Legged Robots

International audienc

Humanoid robot navigation: getting localization information from vision

International audienceIn this article, we present our work to provide a navigation and localization system on a constrained humanoid platform, the NAO robot, without modifying the robot sensors. First we try to implement a simple and light version of classical monocular Simultaneous Localization and Mapping (SLAM) algorithms, while adapting to the CPU and camera quality, which turns out to be insufficient on the platform for the moment. From our work on keypoints tracking, we identify that some keypoints can be still accurately tracked at little cost, and use them to build a visual compass. This compass is then used to correct the robot walk, because it makes it possible to control the robot orientation accurately

End-to-End Pixel-Based Deep Active Inference for Body Perception and Action

We present a pixel-based deep active inference algorithm (PixelAI) inspired by human body perception and action. Our algorithm combines the free-energy principle from neuroscience, rooted in variational inference, with deep convolutional decoders to scale the algorithm to directly deal with raw visual input and provide online adaptive inference. Our approach is validated by studying body perception and action in a simulated and a real Nao robot. Results show that our approach allows the robot to perform 1) dynamical body estimation of its arm using only monocular camera images and 2) autonomous reaching to "imagined" arm poses in the visual space. This suggests that robot and human body perception and action can be efficiently solved by viewing both as an active inference problem guided by ongoing sensory input

Legged Robots

International audienc

Recent Progress in Legged Robots Locomotion Control

International audiencePurpose of review. In recent years, legged robots locomotion has been transitioning from mostly flat ground in controlled settings to generic indoor and outdoor environments, approaching now real industrial scenarios. This paper aims at documenting some of the key progress made in legged locomotion control that enabled this transition. Recent findings. Legged locomotion control makes extensive use of numerical trajectory optimization and its online implementation, Model Predictive Control. A key progress has been how this optimization is handled, with refined models and refined numerical methods. This led the legged locomotion research community to heavily invest in and contribute to the development of new optimization methods and efficient numerical software

Transport collaboratif d'une charge par un couple humain-robot

Les robots humanoïdes sont particulièrement adaptés à collaborer avec des humains. En effet, leur ressemblance avec l'être humain facilite leur acceptation sociale, et leur structure bipède les aide à fonctionner dans des environements conçus pour les humains. Par contre, cette même structure les rend instables et diffcile à contrôler, particulièrement lors d'interactions physiques avec d'autres acteurs. Ce projet de recherche s'attarde au contrôle de robots humanoïdes impliqués dans de telles tâches collaboratives. On s'intéresse plus particulièrement au transport d'objets lourds par un robot humanoïde et un humain. Pour ce faire, un modèle dynamique simplifié prenant en compte la dynamique de la tâche à accomplir ainsi que les forces appliquées sur le robot est proposé. Celui-ci permet une intégration directe de la compliance des bras et l'utilisation de contraintes dynamiques sur les forces d'interactions. Ce modèle est implémenté à l'aide d'un contrôleur de type Model Predictive Control. Un robot humanoïde de taille humaine (HRP-4) et un robot humanoïde de petite taille (NAO) ont été utilisés en simulation pour montrer les performances et la polyvalence de la méthode proposée, chacun transportant collaborativement des charges surpassant leur masse respective

Parallel architectures for humanoid robots

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The structure of humanoid robots can be inspired to human anatomy and operation with open challenges in mechanical performance that can be achieved by using parallel kinematic mechanisms. Parallel mechanisms can be identified in human anatomy with operations that can be used for designing parallel mechanisms in the structure of humanoid robots. Design issues are outlined as requirements and performance for parallel mechanisms in humanoid structures. The example of LARMbot humanoid design is presented as from direct authors’ experience to show an example of the feasibility and efficiency of using parallel mechanisms in humanoid structures. This work is an extension of a paper presented at ISRM 2019 conference (International Symposium on Robotics and Mechatronics)

Movimentação e ensinamento de um robô NAO

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

Omni-directional closed-loop walk for NAO

Abstract—This paper describes the new walk algorithm implemented on the NAO robot. NAO is a small fully actuated biped robot provided by the French company Aldebaran Robotics. Since the beginning of the company in July 2005, a major goal has been the development of robust walk for the robot. After 5 years of mecatronic design and improvements in robustness of the robot (7 prototypes) and multiple prototypes of humanoid dynamic walk algorithm, an omni-directional walk robust against small obstacles is now available for all the NAO units (more than 700) in the world. I