Online Learning of Wheel Odometry Correction for Mobile Robots with Attention-based Neural Network

Modern robotic platforms need a reliable localization system to operate daily beside humans. Simple pose estimation algorithms based on filtered wheel and inertial odometry often fail in the presence of abrupt kinematic changes and wheel slips. Moreover, despite the recent success of visual odometry, service and assistive robotic tasks often present challenging environmental conditions where visual-based solutions fail due to poor lighting or repetitive feature patterns. In this work, we propose an innovative online learning approach for wheel odometry correction, paving the way for a robust multi-source localization system. An efficient attention-based neural network architecture has been studied to combine precise performances with real-time inference. The proposed solution shows remarkable results compared to a standard neural network and filter-based odometry correction algorithms. Nonetheless, the online learning paradigm avoids the time-consuming data collection procedure and can be adopted on a generic robotic platform on-the-fly

Locomotion system for ground mobile robots in uneven and unstructured environments

One of the technology domains with the greatest growth rates nowadays is service robots. The extensive use of ground mobile robots in environments that are unstructured or structured for humans is a promising challenge for the coming years, even though Automated Guided Vehicles (AGV) moving on flat and compact grounds are already commercially available and widely utilized to move components and products inside indoor industrial buildings. Agriculture, planetary exploration, military operations, demining, intervention in case of terrorist attacks, surveillance, and reconnaissance in hazardous conditions are important application domains. Due to the fact that it integrates the disciplines of locomotion, vision, cognition, and navigation, the design of a ground mobile robot is extremely interdisciplinary. In terms of mechanics, ground mobile robots, with the exception of those designed for particular surroundings and surfaces (such as slithering or sticky robots), can move on wheels (W), legs (L), tracks (T), or hybrids of these concepts (LW, LT, WT, LWT). In terms of maximum speed, obstacle crossing ability, step/stair climbing ability, slope climbing ability, walking capability on soft terrain, walking capability on uneven terrain, energy efficiency, mechanical complexity, control complexity, and technology readiness, a systematic comparison of these locomotion systems is provided in [1]. Based on the above-mentioned classification, in this thesis, we first introduce a small-scale hybrid locomotion robot for surveillance and inspection, WheTLHLoc, with two tracks, two revolving legs, two active wheels, and two passive omni wheels. The robot can move in several different ways, including using wheels on the flat, compact ground,[1] tracks on soft, yielding terrain, and a combination of tracks, legs, and wheels to navigate obstacles. In particular, static stability and non-slipping characteristics are considered while analyzing the process of climbing steps and stairs. The experimental test on the first prototype has proven the planned climbing maneuver’s efficacy and the WheTLHLoc robot's operational flexibility. Later we present another development of WheTLHLoc and introduce WheTLHLoc 2.0 with newly designed legs, enabling the robot to deal with bigger obstacles. Subsequently, a single-track bio-inspired ground mobile robot's conceptual and embodiment designs are presented. This robot is called SnakeTrack. It is designed for surveillance and inspection activities in unstructured environments with constrained areas. The vertebral column has two end modules and a variable number of vertebrae linked by compliant joints, and the surrounding track is its essential component. Four motors drive the robot: two control the track motion and two regulate the lateral flexion of the vertebral column for steering. The compliant joints enable limited passive torsion and retroflection of the vertebral column, which the robot can use to adapt to uneven terrain and increase traction. Eventually, the new version of SnakeTrack, called 'Porcospino', is introduced with the aim of allowing the robot to move in a wider variety of terrains. The novelty of this thesis lies in the development and presentation of three novel designs of small-scale mobile robots for surveillance and inspection in unstructured environments, and they employ hybrid locomotion systems that allow them to traverse a variety of terrains, including soft, yielding terrain and high obstacles. This thesis contributes to the field of mobile robotics by introducing new design concepts for hybrid locomotion systems that enable robots to navigate challenging environments. The robots presented in this thesis employ modular designs that allow their lengths to be adapted to suit specific tasks, and they are capable of restoring their correct position after falling over, making them highly adaptable and versatile. Furthermore, this thesis presents a detailed analysis of the robots' capabilities, including their step-climbing and motion planning abilities. In this thesis we also discuss possible refinements for the robots' designs to improve their performance and reliability. Overall, this thesis's contributions lie in the design and development of innovative mobile robots that address the challenges of surveillance and inspection in unstructured environments, and the analysis and evaluation of these robots' capabilities. The research presented in this thesis provides a foundation for further work in this field, and it may be of interest to researchers and practitioners in the areas of robotics, automation, and inspection. As a general note, the first robot, WheTLHLoc, is a hybrid locomotion robot capable of combining tracked locomotion on soft terrains, wheeled locomotion on flat and compact grounds, and high obstacle crossing capability. The second robot, SnakeTrack, is a small-size mono-track robot with a modular structure composed of a vertebral column and a single peripherical track revolving around it. The third robot, Porcospino, is an evolution of SnakeTrack and includes flexible spines on the track modules for improved traction on uneven but firm terrains, and refinements of the shape of the track guidance system. This thesis provides detailed descriptions of the design and prototyping of these robots and presents analytical and experimental results to verify their capabilities

