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.
Angulo C.,University of Pau and Pays de lAdour |
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.
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.
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.
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.