54documents trouvés
Human interaction with motion planning algorithm
M.TAIX, D.FLAVIGNE, E.FERRE
GEPETTO, ISIR, Jussieu, Kineo
Revue Scientifique : Journal of Intelligent & Robotic Systems, Vol.67, N°3-4, pp.285-306, Septembre 2012 , N° 12146
Lien : http://hal.archives-ouvertes.fr/hal-00668407
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Abstract
This paper presents an interactive motion planning system to compute free collision motion in a numerical model. The system is based on interaction between a user and a motion planning algorithm. On one hand the user moves the object with an interactive device and on the other hand a motion planning algorithm searches a solution in the configuration space. The interaction aims at improving the guidance of an operator during a robot motion task in a virtual environment with the help of an automatic path planning algorithm. Existing works use a two-step decomposition which limits the interaction between the user and the ongoing process. We propose a modification of a classic motion planning method, the Rapidly-exploring Random Tree to build an Interactive-RRT. This method is based on exchanging pseudo-forces between the algorithm and the user, and on data gathering (labels) from the virtual scene. Examples are shown to illustrate the Interactive motion planning system with different interactive devices (space mouse and haptic arm). We analyze the influence of the user's dexterity to find a solution depending on various parameters of the algorithm and we show how we can adapt these parameters to a user.
Optimal motion planning for humanoid robots
A.EL KHOURY, F.LAMIRAUX, M.TAIX
GEPETTO
Rapport LAAS N°12383, Juillet 2012, 7p.
Lien : http://hal.archives-ouvertes.fr/hal-00715419
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127723Nao: fundamental support to Master's student projects
M.TAIX, C.BRIAND, P.TRUILLET, A.DE BONNEVAL, I.FERRANE, J.PINQUIER
GEPETTO, MOGISA, IRIT-UPS, TSF
Manifestation sans acte : Nao Tech Day, paris (France), 13 Juin 2012, 25p. , N° 12402
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127784Apport de la simulation interactive et de la planification de chemins dans le domaine industriel
M.TAIX, J.Y.FOURQUET
GEPETTO, ENIT Tarbes
Conférence invitée : Colloque National AIP-PRIMECA 2012 du 27 mars au 30 mars 2012, Mont-Dore (France), Mars 2012, 16p. , N° 12644
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128714Aide à la personne dépendante: comment un robot humanoïde NAO peut jouer un rôle principal
M.TAIX, C.BRIAND, P.TRUILLET, A.DE BONNEVAL, I.FERRANE, P.GRANDJEAN, J.PINQUIER
GEPETTO, MOGISA, IRIT-UPS, TSF, ASTRIUM
Manifestation avec acte : Colloque National AIP-PRIMECA, Mont-Dore (France), 28-30 Mars 2012, 10p. , N° 12254
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127246Dynamic walking makes humanoid robot small-space controllable: application to motion planning
S.DALIBARD, A.EL KHOURY, F.LAMIRAUX, M.TAIX, J.P.LAUMOND
GEPETTO
Rapport LAAS N°11697, Décembre 2011, 21p.
Lien : http://hal.archives-ouvertes.fr/hal-00654175
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This paper presents a general method for planning collision-free whole-body walking motions for humanoid robots. First, we present a randomized algorithm for constrained motion planning, that is used to generate collision-free statically balanced paths solving manipulation tasks. Then, we show that dynamic walking makes humanoid robots small-space controllable. Such a property allows to easily transform collision-free statically balanced paths into collision-free dynamically balanced trajectories. It leads to a sound algorithm which has been applied and evaluated on several problems where whole-body planning and walk are needed, and the results have been validated on a real HRP-2 robot.
A General Framework for Planning Landmark-Based Motions for Mobile Robots
A.C.MALTI, F.LAMIRAUX, M.TAIX
GEPETTO
Revue Scientifique : Advanced Robotics, Vol.25, N°11-12, pp.1427-1450, Novembre 2011 , N° 09670
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128053Small-space controllability of a walking humanoid robot
S.DALIBARD, A.EL KHOURY, F.LAMIRAUX, M.TAIX, J.P.LAUMOND
GEPETTO
Manifestation avec acte : IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS 2011), Bled (Slovénie) , 26-28 Octobre 2011, pp.739-744 , N° 11367
Lien : http://hal.archives-ouvertes.fr/hal-00602384/fr/
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This paper presents a two-stage motion planner for walking humanoid robots. A first draft path is computed using random motion planning techniques that ensure collision avoidance. In a second step, the draft path is approximated by a whole-body dynamically stable walk trajectory. The contributions of this work are: (i) a formal guarantee, based on smalltime controllability criteria, that the first draft path can be approximated by a collision-free dynamically stable trajectory; (ii) an algorithm that uses this theoretical property to find a solution trajectory. We have applied our method on several problems where whole-body planning and walk are needed, and the results have been validated on a real platform: the robot HRP-2.
Interactive locomotion animation using path planning
D.FLAVIGNE, M.TAIX
ISIR, Jussieu, GEPETTO
Manifestation avec acte : Emerging Technologies and Factory Automation (ETFA'2011), Toulouse (France), 5-9 Septembre 2011, 8p. , N° 11248
Lien : http://hal.archives-ouvertes.fr/hal-00592226/fr/
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Abstract
This paper presents a method aimed at enhancing interaction between a path planning algorithm and a user to guide a robot motion task in a virtual environment. Existing works use a two-step decomposition which limits the interaction between the user and the ongoing process. We propose a modification of a classic motion planning method, the Rapidly-exploring Random Tree to build a Interactive-RRT. This method is based on exchanging forces between the algorithm and the user, and on data gathering (labels) from the virtual scene. The Interactive- RRT is combined with a locomotion controller and then applied to a virtual character for generating a locomotion movement along a path suggested by the user.
Path optimization for humanoid walk planning: an efficient approach
A.EL KHOURY, M.TAIX, F.LAMIRAUX
GEPETTO
Manifestation avec acte : International Conference on Informatics in Control Automation and Robotics (ICINCO 2011), Noordwijkerout (Pays Bas), 28-31 Juillet 2011, 6p. , N° 11399
Lien : http://hal.archives-ouvertes.fr/hal-00572375/fr/
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This paper deals with humanoid walk planning in cluttered environments. It presents a heuristic and efficient optimization method that takes as input a path computed for the robot bounding box, and produces a path where a discrete set of configurations is reoriented using an A* search algorithm. The resulting trajectory is realistic and time-optimal. This method is validated in various scenarios on the humanoid robot HRP-2.