems. 2018; 93 (1-2):351-366.

Chicago/Turabian Style

Alejandro Rodriguez-Ramos; Carlos Sampedro; Hriday Bavle; Paloma de la Puente; Pascual Campoy. 2018. "A Deep Reinforcement Learning Strategy for UAV Autonomous Landing on a Moving Platform." Journal of Intelligent & Robotic Systems 93, no. 1-2: 351-366.

Article
Published: 03 July 2018 in Journal of Intelligent & Robotic Systems
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Search and Rescue (SAR) missions represent an important challenge in the robotics research field as they usually involve exceedingly variable-nature scenarios which require a high-level of autonomy and versatile decision-making capabilities. This challenge becomes even more relevant in the case of aerial robotic platforms owing to their limited payload and computational capabilities. In this paper, we present a fully-autonomous aerial robotic solution, for executing complex SAR missions in unstructured indoor environments. The proposed system is based on the combination of a complete hardware configuration and a flexible system architecture which allows the execution of high-level missions in a fully unsupervised manner (i.e. without human intervention). In order to obtain flexible and versatile behaviors from the proposed aerial robot, several learning-based capabilities have been integrated for target recognition and interaction. The target recognition capability includes a supervised learning classifier based on a computationally-efficient Convolutional Neural Network (CNN) model trained for target/background classification, while the capability to interact with the target for rescue operations introduces a novel Image-Based Visual Servoing (IBVS) algorithm which integrates a recent deep reinforcement learning method named Deep Deterministic Policy Gradients (DDPG). In order to train the aerial robot for performing IBVS tasks, a reinforcement learning framework has been developed, which integrates a deep reinforcement learning agent (e.g. DDPG) with a Gazebo-based simulator for aerial robotics. The proposed system has been validated in a wide range of simulation flights, using Gazebo and PX4 Software-In-The-Loop, and real flights in cluttered indoor environments, demonstrating the versatility of the proposed system in complex SAR missions.

ACS Style

Carlos Sampedro; Alejandro Rodriguez-Ramos; Hriday Bavle; Adrian Carrio; Paloma De La Puente; Pascual Campoy. A Fully-Autonomous Aerial Robot for Search and Rescue Applications in Indoor Environments using Learning-Based Techniques. Journal of Intelligent & Robotic Systems 2018, 95, 601 -627.

AMA Style

Carlos Sampedro, Alejandro Rodriguez-Ramos, Hriday Bavle, Adrian Carrio, Paloma De La Puente, Pascual Campoy. A Fully-Autonomous Aerial Robot for Search and Rescue Applications in Indoor Environments using Learning-Based Techniques. Journal of Intelligent & Robotic Systems. 2018; 95 (2):601-627.

Chicago/Turabian Style

Carlos Sampedro; Alejandro Rodriguez-Ramos; Hriday Bavle; Adrian Carrio; Paloma De La Puente; Pascual Campoy. 2018. "A Fully-Autonomous Aerial Robot for Search and Rescue Applications in Indoor Environments using Learning-Based Techniques." Journal of Intelligent & Robotic Systems 95, no. 2: 601-627.

Article
Published: 29 June 2018 in Journal of Intelligent & Robotic Systems
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Future home and service robots will require advanced navigation and interaction capabilities. In particular, domestic environments present open challenges that are hard to identify by conducting controlled tests in home-like settings: there is the need to test and evaluate navigation in the actual homes of users. This paper presents the experiences of operating a mobile robot with manipulation capabilities and an open set of tasks in extensive trials with real users, in their own homes. The main difficulties encountered are the requirement to move safely in cluttered 3D environments, the problems related to navigation in narrow spaces, and the need for an adaptive rather than fixed way to approach the users. We describe our solutions based on RGB-D perception and evaluate the integrated system for navigation in real home environments, pointing out remaining challenges towards more advanced commercial solutions.

ACS Style

Paloma De La Puente; Markus Bajones; Christian Reuther; Daniel Wolf; David Fischinger; Markus Vincze. Robot Navigation in Domestic Environments: Experiences Using RGB-D Sensors in Real Homes. Journal of Intelligent & Robotic Systems 2018, 94, 455 -470.

AMA Style

Paloma De La Puente, Markus Bajones, Christian Reuther, Daniel Wolf, David Fischinger, Markus Vincze. Robot Navigation in Domestic Environments: Experiences Using RGB-D Sensors in Real Homes. Journal of Intelligent & Robotic Systems. 2018; 94 (2):455-470.

Chicago/Turabian Style

Paloma De La Puente; Markus Bajones; Christian Reuther; Daniel Wolf; David Fischinger; Markus Vincze. 2018. "Robot Navigation in Domestic Environments: Experiences Using RGB-D Sensors in Real Homes." Journal of Intelligent & Robotic Systems 94, no. 2: 455-470.

