Autonomous robot systems and competitions: proceedings of the 12th International Conference

This is the 2012’s edition of the scientific meeting of the Portuguese Robotics Open (ROBOTICA’ 2012). It aims to disseminate scientific contributions and to promote discussion of theories, methods and experiences in areas of relevance to Autonomous Robotics and Robotic Competitions. All accepted contributions are included in this proceedings book. The conference program has also included an invited talk by Dr.ir. Raymond H. Cuijpers, from the Department of Human Technology Interaction of Eindhoven University of Technology, Netherlands.The conference is kindly sponsored by the IEEE Portugal Section / IEEE RAS ChapterSPR-Sociedade Portuguesa de Robótic

Modeling, Analysis, and Control of a Mobile Robot for \u3ci\u3eIn Vivo\u3c/i\u3e Fluoroscopy of Human Joints during Natural Movements

In this dissertation, the modeling, analysis and control of a multi-degree of freedom (mdof) robotic fluoroscope was investigated. A prototype robotic fluoroscope exists, and consists of a 3 dof mobile platform with two 2 dof Cartesian manipulators mounted symmetrically on opposite sides of the platform. One Cartesian manipulator positions the x-ray generator and the other Cartesian manipulator positions the x-ray imaging device. The robotic fluoroscope is used to x-ray skeletal joints of interest of human subjects performing natural movement activities. In order to collect the data, the Cartesian manipulators must keep the x-ray generation and imaging devices accurately aligned while dynamically tracking the desired skeletal joint of interest. In addition to the joint tracking, this also requires the robotic platform to move along with the subject, allowing the manipulators to operate within their ranges of motion. A comprehensive dynamic model of the robotic fluoroscope prototype was created, incorporating the dynamic coupling of the system. Empirical data collected from an RGB-D camera were used to create a human kinematic model that can be used to simulate the joint of interest target dynamics. This model was incorporated into a computer simulation that was validated by comparing the simulation results with actual prototype experiments using the same human kinematic model inputs. The computer simulation was used in a comprehensive dynamic analysis of the prototype and in the development and evaluation of sensing, control, and signal processing approaches that optimize the subject and joint tracking performance characteristics. The modeling and simulation results were used to develop real-time control strategies, including decoupling techniques that reduce tracking error on the prototype. For a normal walking activity, the joint tracking error was less than 20 mm, and the subject tracking error was less than 140 mm

Contact aware robust semi-autonomous teleoperation of mobile manipulators

In the context of human-robot collaboration, cooperation and teaming, the use of mobile manipulators is widespread on applications involving unpredictable or hazardous environments for humans operators, like space operations, waste management and search and rescue on disaster scenarios. Applications where the manipulator's motion is controlled remotely by specialized operators. Teleoperation of manipulators is not a straightforward task, and in many practical cases represent a common source of failures. Common issues during the remote control of manipulators are: increasing control complexity with respect the mechanical degrees of freedom; inadequate or incomplete feedback to the user (i.e. limited visualization or knowledge of the environment); predefined motion directives may be incompatible with constraints or obstacles imposed by the environment. In the latter case, part of the manipulator may get trapped or blocked by some obstacle in the environment, failure that cannot be easily detected, isolated nor counteracted remotely. While control complexity can be reduced by the introduction of motion directives or by abstraction of the robot motion, the real-time constraint of the teleoperation task requires the transfer of the least possible amount of data over the system's network, thus limiting the number of physical sensors that can be used to model the environment. Therefore, it is of fundamental to define alternative perceptive strategies to accurately characterize different interaction with the environment without relying on specific sensory technologies. In this work, we present a novel approach for safe teleoperation, that takes advantage of model based proprioceptive measurement of the robot dynamics to robustly identify unexpected collisions or contact events with the environment. Each identified collision is translated on-the-fly into a set of local motion constraints, allowing the exploitation of the system redundancies for the computation of intelligent control laws for automatic reaction, without requiring human intervention and minimizing the disturbance of the task execution (or, equivalently, the operator efforts). More precisely, the described system consist in two different building blocks. The first, for detecting unexpected interactions with the environment (perceptive block). The second, for intelligent and autonomous reaction after the stimulus (control block). The perceptive block is responsible of the contact event identification. In short, the approach is based on the claim that a sensorless collision detection method for robot manipulators can be extended to the field of mobile manipulators, by embedding it within a statistical learning framework. The control deals with the intelligent and autonomous reaction after the contact or impact with the environment occurs, and consist on an motion abstraction controller with a prioritized set of constrains, where the highest priority correspond to the robot reconfiguration after a collision is detected; when all related dynamical effects have been compensated, the controller switch again to the basic control mode