Map-based localization for urban service mobile robotics

Mobile robotics research is currently interested on exporting autonomous navigation results achieved in indoor environments, to more challenging environments, such as, for instance, urban pedestrian areas. Developing mobile robots with autonomous navigation capabilities in such urban environments supposes a basic requirement for a upperlevel service set that could be provided to an users community. However, exporting indoor techniques to outdoor urban pedestrian scenarios is not evident due to the larger size of the environment, the dynamism of the scene due to pedestrians and other moving obstacles, the sunlight conditions, and the high presence of three dimensional elements such as ramps, steps, curbs or holes. Moreover, GPS-based mobile robot localization has demonstrated insufficient performance for robust long-term navigation in urban environments. One of the key modules within autonomous navigation is localization. If localization supposes an a priori map, even if it is not a complete model of the environment, localization is called map-based. This assumption is realistic since current trends of city councils are on building precise maps of their cities, specially of the most interesting places such as city downtowns. Having robots localized within a map allows for a high-level planning and monitoring, so that robots can achieve goal points expressed on the map, by following in a deliberative way a previously planned route. This thesis deals with the mobile robot map-based localization issue in urban pedestrian areas. The thesis approach uses the particle filter algorithm, a well-known and widely used probabilistic and recursive method for data fusion and state estimation. The main contributions of the thesis are divided on four aspects: (1) long-term experiments of mobile robot 2D and 3D position tracking in real urban pedestrian scenarios within a full autonomous navigation framework, (2) developing a fast and accurate technique to compute on-line range observation models in 3D environments, a basic step required by the real-time performance of the developed particle filter, (3) formulation of a particle filter that integrates asynchronous data streams and (4) a theoretical proposal to solve the global localization problem in an active and cooperative way, defining cooperation as either information sharing among the robots or planning joint actions to solve a common goal.Actualment, la recerca en robòtica mòbil té un interés creixent en exportar els resultats de navegació autònoma aconseguits en entorns interiors cap a d'altres tipus d'entorns més exigents, com, per exemple, les àrees urbanes peatonals. Desenvolupar capacitats de navegació autònoma en aquests entorns urbans és un requisit bàsic per poder proporcionar un conjunt de serveis de més alt nivell a una comunitat d'usuaris. Malgrat tot, exportar les tècniques d'interiors cap a entorns exteriors peatonals no és evident, a causa de la major dimensió de l'entorn, del dinamisme de l'escena provocada pels peatons i per altres obstacles en moviment, de la resposta de certs sensors a la il.luminació natural, i de la constant presència d'elements tridimensionals tals com rampes, escales, voreres o forats. D'altra banda, la localització de robots mòbils basada en GPS ha demostrat uns resultats insuficients de cara a una navegació robusta i de llarga durada en entorns urbans. Una de les peces clau en la navegació autònoma és la localització. En el cas que la localització consideri un mapa conegut a priori, encara que no sigui un model complet de l'entorn, parlem d'una localització basada en un mapa. Aquesta assumpció és realista ja que la tendència actual de les administracions locals és de construir mapes precisos de les ciutats, especialment dels llocs d'interés tals com les zones més cèntriques. El fet de tenir els robots localitzats en un mapa permet una planificació i una monitorització d'alt nivell, i així els robots poden arribar a destinacions indicades sobre el mapa, tot seguint de forma deliberativa una ruta prèviament planificada. Aquesta tesi tracta el tema de la localització de robots mòbils, basada en un mapa i per entorns urbans peatonals. La proposta de la tesi utilitza el filtre de partícules, un mètode probabilístic i recursiu, ben conegut i àmpliament utilitzat per la fusió de dades i l'estimació d'estats. Les principals contribucions de la tesi queden dividides en quatre aspectes: (1) experimentació de llarga durada del seguiment de la posició, tant en 2D com en 3D, d'un robot mòbil en entorns urbans reals, en el context de la navegació autònoma, (2) desenvolupament d'una tècnica ràpida i precisa per calcular en temps d'execució els models d'observació de distàncies en entorns 3D, un requisit bàsic pel rendiment del filtre de partícules a temps real, (3) formulació d'un filtre de partícules que integra conjunts de dades asíncrones i (4) proposta teòrica per solucionar la localització global d'una manera activa i cooperativa, entenent la cooperació com el fet de compartir informació, o bé com el de planificar accions conjuntes per solucionar un objectiu comú

A layered control architecture for mobile robot navigation

A Thesis submitted to the University Research Degree Committee in fulfillment ofthe requirements for the degree of DOCTOR OF PHILOSOPHY in RoboticsThis thesis addresses the problem of how to control an autonomous mobile robot navigation in indoor environments, in the face of sensor noise, imprecise information, uncertainty and limited response time. The thesis argues that the effective control of autonomous mobile robots can be achieved by organising low level and higher level control activities into a layered architecture. The low level reactive control allows the robot to respond to contingencies quickly. The higher level control allows the robot to make longer term decisions and arranges appropriate sequences for a task execution. The thesis describes the design and implementation of a two layer control architecture, a task template based sequencing layer and a fuzzy behaviour based low level control layer. The sequencing layer works at the pace of the higher level of abstraction, interprets a task plan, mediates and monitors the controlling activities. While the low level performs fast computation in response to dynamic changes in the real world and carries out robust control under uncertainty. The organisation and fusion of fuzzy behaviours are described extensively for the construction of a low level control system. A learning methodology is also developed to systematically learn fuzzy behaviours and the behaviour selection network and therefore solve the difficulties in configuring the low level control layer. A two layer control system has been implemented and used to control a simulated mobile robot performing two tasks in simulated indoor environments. The effectiveness of the layered control and learning methodology is demonstrated through the traces of controlling activities at the two different levels. The results also show a general design methodology that the high level should be used to guide the robot's actions while the low level takes care of detailed control in the face of sensor noise and environment uncertainty in real time

Robotics 2010

Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development