Research article
Published: 03 June 2018 in Journal of Robotics
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We present the robot developed within the Hobbit project, a socially assistive service robot aiming at the challenge of enabling prolonged independent living of elderly people in their own homes. We present the second prototype (Hobbit PT2) in terms of hardware and functionality improvements following first user studies. Our main contribution lies within the description of all components developed within the Hobbit project, leading to autonomous operation of 371 days during field trials in Austria, Greece, and Sweden. In these field trials, we studied how 18 elderly users (aged 75 years and older) lived with the autonomously interacting service robot over multiple weeks. To the best of our knowledge, this is the first time a multifunctional, low-cost service robot equipped with a manipulator was studied and evaluated for several weeks under real-world conditions. We show that Hobbit’s adaptive approach towards the user increasingly eased the interaction between the users and Hobbit. We provide lessons learned regarding the need for adaptive behavior coordination, support during emergency situations, and clear communication of robotic actions and their consequences for fellow researchers who are developing an autonomous, low-cost service robot designed to interact with their users in domestic contexts. Our trials show the necessity to move out into actual user homes, as only there can we encounter issues such as misinterpretation of actions during unscripted human-robot interaction.

ACS Style

Markus Bajones; David Fischinger; Astrid Weiss; Daniel Wolf; Markus Vincze; Paloma De La Puente; Tobias Kortner; Markus Weninger; Konstantinos Papoutsakis; Damien Michel; Ammar Qammaz; Paschalis Panteleris; Michalis Foukarakis; Ilia Adami; Danai Ioannidi; Asterios Leonidis; Margherita Antona; Antonis Argyros; Peter Mayer; Paul Panek; Hakan Eftring; Susanne Frennert. Hobbit: Providing Fall Detection and Prevention for the Elderly in the Real World. Journal of Robotics 2018, 2018, 1 -20.

AMA Style

Markus Bajones, David Fischinger, Astrid Weiss, Daniel Wolf, Markus Vincze, Paloma De La Puente, Tobias Kortner, Markus Weninger, Konstantinos Papoutsakis, Damien Michel, Ammar Qammaz, Paschalis Panteleris, Michalis Foukarakis, Ilia Adami, Danai Ioannidi, Asterios Leonidis, Margherita Antona, Antonis Argyros, Peter Mayer, Paul Panek, Hakan Eftring, Susanne Frennert. Hobbit: Providing Fall Detection and Prevention for the Elderly in the Real World. Journal of Robotics. 2018; 2018 ():1-20.

Chicago/Turabian Style

Markus Bajones; David Fischinger; Astrid Weiss; Daniel Wolf; Markus Vincze; Paloma De La Puente; Tobias Kortner; Markus Weninger; Konstantinos Papoutsakis; Damien Michel; Ammar Qammaz; Paschalis Panteleris; Michalis Foukarakis; Ilia Adami; Danai Ioannidi; Asterios Leonidis; Margherita Antona; Antonis Argyros; Peter Mayer; Paul Panek; Hakan Eftring; Susanne Frennert. 2018. "Hobbit: Providing Fall Detection and Prevention for the Elderly in the Real World." Journal of Robotics 2018, no. : 1-20.

Conference paper
Published: 03 November 2016 in Research and Advanced Technology for Digital Libraries
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ACS Style

Markus Vincze; Markus Bajones; Markus Suchi; Daniel Wolf; Astrid Weiss; David Fischinger; Paloma de la Puente. Learning and Detecting Objects with a Mobile Robot to Assist Older Adults in Their Homes. Research and Advanced Technology for Digital Libraries 2016, 316 -330.

AMA Style

Markus Vincze, Markus Bajones, Markus Suchi, Daniel Wolf, Astrid Weiss, David Fischinger, Paloma de la Puente. Learning and Detecting Objects with a Mobile Robot to Assist Older Adults in Their Homes. Research and Advanced Technology for Digital Libraries. 2016; ():316-330.

Chicago/Turabian Style

Markus Vincze; Markus Bajones; Markus Suchi; Daniel Wolf; Astrid Weiss; David Fischinger; Paloma de la Puente. 2016. "Learning and Detecting Objects with a Mobile Robot to Assist Older Adults in Their Homes." Research and Advanced Technology for Digital Libraries , no. : 316-330.

Journal article
Published: 28 November 2015 in Journal of Intelligent & Robotic Systems
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This paper presents a completely autonomous solution to participate in the Indoor Challenge of the 2013 International Micro Air Vehicle Competition (IMAV 2013). Our proposal is a multi-robot system with no centralized coordination whose robotic agents share their position estimates. The capability of each agent to navigate avoiding collisions is a consequence of the resulting emergent behavior. Each agent consists of a ground station running an instance of the proposed architecture that communicates over WiFi with an AR Drone 2.0 quadrotor. Visual markers are employed to sense and map obstacles and to improve the pose estimation based on Inertial Measurement Unit (IMU) and ground optical flow data. Based on our architecture, each robotic agent can navigate avoiding obstacles and other members of the multi-robot system. The solution is demonstrated and the achieved navigation performance is evaluated by means of experimental flights. This work also analyzes the capabilities of the presented solution in simulated flights of the IMAV 2013 Indoor Challenge. The performance of the CVG_UPM team was awarded with the First Prize in the Indoor Autonomy Challenge of the IMAV 2013 competition.

ACS Style

Jesús Pestana; Jose Luis Sanchez-Lopez; Paloma de la Puente; Adrian Carrio; Pascual Campoy. A Vision-based Quadrotor Multi-robot Solution for the Indoor Autonomy Challenge of the 2013 International Micro Air Vehicle Competition. Journal of Intelligent & Robotic Systems 2015, 84, 601 -620.

AMA Style

Jesús Pestana, Jose Luis Sanchez-Lopez, Paloma de la Puente, Adrian Carrio, Pascual Campoy. A Vision-based Quadrotor Multi-robot Solution for the Indoor Autonomy Challenge of the 2013 International Micro Air Vehicle Competition. Journal of Intelligent & Robotic Systems. 2015; 84 (1-4):601-620.

Chicago/Turabian Style

Jesús Pestana; Jose Luis Sanchez-Lopez; Paloma de la Puente; Adrian Carrio; Pascual Campoy. 2015. "A Vision-based Quadrotor Multi-robot Solution for the Indoor Autonomy Challenge of the 2013 International Micro Air Vehicle Competition." Journal of Intelligent & Robotic Systems 84, no. 1-4: 601-620.

Journal article
Published: 23 October 2015 in Journal of Intelligent & Robotic Systems
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During the process of design and development of an autonomous Multi-UAV System, two main problems appear. The first one is the difficulty of designing all the modules and behaviors of the aerial multi-robot system. The second one is the difficulty of having an autonomous prototype of the system for the developers that allows to test the performance of each module even in an early stage of the project. These two problems motivate this paper. A multipurpose system architecture for autonomous multi-UAV platforms is presented. This versatile system architecture can be used by the system designers as a template when developing their own systems. The proposed system architecture is general enough to be used in a wide range of applications, as demonstrated in the paper. This system architecture aims to be a reference for all designers. Additionally, to allow for the fast prototyping of autonomous multi-aerial systems, an Open Source framework based on the previously defined system architecture is introduced. It allows developers to have a flight proven multi-aerial system ready to use, so that they can test their algorithms even in an early stage of the project. The implementation of this framework, introduced in the paper with the name of “CVG Quadrotor Swarm”, which has also the advantages of being modular and compatible with different aerial platforms, can be found at https://​github.​com/​Vision4UAV/​cvg_​quadrotor_​swarm with a consistent catalog of available modules. The good performance of this framework is demonstrated in the paper by choosing a basic instance of it and carrying out simulation and experimental tests whose results are summarized and discussed in this paper.

ACS Style

Jose Luis Sanchez-Lopez; Jesús Pestana; Paloma de la Puente; Pascual Campoy. A Reliable Open-Source System Architecture for the Fast Designing and Prototyping of Autonomous Multi-UAV Systems: Simulation and Experimentation. Journal of Intelligent & Robotic Systems 2015, 84, 779 -797.

AMA Style

Jose Luis Sanchez-Lopez, Jesús Pestana, Paloma de la Puente, Pascual Campoy. A Reliable Open-Source System Architecture for the Fast Designing and Prototyping of Autonomous Multi-UAV Systems: Simulation and Experimentation. Journal of Intelligent & Robotic Systems. 2015; 84 (1-4):779-797.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Jesús Pestana; Paloma de la Puente; Pascual Campoy. 2015. "A Reliable Open-Source System Architecture for the Fast Designing and Prototyping of Autonomous Multi-UAV Systems: Simulation and Experimentation." Journal of Intelligent & Robotic Systems 84, no. 1-4: 779-797.

Journal article
Published: 01 January 2015 in Robotics and Autonomous Systems
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ACS Style

Paloma de la Puente; Diego Rodriguez-Losada. Feature based graph SLAM with high level representation using rectangles. Robotics and Autonomous Systems 2015, 63, 80 -88.

AMA Style

Paloma de la Puente, Diego Rodriguez-Losada. Feature based graph SLAM with high level representation using rectangles. Robotics and Autonomous Systems. 2015; 63 ():80-88.

Chicago/Turabian Style

Paloma de la Puente; Diego Rodriguez-Losada. 2015. "Feature based graph SLAM with high level representation using rectangles." Robotics and Autonomous Systems 63, no. : 80-88.

Conference paper
Published: 01 September 2014 in 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
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While navigation based on 2D laser data is well understood, the application of robots at home environments requires seeing more than a slice of the world. RGB-D cameras have been used to perceive the full scenes and solutions exist consuming extensive computing power. We propose a setup with two RGB-D cameras that covers the need for conflicting requirements regarding localization, obstacle avoidance, object search and recognition, and gesture recognition. We show that this setup provides sufficient data to enable navigation at homes and we present how ROS modules can be configured to use virtual RGB-D scans instead of laser data for operation in real-time (10Hz). Finally, we present first results of exploiting this versatile setup for a home service robot that picks up things from the floor to prevent potential falls of its future users.

ACS Style

Paloma De La Puente; M. Bajones; P. Einramhof; Denis Wolf; D. Fischinger; Markus Vincze. RGB-D sensor setup for multiple tasks of home robots and experimental results. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems 2014, 2587 -2594.

AMA Style

Paloma De La Puente, M. Bajones, P. Einramhof, Denis Wolf, D. Fischinger, Markus Vincze. RGB-D sensor setup for multiple tasks of home robots and experimental results. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2014; ():2587-2594.

Chicago/Turabian Style

Paloma De La Puente; M. Bajones; P. Einramhof; Denis Wolf; D. Fischinger; Markus Vincze. 2014. "RGB-D sensor setup for multiple tasks of home robots and experimental results." 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems , no. : 2587-2594.

Conference paper
Published: 01 May 2014 in 2014 International Conference on Unmanned Aircraft Systems (ICUAS)
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This paper presents a completely autonomous solution to participate in the 2013 International Micro Air Vehicle Indoor Flight Competition (IMAV2013). Our proposal is a modular multi-robot swarm architecture, based on the Robot Operating System (ROS) software framework, where the only information shared among swarm agents is each robot's position. Each swarm agent consists of an AR Drone 2.0 quadrotor connected to a laptop which runs the software architecture. In order to present a completely visual-based solution the localization problem is simplified by the usage of ArUco visual markers. These visual markers are used to sense and map obstacles and to improve the pose estimation based on the IMU and optical data flow by means of an Extended Kalman Filter localization and mapping method. The presented solution and the performance of the CVG UPM team were awarded with the First Prize in the Indoors Autonomy Challenge of the IMAV2013 competition.

ACS Style

Jesus Pestana; Jose Luis Sanchez-Lopez; Paloma de la Puente; Adrian Carrio; Pascual Campoy. A Vision-based Quadrotor Swarm for the participation in the 2013 International Micro Air Vehicle Competition. 2014 International Conference on Unmanned Aircraft Systems (ICUAS) 2014, 617 -622.

AMA Style

Jesus Pestana, Jose Luis Sanchez-Lopez, Paloma de la Puente, Adrian Carrio, Pascual Campoy. A Vision-based Quadrotor Swarm for the participation in the 2013 International Micro Air Vehicle Competition. 2014 International Conference on Unmanned Aircraft Systems (ICUAS). 2014; ():617-622.

Chicago/Turabian Style

Jesus Pestana; Jose Luis Sanchez-Lopez; Paloma de la Puente; Adrian Carrio; Pascual Campoy. 2014. "A Vision-based Quadrotor Swarm for the participation in the 2013 International Micro Air Vehicle Competition." 2014 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 617-622.

Journal article
Published: 12 February 2014 in Autonomous Robots
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Introducing a priori knowledge about the latent structure of the environment in simultaneous localization and mapping (SLAM), can improve the quality and consistency results of its solutions. In this paper we describe and analyze a general framework for the detection, evaluation, incorporation and removal of structure constraints into a feature-based graph formulation of SLAM. We specifically show how including different kinds and levels of features in a hierarchical manner allows the system to easily discover new structure and why it makes more sense than other possible representations. The main algorithm in this framework follows an expectation maximization approach to iteratively infer the most probable structure and the most probable map. Experimental results show how this approach is suitable for the integration of a large variety of constraints and how our method can produce nice and consistent maps in regular environments.

ACS Style

Paloma De La Puente; D. Rodriguez-Losada. Feature based graph-SLAM in structured environments. Autonomous Robots 2014, 37, 243 -260.

AMA Style

Paloma De La Puente, D. Rodriguez-Losada. Feature based graph-SLAM in structured environments. Autonomous Robots. 2014; 37 (3):243-260.

Chicago/Turabian Style

Paloma De La Puente; D. Rodriguez-Losada. 2014. "Feature based graph-SLAM in structured environments." Autonomous Robots 37, no. 3: 243-260.