On the Enhancement of the Localization of Autonomous Mobile Platforms

The focus of many industrial and research entities on achieving full robotic autonomy increased in the past few years. In order to achieve full robotic autonomy, a fundamental problem is the localization, which is the ability of a mobile platform to determine its position and orientation in the environment. In this thesis, several problems related to the localization of autonomous platforms are addressed, namely, visual odometry accuracy and robustness; uncertainty estimation in odometries; and accurate multi-sensor fusion-based localization. Beside localization, the control of mobile manipulators is also tackled in this thesis. First, a generic image processing pipeline is proposed which, when integrated with a feature-based Visual Odometry (VO), can enhance robustness, accuracy and reduce the accumulation of errors (drift) in the pose estimation. Afterwards, since odometries (e.g. wheel odometry, LiDAR odometry, or VO) suffer from drift errors due to integration, and because such errors need to be quantified in order to achieve accurate localization through multi-sensor fusion schemes (e.g. extended or unscented kalman filters). A covariance estimation algorithm is proposed, which estimates the uncertainty of odometry measurements using another sensor which does not rely on integration. Furthermore, optimization-based multi-sensor fusion techniques are known to achieve better localization results compared to filtering techniques, but with higher computational cost. Consequently, an efficient and generic multi-sensor fusion scheme, based on Moving Horizon Estimation (MHE), is developed. The proposed multi-sensor fusion scheme: is capable of operating with any number of sensors; and considers different sensors measurements rates, missing measurements, and outliers. Moreover, the proposed multi-sensor scheme is based on a multi-threading architecture, in order to reduce its computational cost, making it more feasible for practical applications. Finally, the main purpose of achieving accurate localization is navigation. Hence, the last part of this thesis focuses on developing a stabilization controller of a 10-DOF mobile manipulator based on Model Predictive Control (MPC). All of the aforementioned works are validated using numerical simulations; real data from: EU Long-term Dataset, KITTI Dataset, TUM Dataset; and/or experimental sequences using an omni-directional mobile robot. The results show the efficacy and importance of each part of the proposed work

Navigation of Automatic Vehicle using AI Techniques

In the field of mobile robot navigation have been studied as important task for the new generation of mobile robot i.e. Corobot. For this mobile robot navigation has been viewed for unknown environment. We consider the 4-wheeled vehicle (Corobot) for Path Planning, an autonomous robot and an obstacle and collision avoidance to be used in sensor based robot. We propose that the predefined distance from the robot to target and make the robot follow the target at this distance and improve the trajectory tracking characteristics. The robot will then navigate among these obstacles without hitting them and reach the specified goal point. For these goal achieving we use different techniques radial basis function and back-propagation algorithm under the study of neural network. In this Corobot a robotic arm are assembled and the kinematic analyses of Corobot arm and help of Phidget Control Panel a wheeled to be moved in both forward and reverse direction by 2-motor controller have to be done. Under kinematic analysis propose the relationships between the positions and orientation of the links of a manipulator. In these studies an artificial techniques and their control strategy are shown with potential applications in the fields of industry, security, defense, investigation, and others. Here finally, the simulation result using the webot neural network has been done and this result is compared with experimental data for different training pattern

Mobility, Navigation and Localization Towards Robotic Endoscopy

With significant progress being made towards improving endoscope technology such as capsule endoscopy and robotic endoscopy, the development of advanced strategies for manipulating, controlling and more generally, easing the accessibility of these devices for physicians is an important next step. This work presents the development of several robotic platforms for experimentally testing navigation and localization strategies in robotic endoscopy followed by the development and testing of navigation strategies using these devices. Finally, visual and visual inertial localization and mapping is explored on two of these robotic systems. We first present a detailed description on the state-of-the-art with regard to minimally invasive robotic surgery and then follow this with in-depth description of our design and validation of two important systems, the Robotic Endoscope Platform (REP) and the Modular Endoscopy Simulation Apparatus (MESA), for exploring some of the challenges in robotic endoscopy. Following these descriptions we present a technique for autonomous navigation of the REP within the MESA as well as an attempt at applying Simultaneous Localization and Mapping (SLAM) to allow for the real-time localization of this system. Finally, we transition these techniques to the Endoculus, a complete robotic endoscope suitable for in vivo testing, and demonstrate both autonomous navigation for this device, and the implementation of three different SLAM systems for localization and mapping of the Endoculus system in real-time. Throughout these experiments we demonstrate the potential for advanced methods in computer vision along with other sensory techniques to substantially benefit endoscopy, enabling greater and greater autonomy of these systems and furthering the case for robotic endoscopy as a whole.</p

Safe navigation and human-robot interaction in assistant robotic applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

