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ABSTRACT: Humanoid robotics is a field of a great research interest nowadays. This work implements a low-cost teleoperated system to control a humanoid robot, as a first step for further development and study of human motion and walking. A human suit is built, consisting of 8 sensors, 6 resistive linear potentiometers on the lower extremities and 2 digital accelerometers for the arms. The goal is to replicate the suit movements in a small humanoid robot. The data from the sensors is wirelessly transmitted via two ZigBee RF configurable modules installed on each device: the robot and the suit. Replicating the suit movements requires a robot stability control module to prevent falling down while executing different actions involving knees flexion. This is carried out via a feedback control system with an accelerometer placed on the robot's back. The measurement from this sensor is filtered using Kalman. In addition, a two input fuzzy algorithm controlling five servo motors regulates the robot balance. The humanoid robot is controlled by a medium capacity processor and a low computational cost is achieved for executing the different algorithms. Both hardware and software of the system are based on open platforms. The successful experiments carried out validate the implementation of the proposed teleoperated system.
Sensors 01/2013; 13(2):1385-401. · 1.74 Impact Factor
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Robotics and Autonomous Systems. 01/2010; 58:991-1002.
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IEEE Transactions on Intelligent Transportation Systems. 01/2009; 10:440-452.
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2009 IEEE International Conference on Robotics and Automation, ICRA 2009, Kobe, Japan, May 12-17, 2009; 01/2009
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Computer Aided Systems Theory - EUROCAST 2007, 11th International Conference on Computer Aided Systems Theory, Las Palmas de Gran Canaria, Spain, February 12-16, 2007, Revised Selected Papers; 01/2007
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2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 29 - November 2, 2007, Sheraton Hotel and Marina, San Diego, California, USA; 01/2007
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Computer Aided Systems Theory - EUROCAST 2007, 11th International Conference on Computer Aided Systems Theory, Las Palmas de Gran Canaria, Spain, February 12-16, 2007, Revised Selected Papers; 01/2007
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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006, October 9-15, 2006, Beijing, China; 01/2006
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IEEE Transactions on Intelligent Transportation Systems. 01/2006; 7:63-77.
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2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006, October 9-15, 2006, Beijing, China; 01/2006
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Auton. Robots. 01/2005; 19:67-87.
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Journal of Intelligent and Robotic Systems. 01/2004; 40:233-265.
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The 21st IASTED International Multi-Conference on Applied Informatics (AI 2003), February 10-13, 2003, Innsbruck, Austria; 01/2003
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ESANN 2000, 8th European Symposium on Artificial Neural Networks, Bruges, Belgium, April 26-28, 2000, Proceedings; 01/2000
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ABSTRACT: The increasing number of traffic accidents due to driver inattention has become a serious problem for society. Every year,
about 45,000 people die and 1.5 million people are injured in traffic accidents in Europe. These figures imply that one person
out of every 200 European citizens is injured in a traffic accident every year and that around one out 80 European citizens
dies 40 years short of the life expectancy. It is known that the great majority of road accidents (about 90-95%) are caused
by human error. More recent data has identified inattention (including distraction and falling asleep at the wheel) as the
primary cause of accidents, accounting for at least 25% of the crashes [15]. Road safety is thus a major European health problem.
In the “White Paper on European Transport Policy for 2010”, the European Commission declares the ambitious objective of reducing
by 50% the number of fatal accidents on European roads by 2010 (European Commission, 2001).
01/1970: pages 25-51;
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ABSTRACT: This paper presents a new real-time hierarchical (topological/metric) localization system applied to the robust self-location of a vehicle in large-scale urban environments. Our proposal improves the current vehicle navigation systems based only on GPS sensor. It is exclusively based on the information provided by both, a low-cost wide-angle stereo camera and a low-cost GPS. A low level metric process obtains a 3D sequential mapping of natural landmarks and the vehicle location/orientation. GPS measurements are integrated within this low level, improving vehicle positioning. A higher topological processing level, based on fingerprints and the multi level relaxation (MLR) algorithm, has been added to reduce the global error keeping real-time constraints. Some experimental tests, using a real car navigation system on urban environments with loop closures, have been carried out. Main results and conclusions are presented.
Signal Processing.
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ABSTRACT: In this paper we present a new real-time hierarchical (topological/metric) Visual SLAM system focusing on the localization of a vehicle in large-scale outdoor urban environments. It is exclusively based on the visual information provided by a cheap wide-angle stereo camera. Our approach divides the whole map into local sub-maps identified by the so-called fingerprints (vehicle poses). At the sub-map level (low level SLAM), 3D sequential mapping of natural landmarks and the robot location/orientation are obtained using a top-down Bayesian method to model the dynamic behavior. A higher topological level (high level SLAM) based on fingerprints has been added to reduce the global accumulated drift, keeping real-time constraints. Using this hierarchical strategy, we keep the local consistency of the metric sub-maps, by mean of the EKF, and global consistency by using the topological map and the MultiLevel Relaxation (MLR) algorithm. Some experimental results for different large-scale outdoor environments are presented, showing an almost constant processing time.
Robotics and Autonomous Systems.
