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

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

International audienceProducing 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

Modular House Revival

The Modular House, located in Poly Canyon, has seen extensive damage since the last caretaker left nearly ten years ago. To prevent further damage and improve the safety and appeal of the structure, we are proposing a renovation of the existing building that removes the existing cladding and partitions. By the end of Spring Quarter 2017, the Modular House will have a guardrail system replacing the wood paneling on the walls and a new steel composite deck to replace the current flooring system. The structural steel framing system will remain as is

Modular House Project Narrative

The Modular House, located in Poly Canyon, has seen extensive damage since the last caretaker left nearly ten years ago. To prevent further damage and improve the safety and appeal of the structure, we are proposing a renovation of the existing building that removes the existing cladding and partitions. By the end of Spring Quarter 2017, the Modular House will have a guardrail system replacing the wood paneling on the walls and a new steel composite deck to replace the current flooring system. The structural steel framing system will remain as is

The CoDyCo Project achievements and beyond: Towards Human Aware Whole-body Controllers for Physical Human Robot Interaction

International audienceThe success of robots in real-world environments is largely dependent on their ability to interact with both humans and said environment. The FP7 EU project CoDyCo focused on the latter of these two challenges by exploiting both rigid and compliant contacts dynamics in the robot control problem. Regarding the former, to properly manage interaction dynamics on the robot control side, an estimation of the human behaviours and intentions is necessary. In this paper we present the building blocks of such a human-in-the-loop controller, and validate them in both simulation and on the iCub humanoid robot using a human-robot interaction scenario. In this scenario, a human assists the robot in standing up from being seated on a bench

Compatibilité des tâches et maximisation de la faisabilité pour le contrôle de l'ensemble du corps

Producing useful behaviors on complex robots, such as humanoids, is a challenging undertaking. Model-based whole-body control alleviates some of this difficulty by allowing complex whole-body motions to be broken up into multiple atomic tasks, which are performed simultaneously on the robot. However, modeling errors and assumptions, made during task planning, often result in infeasible and/or incompatible task combinations when executed on the robot. Consequently, there is no guarantee that the prescribed tasks will be accomplished, resulting in unpredictable, and most likely, unsafe whole-body motions. The objective of this work is to better understand what makes tasks infeasible or incompatible, and develop automatic methods of improving on these two issues so that the overall whole-body motions may be accomplished as planned. We start by building a concrete analytical formalism of what it means for tasks to be feasible with the control constraints and compatible with one another. Using the model-based feasibility and compatibility metrics, we demonstrate how the tasks can be optimized using non-linear model predictive control, while also detailing the shortcomings of this model-based approach. In order to overcome these weaknesses, an optimization loop is designed, which automatically improves task feasibility and compatibility using model-free policy search in conjunction with model-based whole-body control. Through a series of simulated and real-world experiments, we demonstrate that by simply optimizing the tasks to improve both feasibility and compatibility, complex and useful whole-body motions can be realized.Le développement de comportements utiles pour les robots complexes, tel que des humanoïdes, s'avère difficile. La commande corps-complet à base de modèle allège en partie ces difficultés, en permettant la composition des comportements corps-complets complexes à partir de plusieurs tâches atomiques effectuées simultanément sur le robot. Cependant, des hypothèses et erreurs de modélisation, faites pendant la planification des tâches, peuvent produire des combinaisons infaisables/incompatibles quand exécutées sur le robot, créant des mouvements corps-complet imprévisibles, et probablement dangereux. L'objectif de ce travail est de mieux comprendre ce qui rend les tâches infaisables ou incompatibles et de développer des méthodes automatiques pour améliorer ces problèmes pour que les mouvements corps-complets puissent être accomplis comme prévu. Nous commençons par construire un formalisme permettant d'analyser quand les tâches sont faisables et compatibles étant données les contraintes de commande. En utilisant les métriques de faisabilité et compatibilité à base de modèle, nous démontrons comment optimiser les tâches avec des outils de commande prédictive non-linéaire ainsi que les inconvénients de cette approche. Afin de surmonter ces faiblesses, une boucle d'optimisation est formulée, qui améliore automatiquement la faisabilité et compatibilité des tâches via la recherche de politique sans modèle en conjonction avec la commande corps-complets à base de modèle. À travers une série d'expériences simulées et réelles, nous montrons que la simple optimisation de faisabilité et compatibilité des tâches nous permet de réaliser des mouvements corps-complets utiles

Optimization-Based Controllers for Robotics Applications (OCRA): The Case of iCub’s Whole-Body Control

OCRA stands for Optimization-based Control for Robotics Applications. It consists of a set of platform-independent libraries which facilitates the development of optimization-based controllers for articulated robots. Hierarchical, weighted, and hybrid control strategies can easily be implemented using these tools. The generic interfaces provided by OCRA allow different robots to use the exact same controllers. OCRA also allows users to specify high-level objectives via tasks. These tasks provide an intuitive way of generating complex behaviors and can be specified in XML format. To illustrate the use of OCRA, an implementation of interest to this research topic for the humanoid robot iCub is presented. OCRA stands for Optimization-based Control for Robotics Applications. It consists of a set of platform-independent libraries which facilitates the development of optimization-based controllers for articulated robots. Hierarchical, weighted, and hybrid control strategies can easily be implemented using these tools. The generic interfaces provided by OCRA allow different robots to use the exact same controllers. OCRA also allows users to specify high-level objectives via tasks. These tasks provide an intuitive way of generating complex behaviors and can be specified in XML format. To illustrate the use of OCRA, an implementation of interest to this research topic for the humanoid robot iCub is presented

ocra-recipes/ocra-recipes: Experiments at IIT on real robot

This subversion comes after OCRA was successfully tested on the real robot at IIT in Genova, Italy