Enchaînements dynamiques de tâches pour des manipulateurs mobiles à roues

La nature des missions qui sont aujourd'hui envisagées en Robotique suppose de plus en plus un espace de travail étendu du robot. Cette extension va de pair avec la combinaison de moyens de manipulation et de moyens de locomotion et c'est la raison d'être des manipulateurs mobiles. Parmi ces systèmes, qui prennent des formes diverses, nous distinguons les manipulateurs mobiles à roues qui sont la combinaison d'une plateforme à roues et d'un bras manipulateur. Ce mémoire présente notre contribution à l'étude de leur commande coordonnée (le système est vu comme un tout) au niveau opérationnel et plus particulièrement en vue de missions complexes qui nécessitent l'enchaînement dynamique de tâches de natures différentes : suivi de trajectoire, contrˆole d'effort. En nous basant sur la forme générique des modèles cinématiques de ces systèmes, nous avons développé un modèle dynamique unifié, directement exploitable pour les techniques de commande à couple calculé. Afin de tenir compte des contraintes secondaires intrinsèques à tout système robotique mais aussi des contraintes imposées par l'environnement (obstacles par exemple), nous proposons une structure de commande qui permet l'intégration des lois de commande opérationnelle tout en assurant, notamment grâce à l'exploitation de la redondance du système, le respect des différentes contraintes. Cette structure gère l'enchaînement dynamique des tâches à réaliser et permet, qu'elles soient planifiées ou générés en temps réel, l'adaptation des consignes pour la gestion des incertitudes sur la connaissance de l'environnement mais aussi sur le déroulement de la mission. L'approche proposée a été validée en simulation et expérimentalement sur le robot H2Bis+GT6A de l'équipe RIA du LAAS. ABSTRACT : Nowadays, robotics missions induce large workspaces of the robots. This extension explains the growing usage of mobile manipulators which are systems combining a mobile platform and means of manipulation. Among those systems that can take various shapes, we distinguish wheeled mobile manipulators which are systems combining a wheeled mobile platform and a manipulator arm. This PhD thesis report presents our contribution to the coordinated control of this kind of system, at an operational level, within the framework of complex missions execution based on the dynamic sequencing of tasks whose natures are different : motion, force. Using generic kinematics models of these systems, we have developed a unified dynamic model which can be used for control purpose (computed torque). We also propose a structure allowing the integration of operational control laws and ensuring the respect of secondary constraints inherent to the system or induced by the environment (obstacles for example). This structure manages the tasks sequencing and permits the reactive adaptation of the desired trajectories (that are planned or generated in real time) in order to handle uncertainties. This approach was validated in simulation but also using robot H2Bis+GT6A of the LAAS laboratory in Toulouse

Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study

Accurate post-impact velocity predictions are essential in developing impact-aware manipulation strategies for robots, where contacts are intentionally established at non-zero speed mimicking human manipulation abilities in dynamic grasping and pushing of objects. Starting from the recorded dynamic response of a 7DOF torque-controlled robot that intentionally impacts a rigid surface, we investigate the possibility and accuracy of predicting the post-impact robot velocity from the pre-impact velocity and impact configuration. The velocity prediction is obtained by means of an impact map, derived using the framework of nonsmooth mechanics, that makes use of the known rigid-body robot model and the assumption of a frictionless inelastic impact.The main contribution is proposing a methodology that allows for a meaningful quantitative comparison between the recorded post-impact data, that exhibits a damped oscillatory response after the impact, and the post-impact velocity prediction derived via the readily available rigid-body robot model, that presents no oscillations and that is the one typically obtained via mainstream robot simulator software. The results of this new approach are promising in terms of prediction accuracy and thus relevant for the growing field of impact-aware robot control. The recorded impact data (18 experiments) is made publicly available, together with the numerical routines employed to generate the quantitative comparison, to further stimulate interest/research in this field

Task Feasibility Maximization using Model-Free Policy Search and Model-Based Whole-Body Control

Producing feasible motions for highly redundant robots, such as humanoids, is a complicated and high-dimensional problem.Model-based whole-body control of such robots, can generate complex dynamic behaviors through the simultaneous execution of multiple tasks.Unfortunately, tasks are generally planned without close consideration for the underlying controller being used, or the other tasks being executed, and are often infeasible when executed on the robot. Consequently, there is no guarantee that the motion will be accomplished.In this work, we develop an optimization loop which automatically improves task feasibility using model-free policy search in conjunction with model-based whole-body control.This combination allows problems to be solved, which would be otherwise intractable using simply one or the other.Through experiments on both the simulated and real iCub humanoid robot, we show that by optimizing task feasibility, initially infeasible complex dynamic motions can be realized --- specifically, a sit-to-stand transition