분산형 통신 및 구동부족 로봇시스템 을 위한 분할기법 기반의 반자율 원격제어 프레임워크 개발

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2018. 2. 이동준.The framework of stable bilateral teleoperation has been well established during decades. However, the standard bilateral teleoperation framework could be a baseline for a successful telerobotics but not sufficient for real-application because they usually concentrate on only the bilateral stability. The least considered in the previous research is how to apply a complex robot systems such as multiple mobile robots or a large degree of freedom mobile manipulators for real applications. The main challenges of teleoperation of complex robotic systems in real-world are to achieve two different control objectives (i.e., follow the human command and the coordination/ stabilization of the internal movement) of the slave robots simultaneously, while providing intuitive information about the complicated features of the system. In this thesis, we develop decomposition-based semi-autonomous teleoperation framework for robotic systems which have distributed communication and underactuation property, consisting of three steps: 1) decomposition step, where the human command is defined, and the robotic system is split into the command tracking space and its orthogonal complement (i.e., internal motion)2) control design of the slave robot, in which we design the slave controller for human command tracking and stabilization/coordination of internal motion spaceand 3) feedback interface design, through which we propose a multi-modal feedback interface (for example, visual and haptic) designed with the consideration of the task and the characteristics of the system. Among numerous types of robots, in this thesis, we focus on two types of robotic systems: 1) multiple nonholonomic wheeled mobile robots (WMRs) with distributed communication requirement and 2) manipulator-stage over vertical flexible beam which is under-actuated system. The proposed framework is applied to both case step by step and perform experiments and human subject study to verify/demonstrate the proposed framework for both cases. For distributed WMRs, we consider the scenario that a single user remotely operates a platoon of nonholonomic WMRs that distributively communicate each other in unknown environment. For this, in decomposition step, we utilize nonholonomic passive decomposition to split the platoon kinematics into that of the formation-keeping aspect and the collective tele-driving aspect. Next, in control design step, we design the controls for these two aspects individually and distribute them into each WMR while fully incorporating their nonholonomic constraint and distribution requirement. Finally, in the step of feedback interface design, we also propose a novel predictive display, which, by providing the user with the estimated current and predicted future pose informations of the platoon and future possibility of collision while fully incorporating the uncertainty inherent to the distribution, can significantly enhance the tele-driving performance and easiness of the platoon. The second part is the manipulator-stage over vertical flexible beam which is under-actuated system. Here, the human command defines the desired motion of the end-effector (or the manipulator), and the vibration of the beam should be subdued at the same time. Thus, at the first step, we utilize the passive decomposition to split the dynamics into manipulator motion space and its orthogonal complement, in which we design the control for the suppression of the vibration. For human command tracking, we design the passivity-based control, and, for the suppression of the vibration, we propose two controls: LQR-based control and nonlinear control based on Lyapunov function analysis. Finally, visuo-haptic feedback interface is preliminarily designed for successful peg-in-hole tasks.1 Introduction 1 1.1 Background and Contribution 1 1.2 Related Works 4 1.2.1 Related Works on Distributed Systems 5 1.2.2 Related Works on Manipulator-Stage System 6 1.3 Outline 6 2 Preliminary 7 2.1 Passive Decomposition 7 2.1.1 Basic Notations and Properties of Standard Passive Decomposition 7 2.1.2 Nonholonomic Passive Decomposition 9 3 Semi-Autonomous Teleoperation of Nonholonomic Wheeled Mobile Robots with Distributed Communication 11 3.1 Distributed Control Design 11 3.1.1 Nonholonomic Passive Decomposition 11 3.1.2 Control Design and Distribution 19 3.2 Distributed Pose Estimation 25 3.2.1 EKF Pose Estimation of Leader WMR 25 3.2.2 EKF Pose Estimation of Follower WMRs 28 3.3 Predictive Display for Distributed Robots Teleoperation 29 3.3.1 Estimation Propagation 31 3.3.2 Prediction Propagation 34 3.4 Experiments 38 3.4.1 Test Setup 38 3.4.2 Performance Experiment 39 3.4.3 Teleoperation Experiment with Predictive Display 40 3.4.4 Human Subject Study 44 4 Semi-Autonomous Teleoperatoin of Stage-Manipulator System on Flexible Vertical Beam 49 4.1 System Modeling 49 4.1.1 System Description 49 4.1.2 Assumed Mode Shapes 51 4.1.3 Exact Solution under Given Boundary Conditions 51 4.1.4 Euler-Lagrangian Equation 61 4.2 LQR-based Control Design 62 4.2.1 Passive Decomposition 63 4.2.2 Vibration Suppression Control Design 64 4.2.3 Joint Tracking Control Design 66 4.3 Lyapunov-based Control Design 68 4.3.1 Twice Passive Decomposition for Input Coupling 69 4.3.2 Interconnected System Description 70 4.3.3 Passivity-based Manipulator Motion Control 74 4.3.4 Dissipative Control for Vibration Suppression 74 4.4 Experiments 78 4.4.1 Test Setup 78 4.4.2 Joint Tracking and Vibration Suppression Experiment 81 4.4.3 Comparison Experiment between the LQR and the Nonlinear Control 82 5 Conclusion 83 5.1 Summary 83 5.2 Future Works 83 A Appendix 85 A.1 Internal Wrench Representation 85Docto

Visual Servoing

The goal of this book is to introduce the visional application by excellent researchers in the world currently and offer the knowledge that can also be applied to another field widely. This book collects the main studies about machine vision currently in the world, and has a powerful persuasion in the applications employed in the machine vision. The contents, which demonstrate that the machine vision theory, are realized in different field. For the beginner, it is easy to understand the development in the vision servoing. For engineer, professor and researcher, they can study and learn the chapters, and then employ another application method

Contemporary Robotics

This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials