Vision Aided Planning For Robust Autonomous Navigation Of Small Scale Quadruped Robots PDF Download
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| Author | : Thomas O. Dudzik |
| Publisher | : |
| Total Pages | : 77 |
| Release | : 2020 |
| Genre | : |
| ISBN | : |
Download Vision-aided Planning for Robust Autonomous Navigation of Small-Scale Quadruped Robots Book in PDF, ePub and Kindle
Robust path planning in non-flat and non-rigid terrain poses a significant challenge for small-scale legged robots. For a quadruped robot to reliably operate autonomously in complex environments, it must be able to continuously determine sequences of feasible body positions that lead it towards a goal while maintaining balance and avoiding obstacles. Current solutions to the problem of motion planning have several shortcoming such as not exploiting the full flexibility of legged robots and not scaling well with environment size or complexity. In this thesis, we address the problem of navigation of quadruped robots by proposing and implementing a vision-aided planning framework on top of existing motion controllers that combines terrain awareness with graph-based search techniques. In particular, the proposed approach exploits the distinctive obstacle-negotiation capabilities of legged robots while keeping the computational complexity low enough to enable planning over considerable distances in real-time. We showcase the effectiveness of our approach both in simulated environments and on actual hardware using the MIT Mini-Cheetah Vision robotic platform.
| Author | : Amitava Chatterjee |
| Publisher | : Springer |
| Total Pages | : 226 |
| Release | : 2012-10-13 |
| Genre | : Computers |
| ISBN | : 9783642339660 |
Download Vision Based Autonomous Robot Navigation Book in PDF, ePub and Kindle
This monograph is devoted to the theory and development of autonomous navigation of mobile robots using computer vision based sensing mechanism. The conventional robot navigation systems, utilizing traditional sensors like ultrasonic, IR, GPS, laser sensors etc., suffer several drawbacks related to either the physical limitations of the sensor or incur high cost. Vision sensing has emerged as a popular alternative where cameras can be used to reduce the overall cost, maintaining high degree of intelligence, flexibility and robustness. This book includes a detailed description of several new approaches for real life vision based autonomous navigation algorithms and SLAM. It presents the concept of how subgoal based goal-driven navigation can be carried out using vision sensing. The development concept of vision based robots for path/line tracking using fuzzy logic is presented, as well as how a low-cost robot can be indigenously developed in the laboratory with microcontroller based sensor systems. The book describes successful implementation of integration of low-cost, external peripherals, with off-the-shelf procured robots. An important highlight of the book is that it presents a detailed, step-by-step sample demonstration of how vision-based navigation modules can be actually implemented in real life, under 32-bit Windows environment. The book also discusses the concept of implementing vision based SLAM employing a two camera based system.
| Author | : Christian Laugier |
| Publisher | : Springer |
| Total Pages | : 176 |
| Release | : 2007-10-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3540734228 |
Download Autonomous Navigation in Dynamic Environments Book in PDF, ePub and Kindle
This book presents a foundation for a broad class of mobile robot mapping and navigation methodologies for indoor, outdoor, and exploratory missions. It addresses the challenging problem of autonomous navigation in dynamic environments, presenting new ideas and approaches in this emerging technical domain. Coverage discusses in detail various related challenging technical aspects and addresses upcoming technologies in this field.
| Author | : Michael F. Everett |
| Publisher | : |
| Total Pages | : 163 |
| Release | : 2020 |
| Genre | : |
| ISBN | : |
Download Algorithms for Robust Autonomous Navigation in Human Environments Book in PDF, ePub and Kindle
Today’s robots are designed for humans, but are rarely deployed among humans. This thesis addresses problems of perception, planning, and safety that arise when deploying a mobile robot in human environments. A first key challenge is that of quickly navigating to a human-specified goal – one with known semantic type, but unknown coordinate – in a previously unseen world. This thesis formulates the contextual scene understanding problem as an image translation problem, by learning to estimate the planning cost-to-go from aerial images of similar environments. The proposed perception algorithm is united with a motion planner to reduce the amount of exploration time before finding the goal. In dynamic human environments, pedestrians also present several important technical challenges for the motion planning system. This thesis contributes a deep reinforcement learning-based (RL) formulation of the multiagent collision avoidance problem, with relaxed assumptions on the behavior model and number of agents in the environment. Benefits include strong performance among many nearby agents and the ability to accomplish long-term autonomy in pedestrian-rich environments. These and many other state-of-the-art robotics systems rely on Deep Neural Networks for perception and planning. However, blindly applying deep learning in safety-critical domains, such as those involving humans, remains dangerous without formal guarantees on robustness. For example, small perturbations to sensor inputs are often enough to change network-based decisions. This thesis contributes an RL framework that is certified robust to uncertainties in the observation space.
| Author | : Daniel A. Carballo |
| Publisher | : |
| Total Pages | : 55 |
| Release | : 2020 |
| Genre | : |
| ISBN | : |
Download Visual Navigation for Dynamic Quadruped Robots Book in PDF, ePub and Kindle
Legged robots have been highlighted as promising mobile platforms for disaster response and rescue scenarios because of their rough terrain locomotion capability. In cluttered environments, small robots are desirable as they can maneuver through small gaps, narrow paths, or tunnels. However small robots have their own set of difficulties such as limited space for sensors, limited obstacle clearance, and scaled-down walking speed. In this paper, we extensively address these difficulties via effective sensor integration and exploitation of dynamic locomotion and jumping. We integrate two Intel RealSense sensors into the MIT Mini-Cheetah, a 0.3 m tall, 9 kg quadruped robot. Simple and effective filtering and evaluation algorithms are used for foothold adjustment and obstacle avoidance. We showcase the exploration of highly irregular terrain using dynamic trotting and jumping with the small-scale, fully sensorized Mini-Cheetah quadruped robot.