Predicting the post-impact velocity of a robotic arm

Starting from the recorded dynamic response of a 7DOF torque-controlled robot while intentionally impacting a rigid surface, we investigate the possibility of predicting the post-impact robot velocity from the ante-impact velocity and configuration. The velocity prediction is obtained by means of an impact map, derived using the framework of nonsmooth mechanics, that makes use of the known rigid-body robot model and the assumption of a frictionless inelastic impact. The main contribution is proposing a methodology that allows for a meaningful quantitative comparison between the recorded post-impact data, that exhibits a damped oscillatory response after the impact, and the post-impact velocity prediction derived via the rigid-body robot model, that presents no oscillations. The results of this approach are promising and the recorded impact data (18 experiments) is made publicly available, together with the numerical routines employed to generate the quantitative comparison, to further stimulate research in this field

Assessment of physical exposure to musculoskeletal risks in collaborative robotics using dynamic simulation

Many industrial tasks cannot be executed by a robot alone. A way to help workers in order to decrease the risk of musculoskeletal disorders is to assist them with a collaborative robot. Yet assessing its usefulness to the worker remains costly because it usually requires a prototype. We propose a dynamic simulation framework to model the performing of a task jointly by a virtual manikin and a robot. It allows to measure physical quantities in order to perform an ergonomic assessment of the robot. Experiments are carried out on two different robots. The results show that the proposed simulation framework is helpful for designing collaborative robots. Further work includes enhancing the simulation realism and validation on a real robot

Online velocity constraint adaptation for safe and efficient human-robot workspace sharing

Despite the many advances in collaborative robotics, collaborative robot control laws remain similar to the ones used in more standard industrial robots, significantly reducing the capabilities of the robot when in proximity to a human. Improving the efficiency of collaborative robots requires revising the control approaches and modulating online and in real-time the low-level control of the robot to strictly ensure the safety of the human while guaranteeing efficient task realization. In this work, an openly simple and fast optimization based joint velocity controller is proposed which modulates the joint velocity constraints based on the robot's braking capabilities and the separation distance. The proposed controller is validated on the 7 degrees-of-freedom Franka Emika Panda collaborative robot

Simulation Study of the Upper-limb Wrench Feasible Set with Glenohumeral Joint Constraints

The aim of this work is to improve musculoskeletal-based models of the upper-limb Wrench Feasible Set i.e. the set of achievable maximal wrenches at the hand for applications in collaborative robotics and computer aided ergonomics. In particular, a recent method performing wrench capacity evaluation called the Iterative Convex Hull Method is upgraded in order to integrate non dislocation and compression limitation constraints at the glenohumeral joint not taken into account in the available models. Their effects on the amplitude of the force capacities at the hand, glenohumeral joint reaction forces and upper-limb muscles coordination in comparison to the original iterative convex hull method are investigated in silico. The results highlight the glenohumeral potential dislocation for the majority of elements of the wrench feasible set with the original Iterative Convex Hull method and the fact that the modifications satisfy correctly stability constraints at the glenohumeral joint. Also, the induced muscles coordination pattern favors the action of stabilizing muscles, in particular the rotator-cuff muscles, and lowers that of known potential destabilizing ones according to the literature.Comment: 30 pages (double spacing), 10 figures, 2 table

Automatic selection of ergonomic indicators for the design of collaborative robots: a virtual-human in the loop approach

Conference of 2014 14th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014 ; Conference Date: 18 November 2014 Through 20 November 2014; Conference Code:112990International audienceThe growing number of musculoskeletal disorders in industry could be addressed by the use of collaborative robots, which allow the joint manipulation of objects by both a robot and a person. Designing these robots requires to assess the ergonomic benefit they offer. However there is a lack of adapted assessment methods in the literature. Many biomechanical quantities can represent the physical solicitations to which the worker is exposed, but their relevance strongly depends on the considered task. This paper presents a method to automatically select relevant ergonomic indicators for a given task to be performed with a collaborative robot. A virtual human simulation is used to estimate thirty indicators for varying human and robot features. A variance-based analysis is then conducted to extract the most discriminating indicators. The method is validated on several different tasks. The relevance of the proposed approach is confirmed by the obtained results

On-line force capability evaluation based on efficient polytope vertex search

International audienceEllipsoid-based manipulability measures are often used to characterize the force/velocity task-space capabilities of robots. While computationally simple, this approach largely approximate and underestimate the true capabilities. Force/velocity polytopes appear to be a more appropriate representation to characterize the robot's task-space capabilities. However, due to the computational complexity of the associated vertex search problem, the polytope approach is mostly restricted to offline use, e.g. as a tool aiding robot mechanical design, robot placement in work-space and offline trajectory planning. In this paper, a novel on-line polytope vertex search algorithm is proposed. It exploits the parallelotope geometry of actuator constraints. The proposed algorithm significantly reduces the complexity and computation time of the vertex search problem in comparison to commonly used algorithms. In order to highlight the on-line capability of the proposed algorithm and its potential for robot control, a challenging experiment with two collaborating Franka Emika Panda robots, carrying a load of 12 kilograms, is proposed. In this experiment, the load distribution is adapted on-line, as a function of the configuration dependant task-space force capability of each robot, in order to avoid, as much as possible, the saturation of their capacit