Development of a Locomotion and Balancing Strategy for Humanoid Robots

The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, makes the gait unnatural, energy inefficient and exert large amounts of torque to the knee joint. Thus creating a walking engine that produces a quality and natural gait is essential for humanoid robots in general and is a factor for succeeding in RoboCup competition. Humanoids robots are required to walk fast to be practical for various life tasks. However, its complex structure makes it prone to falling during fast locomotion. On the same hand, the robots are expected to work in constantly changing environments alongside humans and robots, which increase the chance of collisions. Several human-inspired recovery strategies have been studied and adopted to humanoid robots in order to face unexpected and avoidable perturbations. These strategies include hip, ankle, and stepping, however, the use of the arms as a recovery strategy did not enjoy as much attention. The arms can be employed in different motions for fall prevention. The arm rotation strategy can be employed to control the angular momentum of the body and help to regain balance. In this master\u27s thesis, I developed a detailed study of different ways in which the arms can be used to enhance the balance recovery of the NAO humanoid robot while stationary and during locomotion. I model the robot as a linear inverted pendulum plus a flywheel to account for the angular momentum change at the CoM. I considered the role of the arms in changing the body\u27s moment of inertia which help to prevent the robot from falling or to decrease the falling impact. I propose a control algorithm that integrates the arm rotation strategy with the on-board sensors of the NAO. Additionally, I present a simple method to control the amount of recovery from rotating the arms. I also discuss the limitation of the strategy and how it can have a negative impact if it was misused. I present simulations to evaluate the approach in keeping the robot stable against various disturbance sources. The results show the success of the approach in keeping the NAO stable against various perturbations. Finally,I adopt the arm rotation to stabilize the ball kick, which is a common reason for falling in the soccer humanoid RoboCup competitions

Humanoid Robot Soccer Locomotion and Kick Dynamics: Open Loop Walking, Kicking and Morphing into Special Motions on the Nao Robot

Striker speed and accuracy in the RoboCup (SPL) international robot soccer league is becoming increasingly important as the level of play rises. Competition around the ball is now decided in a matter of seconds. Therefore, eliminating any wasted actions or motions is crucial when attempting to kick the ball. It is common to see a discontinuity between walking and kicking where a robot will return to an initial pose in preparation for the kick action. In this thesis we explore the removal of this behaviour by developing a transition gait that morphs the walk directly into the kick back swing pose. The solution presented here is targeted towards the use of the Aldebaran walk for the Nao robot. The solution we develop involves the design of a central pattern generator to allow for controlled steps with realtime accuracy, and a phase locked loop method to synchronise with the Aldebaran walk so that precise step length control can be activated when required. An open loop trajectory mapping approach is taken to the walk that is stabilized statically through the use of a phase varying joint holding torque technique. We also examine the basic princples of open loop walking, focussing on the commonly overlooked frontal plane motion. The act of kicking itself is explored both analytically and empirically, and solutions are provided that are versatile and powerful. Included as an appendix, the broader matter of striker behaviour (process of goal scoring) is reviewed and we present a velocity control algorithm that is very accurate and efficient in terms of speed of execution

Humanoid navigation and heavy load transportation in a cluttered environment

International audienceAlthough in recent years several studies aimed at the navigation of robots in cluttered environments, just a few have addressed the problem of robots navigating while moving a large or heavy object. This is especially useful when transporting loads with variable weights and shapes without having to change the robot hardware. On one hand, a major advantage of using a humanoid robot to move an object is that it has arms to firmly grasp it and control it. On the other hand, humanoid robots tend to have higher drift than their wheeled counterparts as well as having significant lateral swing while walking, which propagates to anything they carry. In this work, we present algorithms for a humanoid robot navigating in a cluttered environment while pushing a cart-like object. In addition, the algorithms make use of the hands and arms to articulate the cart when executing tight turns using whole body control scheme to reduce the lateral swing effect on the load and ensure a safe transport. Experiments conducted on a real Nao robot assessed the proposed approach and algorithms, they show that the payload of a humanoid robot can be significantly increased without changing the humanoid robot's hardware, and therefore enact the capacity of humanoid robots in real-life situations

Form, Function and Etiquette – Potential Users’ Perspectives on Social Domestic Robots

Social Domestic Robots (SDRs) will soon be launched en masse among commercial markets. Previously, social robots only inhabited scientific labs; now there is an opportunity to conduct experiments to investigate human-robot relationships (including user expectations of social interaction) within more naturalistic, domestic spaces, as well as to test models of technology acceptance. To this end we exposed 20 participants to advertisements prepared by three robotics companies, explaining and “pitching” their SDRs’ functionality (namely, Pepper by SoftBank; Jibo by Jibo, Inc.; and Buddy by Blue Frog Robotics). Participants were interviewed and the data was thematically analyzed to critically examine their initial reactions, concerns and impressions of the three SDRs. Using this approach, we aim to complement existing survey results pertaining to SDRs, and to try to understand the reasoning people use when evaluating SDRs based on what is publicly available to them, namely, advertising. Herein, we unpack issues raised concerning form/function, security/privacy, and the perceived emotional impact of owning an SDR. We discuss implications for the adequate design of socially engaged robotics for domestic applications, and provide four practical steps that could improve the relationships between people and SDRs. An additional contribution is made by expanding existing models of technology acceptance in domestic settings with a new factor of privacy

Development of the mirror system with humanoid robots

This project focuses in the concept of robot teleoperation and how to make it easier for any type of user. The use of robots requires in most of the cases high knowledge in the area which restrict their use to people specifically prepared for the task. For that reason it is essential for everybody the research for controlling robots using simpler techniques approaching the robotics for everybody. In this project, the user will use the simplest way to control the robot arms and using his/her own arms in the same way that he/she wants to move the robot arms. For reaching that goal, the project assumes the use of Microsoft Kinect device that capture everything the user does. Then a computer will process it and send the information to the robot, in this case a NAO robot. For that reason, the teleoperation is simple and possible even to old people or children. This type of interface opens the door to infinite possibilities and creates a solid foundation on which to establish future knowledge.Ingeniería Informátic

On particle filter localization and mapping for Nao robot

The performance of autonomous mobile robots within an indoor environment relies on an effective detection and localization system. Self-Localization within an indoor environment has been studied and tested experimentally on humanoid robot Nao. The solution utilizes a pre-existing map with known and unknown features. The aim of this thesis is to utilize map of visual features and the Monte-Carlo Scheme (particle filters) in localization and navigation. Nao robot cameras has been used for detection Naomarks, the detection of these features provides an estimation of the relative distances of features to current robot position. These measurements are applied to a visual localization algorithm that uses a pair of known feature to localize the robot, furthermore the measurements is fused to a particle filter algorithm for estimating the pose of the robot within the map. The particle filter implementation was based on the C++ programming language. A simple path planning scheme was implemented for continuous localization while navigating a paths with obstacles. The algorithms has been tested with reference to measurements provided by an external sensor. The results of the implementations indicates that the robot can effectively navigate from a start position to a predefined location while avoiding obstacles on its path

A reliability-based particle filter for humanoid robot self-localization in Robocup Standard Platform League

This paper deals with the problem of humanoid robot localization and proposes a new method for position estimation that has been developed for the RoboCup Standard Platform League environment. Firstly, a complete vision system has been implemented in the Nao robot platform that enables the detection of relevant field markers. The detection of field markers provides some estimation of distances for the current robot position. To reduce errors in these distance measurements, extrinsic and intrinsic camera calibration procedures have been developed and described. To validate the localization algorithm, experiments covering many of the typical situations that arise during RoboCup games have been developed: ranging from degradation in position estimation to total loss of position (due to falls, ‘kidnapped robot’, or penalization). The self-localization method developed is based on the classical particle filter algorithm. The main contribution of this work is a new particle selection strategy. Our approach reduces the CPU computing time required for each iteration and so eases the limited resource availability problem that is common in robot platforms such as Nao. The experimental results show the quality of the new algorithm in terms of localization and CPU time consumption.This work has been supported by the Spanish Science and Innovation Ministry (MICINN) under the CICYT project COBAMI: DPI2011-28507-C02-01/02. The responsibility for the content remains with the authors.Munera Sánchez, E.; Muñoz Alcobendas, M.; Blanes Noguera, F.; Benet Gilabert, G.; Simó Ten, JE. (2013). A reliability-based particle filter for humanoid robot self-localization in Robocup Standard Platform League. Sensors. 13(11):14954-14983. https://doi.org/10.3390/s131114954S1495414983131

Artificial Vision in the Nao Humanoid Robot

Projecte Final de Màster UPC realitzat en col.laboració amb l'Universitat Rovira i Virgili. Departament d'Enginyeria Informàtica i MatemàtiquesRobocup is an international robotic soccer competition held yearly to promote innovative research and application in robotic intelligence. Nao humanoid robot is the new RoboCup Standard Platform robot. This platform is the new Nao robot designed and manufactured by the french company Aldebaran Robotics. The new robot is an advanced platform for developing new computer vision and robotics methods. This Master Thesis is oriented to the study of some fundamental issues for the artificial vision in the Nao humanoid robots. In particular, color representation models, real-time segmentation techniques, object detection and visual sonar approaches are the computer vision techniques applied to Nao robot in this Master Thesis. Also, Nao’s camera model, mathematical robot kinematic and stereo-vision techniques are studied and developed. This thesis also studies the integration between kinematic model and robot perception model to perform RoboCup soccer games and RoboCup technical challenges. This work is focused in the RoboCup environment but all computer vision and robotics algorithms can be easily extended to another robotics fields

Scalable Multicore Motion Planning Using Lock-Free Concurrency

We present PRRT (Parallel RRT) and PRRT* (Parallel RRT*), sampling-based methods for feasible and optimal motion planning designed for modern multicore CPUs. We parallelize RRT and RRT* such that all threads concurrently build a single motion planning tree. Parallelization in this manner requires that data structures, such as the nearest neighbor search tree and the motion planning tree, are safely shared across multiple threads. Rather than rely on traditional locks which can result in slowdowns due to lock contention, we introduce algorithms based on lock-free concurrency using atomic operations. We further improve scalability by using partition-based sampling (which shrinks each core’s working data set to improve cache efficiency) and parallel work-saving (in reducing the number of rewiring steps performed in PRRT*). Because PRRT and PRRT* are CPU-based, they can be directly integrated with existing libraries. We demonstrate that PRRT and PRRT* scale well as core counts increase, in some cases exhibiting superlinear speedup, for scenarios such as the Alpha Puzzle and Cubicles scenarios and the Aldebaran Nao robot performing a 2-handed task