Planification de trajectoire pour la manipulation d'objets et l'interaction homme-robot

Le contexte de la robotique de service est caractérisé par la présence de l'homme dans l'espace de travail du robot. Les mouvements de ces robots ne doivent perturber ni la sécurité de l'homme ni son confort. D'un point de vu planification de mouvement, le planificateur doit d'une part éviter de heurter l'homme ou l'environnement et d'autre part adapter les limites cinématiques du robot en fonction de la proximité de l'homme. A chaque niveau du système (planification et exécution/contrôle), le robot doit garantir la sécurité et le confort de l'homme. Nous proposons une approche de la planification et du contrôle de mouvement basée sur des trajectoires polynomiales. Dans une première partie, nous présentons un générateur de trajectoires qui limite la vitesse, l'accélération et le jerk. Il génère des trajectoires composées de suites de segments de courbes cubiques. Le cas mono-dimensionnel est d'abord présenté puis étendu au cas multi-dimensionnel. Dans une deuxième partie, nous proposons d'approximer les trajectoires par des suites de triplets de segments de courbes cubiques. Cette méthode permet de calculer des trajectoires respectant une erreur maximale donnée. Ces générateurs de trajectoire sont intégrés au planificateur de chemin et produisent des trajectoires directement exécutables. Une application originale de l'approximation permet d'approximer une trajectoire définie dans l'espace cartésien par une trajectoire définie dans l'espace articulaire. Cette approche simplifie la structure du contrôleur du robot. La présence de l'homme dans l'espace de travail du robot nécessite une adaptation des trajectoires pendant l'exécution. Nous proposons une méthode pour adapter la loi de mouvement de la trajectoire multidimensionnelle pendant l'exécution. Ces travaux, menés dans le cadre du projet européen DEXMART et du projet ANR ASSIST, ont été intégrés et validés sur les plateformes Jido et PR2 du LAAS-CNRS.The context of service robotics is characterized by the presence of humans in the vicinity of the robot. The movements of these robots should not disturb the safety of humans or their comfort. From the motion planning point of view, the planner must both avoid hitting humans or colliding with the environment and also adapt the robot's kinematic limits depending on the proximity of humans. At each level of the system (Planning and execution / Control), the robot must ensure the safety and the comfort of humans. We propose an approach of motion planning and motion control based on polynomial trajectories. In the first part, we present a trajectory generator which limits the speed, the acceleration and the jerk (derivative of the acceleration). The motion planner generates trajectories consisting of series of segments of cubic polynomial curves. The mono-dimensional case is first introduced and then extended to the multi-dimensional one. In the second part, we propose to approximate the trajectories by sequences of triplets of segments of cubic curves. This method allows to find trajectories that respect a given maximum error. These trajectory generators are integrated into the path planner and produce directly executable motion. An original application of the trajectory approximation is the approximation of a trajectory defined in Cartesian space by a trajectory defined in the joint space. This approach simplifies the structure of the robot controller. The presence of humans in the workspace of the robot requires also an adaptation of the trajectories during the execution. We propose a method to adapt the motion law of the multidimensional path at runtime. This work, conducted as part of the European project DEXMART and the ANR project ASSIST, has been integrated and validated on the Jido and PR2 platforms of LAAS-CNRS

Soft Motion Trajectory Planner for Service Manipulator Robot

Human interaction introduces two main constraints: Safety and Comfort. Therefore service robot manipulator can't be controlled like industrial robotic manipulator where personnel is isolated from the robot's work envelope. In this paper, we present a soft motion trajectory planner to try to ensure that these constraints are satisfied. This planner can be used on-line to establish visual and force control loop suitable in presence of human. The cubic trajectories build by this planner are good candidates as output of a manipulation task planner. The obtained system is then homogeneous from task planning to robot control. The soft motion trajectory planner limits jerk, acceleration and velocity in cartesian space using quaternion. Experimental results carried out on a Mitsubishi PA10-6CE arm are presented

Planification de trajectoire pour la manipulation d'objets et l'interaction Homme-robot

