Vers la modélisation d’une classe de robots mobiles manipulateurs bioniques

Ce travail concerne une catégorie de robot mobile manipulateur omnidirectionnel bionique, en l’occurence le RobotinoXT qui dispose d’un manipulateur bionique CBHA monté sur un robot mobile omnidirectionnel, nommée Robotino. D’abord, nous avons proposé un modèle cinématique direct de ce système en utilisant une méthode nommée « arc geometry ». Celle-ci a été validée grâce à un banc d’expérimentation en ayant recours à une technique de trilatération. Pour atteindre cet objectif, les capteurs ont été calibrés. Concernant le problème de calibration des paramètres constants du modèle, il a été résolu en développant un algorithme d’optimisation incluant une méthode nommée SQP, validée via un manipulateur industriel à bras rigides. Puis, nous avons proposé un modèle cinématique inverse du CBHA en supposant que chaque vertèbre de celui-ci est assimilée à un robot parallèle. Ce modèle a été validé par les mesures réelles obtenues avec le manipulateur industriel, permettant la définition de l’espace de travail du robot. Enfin, nous avons implémenté une boîte à outils qui englobe les modèles développés dans ce travail.This work deals with a particular class of mobile omnidrive-bionic manipulator robot namely RobotinoXT. It contains a bionic manipulator Compact Bionic Handling Assistant (CBHA) mounted over a mobile omnidrive robot Robotino. We first proposed a forward kinematic model of such a system by using an “arc geometry” method which was validated through a test bench using a trilateration technique. To achieve this purpose, the sensors were calibrated. For the model’s constant parameters calibration problem, this latter was resolved by developing an optimization algorithm which incorporates a SQP method, validated via an industrial manipulator with rigid links. Then, we proposed an inverse kinematic model of the CBHA by assuming that each backbone of it, is assimilated to a parallel robot. This model was validated by real measurements obtained with the industrial manipulator, allowing defining the robot workspace. Finally, we implemented a toolbox which encompasses the models developed in this work

Kinematic Calibration of a Multisection Bionic Manipulator

International audience—This paper deals with the forward kinematic calibration of a bionic arm inspired from the organic elephant trunk and called compact bionic handling assistant (CBHA). First, a forward kinematic model is developed based on the principle of the constant curvature continuum robot theory. Then, two experimental setups are proposed in order to carry out the model calibration and validation. The first one is based on the trilateration method, while the second one is based on the coupling of the CBHA with a rigid six-degree-of-freedom rigid manipulator. The aim of the calibration is to enhance the precision of the forward kinematic model

Inverse Kinematic modeling of a class of continuum bionic handling arm

International audience— This paper presents a development of Inverse Kinematic Model (IKM) of a class of Continuum Bionic Handling Arm (CBHA). The modeling approach is inspired from a model of a hyper-redundant backbone-based manipulator, combined with an optimal placement of the backbones. The latter is obtained using an optimization algorithm, based on a Sequential Quadratic Program (SQP). The main interest of developing such model is to design an autonomous control of the CBHA. The high number of Degrees of Freedom (DoF) present on the continuum structure of the CBHA, makes difficult the synthesis of the analytical IKM for the overall arm. To resolve this issue, it is proposed to assimilate the CBHA's behavior to that of a hyper-redundant robot manipulator. This robot is represented by a concatenation of hybrid (parallel and serial) vertebrae along the vertebral column or backbones of the CBHA. The combination of all these vertebra allows the reconstruction with optimal configuration of the real posture of the continuum arm inside its workspace, with only the knowledge of the Cartesian coordinates of the robot pose. Simulations and experimental validation of the model demonstrate the efficiency of the modeling approach for this class of CBHA

On the Kinematic Modeling of a Class of Continuum Manipulators

International audience— This paper addresses the forward kinematic model (FKM) of a continuum manipulator, namely the Compact Bionic Handling Assistant (CBHA). This model is an essential step in the design of an autonomous robot control. The CBHA is considered as a concatenation of three degrees of freedom (DoF) parallel robot with 3UPS-1UP (Universal-Prismatic-Spherical) joint structure along the backbone. A mathematical solution of the inverse kinematic problem of such manipulators is easy to derive; however, the forward kinematic problem is mathematically intractable. Therefore, a FKM of the CBHA based on the IKM of each parallel robot is proposed. A neural-network-based hybrid approach that solves the FKM with a good degree of accuracy is developed in this paper. The proposed approach is validated by real measurements obtained by using an industrial manipulator (Kuka) as an external sensor. A comparison with a quantitative geometric approach, according to the model accuracy is also presented

On the Kinematic Modeling of a Class of Continuum Manipulators

International audience— This paper addresses the forward kinematic model (FKM) of a continuum manipulator, namely the Compact Bionic Handling Assistant (CBHA). This model is an essential step in the design of an autonomous robot control. The CBHA is considered as a concatenation of three degrees of freedom (DoF) parallel robot with 3UPS-1UP (Universal-Prismatic-Spherical) joint structure along the backbone. A mathematical solution of the inverse kinematic problem of such manipulators is easy to derive; however, the forward kinematic problem is mathematically intractable. Therefore, a FKM of the CBHA based on the IKM of each parallel robot is proposed. A neural-network-based hybrid approach that solves the FKM with a good degree of accuracy is developed in this paper. The proposed approach is validated by real measurements obtained by using an industrial manipulator (Kuka) as an external sensor. A comparison with a quantitative geometric approach, according to the model accuracy is also presented