News Article | May 23, 2017
If any place in the world is moving towards a Bladerunner-esque, sci-fi future, it's Dubai. From a fleet of supercars that enlist the assistance of Crime Prediction software in preventing crime to their jet-pack riding firefighters, this is a city that isn't afraid to embrace 21st century technology. Now it is introducing robots into its police force with the first cop-bot starting work this week and plans for 25 percent of its force to be robotic by 2030. The initial robocop introduction will come in the form of REEM, a humanoid robot from Spanish outfit PAL Robotics. REEM was first launched back in 2011 essentially as a customizable service robot on a wheeled base designed to act as a high-tech interactive info booth for airports, museums or hospitals. Dubai Police worked with PAL Robotics to refine the REEM design for their purposes and unveiled an adapted version in late 2016. In a recent interview with CNN, Brigadier Khalid Nasser Alrazooqi, head of the police robot project, revealed that the robocop will initially be rolled out in shopping centers and at tourist attractions before being moved into police stations to act as receptionists. Citizens will be able to pay fines, report crimes and generally conduct an assortment of initial, first-encounter police interactions. "We are looking to have more robots in future to handle policing," the director of the Future Shaping Centre of Dubai Police, Brigadier Abdullah Bin Sultan, said in an announcement in March reported by Gulf News. "By 2030, we are keen to make robots around 25 per cent of the total police force." While this initial robotic introduction to Dubai's police ranks is fairly modest, mobile robotic cops are apparently on the cards. The Dubai Police is expecting to reveal a prototype mobile police robot by 2020, and also aims to have a human-free police station manned completely by robots by 2030. The impressive ambitions of Dubai's police aside, there are a host of ethical and practical issues in actually moving to a world where autonomous robots detain or arrest people on the streets. In the meantime, though, we can definitely see robot receptionists taking over the dry admin tasks in police stations or the boring surveillance activities of mall cops. So in the short term at least, the future may be less Robocop and more Paul Blart: Mall Robocop.
Diaz M.,Polytechnic University of Catalonia |
Paillacho D.,ESPOL Polytechnic University |
Angulo C.,Polytechnic University of Catalonia |
Torres O.,PAL Robotics |
And 2 more authors.
ACM/IEEE International Conference on Human-Robot Interaction | Year: 2014
In order to observe spatial relationships in social human-robot interactions, a field trial was carried out within the CosmoCaixa Science Museum in Barcelona. The follow me episodes studied showed that the space configurations formed by guide and visitors walking together did not always fit the robot social affordances and navigation requirements to perform the guidance successfully, thus additional communication prompts are considered to regulate effectively the walking together and follow me behaviors.
Corominas-Murtra A.,Beta Robots |
Corominas-Murtra A.,Polytechnic University of Catalonia |
Pages J.,PAL Robotics |
Pfeiffer S.,PAL Robotics
2015 European Conference on Mobile Robots, ECMR 2015 - Proceedings | Year: 2015
People tracking is a key perception skill for mobile robots designed to share environments with human beings. It allows the robot to keep track of people around them, which is fundamental for two main reasons: safety and social interaction. This paper presents the work done on people tracking with the REEM robot after two years of paticipation at the RoboCup@home challenge. The main contribution of the paper is the tracker part, which is designed to be multi-target and to fuse heterogeneous detections from a variety of sensors, each one yielding different rates, field of views and quality performance. The paper carefully describes the tracker approach, based on multi-target particle filtering, as well as data association step, based on a probabilistic multi-hypothesis tree. Quantitative evaluations of real datasets using CLEAR MOT metrics are provided, comparing different sensor/detector set-ups and different data association approaches. © 2015 IEEE.
Pfeiffer S.,PAL Robotics |
Angulo C.,Polytechnic University of Catalonia
Pattern Recognition Letters | Year: 2015
A system for learning and executing gestures in a humanoid robot has been developed and implemented in this work. Gestures are represented via the use of dynamical movement primitives on the robotic platform REEM. Since agnostic knowledge is considered when designing trajectories, our approach can be easily extended to other robots. Implemented work involves recording of gestures using three different procedures, from the own robot, with the help of a user, and from external devices. Next, the dynamic movement primitives representing the motions are generated to describe trajectories that will finally be executed on the real humanoid robot. Several experiments are provided illustrating how knowledge is acquired by the robot, represented in the form of dynamical systems, generalized and reproduced from different starting conditions. © 2015 Elsevier B.V. All rights reserved.
Angulo C.,University of Pau and Pays de l'Adour |
Pfeiffer S.,PAL Robotics |
Tellez R.,Polytechnic University of Catalonia |
Alenya G.,Polytechnic University of Catalonia
Journal of Ambient Intelligence and Smart Environments | Year: 2015
We introduce robots as a tools to enhance Ambient Assisted Living (AAL) services. Robots are a unique opportunity to create new systems to cooperate in reaching better living conditions. Robots offer the possibility of richer interaction with humans, and can perform actions to actively change the environment. The current state-of-art includes skills in various areas, including advanced interaction (natural language, visual attention, object recognition, intention learning), navigation (map learning, obstacle avoidance), manipulation (grasping, use of tools), and cognitive architectures to handle highly unpredictable environments. From our experience in several robotics projects and principally in the RoboCup@Home competition, a new set of evaluation methods is proposed to assess the maturity of the required skills. Such comparison should ideally enable the abstraction from the particular robotic platform and concentrate on the easy comparison of skills. The validity of that low-level skills can be then scaled to more complex tasks, that are composed by several skills. Our conclusion is that effective evaluation methods can be designed with the objective of enabling robots to enlarge AAL services. © 2015 - IOS Press and the authors. All rights reserved.
Lanari L.,University of Rome La Sapienza |
Hutchinson S.,University of Illinois at Urbana - Champaign |
Marchionni L.,Pal Robotics
IEEE-RAS International Conference on Humanoid Robots | Year: 2015
It is in general complex to consider the complete robot dynamics when planning trajectories for bipedal locomotion. We present an approach to trajectory planning, with the classical Linear Inverted Pendulum Model (LIPM), that takes explicit consideration of the unstable dynamics. We derive a relationship between initial state and the control input that ensures the overall system dynamics will converge to a stable steady state solution. This allows us to exploit the unstable dynamics to achieve system goals, while imposing constraints on certain degrees of freedom of the input and initial conditions. Based on this, we propose an approach to trajectory planning, and derive solutions for several typical applications. Experimental simulations using the REEM-C biped robot platform of Pal Robotics validate our approach. © 2014 IEEE.
Puigbo J.-Y.,Polytechnic University of Catalonia |
Pumarola A.,Polytechnic University of Catalonia |
Tellez R.,Pal Robotics
CEUR Workshop Proceedings | Year: 2013
In this paper, a humanoid service robot is equipped with a set of simple action skills including navigating, grasping, recognizing objects or people, among others. By using those skills the robot has to complete a voice command in natural language that encodes a complex task (defined as the concatenation of several of those basic skills). To decide which of those skills should be activated and in which sequence no traditional planner has been used. Instead, the SOAR cognitive architecture acts as the reasoner that selects the current action the robot must do, moving it towards the goal. We tested it on a human size humanoid robot Reem acting as a general purpose service robot. The architecture allows to include new goals by just adding new skills (without having to encode new plans). Copyright © 2013 for the individual papers by the papers' authors.
Puigbo J.-Y.,University of Barcelona |
Pumarola A.,University of Barcelona |
Angulo C.,University of Barcelona |
Tellez R.,Pal Robotics
Connection Science | Year: 2015
A humanoid service robot equipped with a set of simple action skills including navigating, grasping, recognising objects or people, among others, is considered in this paper. By using those skills the robot should complete a voice command expressed in natural language encoding a complex task (defined as the concatenation of a number of those basic skills). As a main feature, no traditional planner has been used to decide skills to be activated, as well as in which sequence. Instead, the SOAR cognitive architecture acts as the reasoner by selecting which action the robot should complete, addressing it towards the goal. Our proposal allows to include new goals for the robot just by adding new skills (without the need to encode new plans). The proposed architecture has been tested on a human-sized humanoid robot, REEM, acting as a general purpose service robot. © 2015, © 2015 Taylor & Francis.
Carreras A.,University Pompeu Fabra |
Nur K.,University Pompeu Fabra |
Morenza-Cinos M.,University Pompeu Fabra |
Oliver J.,PAL ROBOTICS |
And 3 more authors.
UbiComp 2013 Adjunct - Adjunct Publication of the 2013 ACM Conference on Ubiquitous Computing | Year: 2013
Today's retail consumers' general behavior consists of doing the research for products preferably online while purchasing them offline. Users would like to access stores' inventories before going to the shop. This paper first identifies the challenges that need to be addressed to navigate within a store and its inventory anytime and anywhere without being physically there. Then, it analyzes the existing approaches for inventory management based on Radio Frequency Identification (RFID). And finally, it proposes a solution based on robots. We believe that this proposal is an important contribution to fill the gap between online and offline worlds in the context of retail. Copyright © 2013 ACM.
News Article | December 9, 2016
Suburban complexes in Sydney and Melbourne owned by property developer Stockland have just employed new shopping assistants to help the public with their Christmas shopping. The shopping centres are sharing prototypes of a social humanoid robot called Chip. The 100-kilo, 1.7-metre tall robots are more than happy to help with your shopping; they were developed by Spanish company PAL Robotics and are owned by the Commonwealth Bank. Each Chip is armed with a 12.1-inch touchscreen on its chest that can direct shoppers to stores that have sales, or show them the way to a particular shop. The robots also have the ability to carry shopping bags to the car. Chip has myriad cameras, lasers, ultrasound scanners, microphones and speakers installed that help with face recognition, and allow the robots to have conversations and answer questions. Stockland is the first company to use robotics in its shopping complexes in Australia, and the Merrylands centre in Western Sydney is the first to test the robot-human interaction. Students from five leading Australian technology universities have also been granted access to the social robotics technology in Chip, and have been given the opportunity to run experiments and conduct research. Robotic assistants are big business, with predictions being that the global robotics market will be worth AU$181 billion (US$135 billion) by 2019. Just a couple of months ago, JLL Australia introduced its newest robot receptionist called JiLL, a fully automated visitor management solution to greet visitors and couriers, and help staff with front-of-house tasks.