The context of service robotics is characterized by the presence of humans in the vicinity of the robot. The movements of these robots should not disturb the safety of humans or their comfort. From the motion planning point of view, the planner must both avoid hitting humans or colliding with the environment and also adapt the robot's kinematic limits depending on the proximity of humans. At each level of the system (Planning and execution / Control), the robot must ensure the safety and the comfort of humans. We propose an approach of motion planning and motion control based on polynomial trajectories. In the first part, we present a trajectory generator which limits the speed, the acceleration and the jerk (derivative of the acceleration). The motion planner generates trajectories consisting of series of segments of cubic polynomial curves. The mono-dimensional case is first introduced and then extended to the multi-dimensional one. In the second part, we propose to approximate the trajectories by sequences of triplets of segments of cubic curves. This method allows to find trajectories that respect a given maximum error. These trajectory generators are integrated into the path planner and produce directly executable motion. An original application of the trajectory approximation is the approximation of a trajectory defined in Cartesian space by a trajectory defined in the joint space. This approach simplifies the structure of the robot controller. The presence of humans in the workspace of the robot requires also an adaptation of the trajectories during the execution. We propose a method to adapt the motion law of the multidimensional path at runtime. This work, conducted as part of the European project DEXMART and the ANR project ASSIST, has been integrated and validated on the Jido and PR2 platforms of LAAS-CNRS.Le contexte de la robotique de service est caractérisé par la présence de l'homme dans l'espace de travail du robot. Les mouvements de ces robots ne doivent perturber ni la sécurité de l'homme ni son confort. D'un point de vu planification de mouvement, le planificateur doit d'une part éviter de heurter l'homme ou l'environnement et d'autre part adapter les limites cinématiques du robot en fonction de la proximité de l'homme. A chaque niveau du système (planification et exécution/contrôle), le robot doit garantir la sécurité et le confort de l'homme. Nous proposons une approche de la planification et du contrôle de mouvement basée sur des trajectoires polynomiales. Dans une première partie, nous présentons un générateur de trajectoires qui limite la vitesse, l'accélération et le jerk. Il génère des trajectoires composées de suites de segments de courbes cubiques. Le cas mono-dimensionnel est d'abord présenté puis étendu au cas multi-dimensionnel. Dans une deuxième partie, nous proposons d'approximer les trajectoires par des suites de triplets de segments de courbes cubiques. Cette méthode permet de calculer des trajectoires respectant une erreur maximale donnée. Ces générateurs de trajectoire sont intégrés au planificateur de chemin et produisent des trajectoires directement exécutables. Une application originale de l'approximation permet d'approximer une trajectoire définie dans l'espace cartésien par une trajectoire définie dans l'espace articulaire. Cette approche simplifie la structure du contrôleur du robot. La présence de l'homme dans l'espace de travail du robot nécessite une adaptation des trajectoires pendant l'exécution. Nous proposons une méthode pour adapter la loi de mouvement de la trajectoire multidimensionnelle pendant l'exécution. Ces travaux, menés dans le cadre du projet européen DEXMART et du projet ANR ASSIST, ont été intégrés et validés sur les plateformes Jido et PR2 du LAAS-CNRS

An Attentional Approach to Human–Robot Interactive Manipulation

Human robot collaborative work requires interactive manipulation and object handover. During the execution of such tasks, the robot should monitor manipulation cues to assess the human intentions and quickly determine the appropriate execution strategies. In this paper, we present a control architecture that combines a supervisory attentional system with a human aware manipulation planner to support effective and safe collaborative manipulation. After detailing the approach, we present experimental results describing the system at work with different manipulation tasks (give, receive, pick, and place)

Human Robot Interaction

To interact with humans, robots will possess a software architecture much more complete than current robots and be equipped with new functionalities. The purpose of this chapter is to introduce some necessary elements to build companion robots that interact physically with humans and particularly for the exchange of object tasks. To obtain soft motion acceptable by humans, we use trajectories represented by cubic functions of time that allow mastering and limiting velocity, acceleration and jerk of the robot in the vicinity of the humans. During a handover task and to adapt its trajectory to the human behavior, the robot must adjust the time motion law and the path of the trajectory in real time. The necessity of real time planning is illustrated by the task of exchanging an object and in particular by the planning of double grasps. The robot has to choose dynamically a consistent grasp that enables both robot and human to hold simultaneously the exchanged object. Then, we present a robotic control system endowed with attentional models and mechanisms suitable for balancing the trade-off between safe human-robot interaction (HRI) and effective task execution. In particular, these mechanisms allow the robot to increase or decrease the degree of attention toward relevant activities modulating the frequency of the monitoring rate and the speed associated to the robot movements. In this attentional framework, we consider pick-and-place and give-and-receive attentional behaviors. To assess the system performances we introduce suitable evaluation criteria taking into account safety, reliability, efficiency, and effectiveness

Synthesizing Robot Motions Adapted to Human Presence

International audienceWith robotics hardware becoming more and more safe and compliant, robots are not far from entering our homes. The robot, that will share the same environment with humans, will be expected to consider the geometry of the interaction and to perform intelligent space sharing.In this case, even the simplest tasks, e.g. handing over an object to a person, raise important questions such as: where the task should be achieved?; how to place the robot relatively to the human in order to ease the human action?; how to hand over an object?; and more generally, how to move in a relatively constrained environment in the presence of humans?In this paper we present an integrated motion synthesis framework from planning to execution that is especially designed for a robot that interacts with humans. This framework, composed of Perspective Placement, Human Aware Manipulation Planner and Soft Motion Trajectory Planner, generates robot motions by taking into account human’s safety; his vision field and his perspective; his kinematics and his posture along with the task constraints