| Author | : |
| Publisher | : |
| Total Pages | : 48 |
| Release | : 2002 |
| Genre | : |
| ISBN | : |
Download Robust Planning for Autonomous Navigation of Mobile Robots in Unstructured, Dynamic Environments Book in PDF, ePub and Kindle
This report summarizes the analytical and experimental efforts for the Laboratory Directed Research and Development (LDRD) project entitled ''Robust Planning for Autonomous Navigation of Mobile Robots In Unstructured, Dynamic Environments (AutoNav)''. The project goal was to develop an algorithmic-driven, multi-spectral approach to point-to-point navigation characterized by: segmented on-board trajectory planning, self-contained operation without human support for mission duration, and the development of appropriate sensors and algorithms to navigate unattended. The project was partially successful in achieving gains in sensing, path planning, navigation, and guidance. One of three experimental platforms, the Minimalist Autonomous Testbed, used a repetitive sense-and-re-plan combination to demonstrate the majority of elements necessary for autonomous navigation. However, a critical goal for overall success in arbitrary terrain, that of developing a sensor that is able to distinguish true obstacles that need to be avoided as a function of vehicle scale, still needs substantial research to bring to fruition.
| Author | : Xj Jing |
| Publisher | : IntechOpen |
| Total Pages | : 608 |
| Release | : 2008-06-01 |
| Genre | : Technology & Engineering |
| ISBN | : 9789537619015 |
Download Motion Planning Book in PDF, ePub and Kindle
In this book, new results or developments from different research backgrounds and application fields are put together to provide a wide and useful viewpoint on these headed research problems mentioned above, focused on the motion planning problem of mobile ro-bots. These results cover a large range of the problems that are frequently encountered in the motion planning of mobile robots both in theoretical methods and practical applications including obstacle avoidance methods, navigation and localization techniques, environmental modelling or map building methods, and vision signal processing etc. Different methods such as potential fields, reactive behaviours, neural-fuzzy based methods, motion control methods and so on are studied. Through this book and its references, the reader will definitely be able to get a thorough overview on the current research results for this specific topic in robotics. The book is intended for the readers who are interested and active in the field of robotics and especially for those who want to study and develop their own methods in motion/path planning or control for an intelligent robotic system.
| Author | : Om Krishna Gupta |
| Publisher | : |
| Total Pages | : 372 |
| Release | : 2011 |
| Genre | : |
| ISBN | : |
Download Spatio-temporal Probabilistic Path Planning for Autonomous Robot Navigation Book in PDF, ePub and Kindle
In recent years, robotic technology has improved significantly, aided by cutting-edge scientific research studies and innovative industrial designs. It has taken a progressive leap from the coordinated world of industry to the less-ordered domestic domain with great advancements in sensor technology and computational intelligence. It is beginning to prove more useful than a robot vacuum cleaner or a mere plaything in human-centric spaces. This has created an imminent need for robust intelligence for a robot to move optimally with high efficiency and collision-free navigation. This research provides valuable insights into all significant stages required for autonomous navigation in dynamic cluttered environments and makes several important contributions in the area.A unique and real-time method for global path planning and collision avoidance for navigation of a mobile robot in complex time varying environments is developed. An occupancy-based three dimensional (3D) grid map and model-based obstacle prediction are employed to represent the dynamic environment. Path planning and obstacle avoidance are performed by applying a cost-evaluation function on time-space Distance Transforms to uniquely produce the optimal path at the time of planning. Dealing with uncertainty with regard to the position of obstacles for a given navigation task is accommodated by introducing the notion of probabilities to the algorithm. The spatio-temporal cost evaluation based path planning algorithm provides the key contribution of this research.A robust method of pose estimation and tracking for a mobile robot is also investigated. The technique utilises an overhead panoramic vision camera in an indoor cluttered environment with the robot workspace of a two-dimensional planar surface. It is fast and does not require any unwarping of the panoramic view. A unique system, combining mean-shift, Kalman Filter and Hough Transform-based tracking, is used to improve the result. Experiments are conducted confirming that the system is capable of reliably localising and tracking the robot in cluttered scenes with variations of illumination and periods of occlusion.The thesis commences by describing the design of a real-time open-source 3D simulation platform based on a game engine. The platform is primarily aimed towards research in mobile robotics, in-game character manipulation, visual surveillance-related research and high quality synthetic video generation. It provided the initial test-bed for this research to analyse ideas and algorithms including path planning, prior to the physical realisation experiments.Finally, a complete navigation system is integrated for a wheel-based mobile robot verifying the innovations in a real-world scenario. The system will be incorporated into a larger project that is aimed towards the enhancement of robotic assistive technologies for elderly and disabled people.
| Author | : Ahmed Saber Soliman Sayem |
| Publisher | : |
| Total Pages | : 164 |
| Release | : 2016 |
| Genre | : Aids to navigation |
| ISBN | : |
Download Vision-aided Navigation for Autonomous Vehicles Using Tracked Feature Points Book in PDF, ePub and Kindle
This thesis discusses the evaluation, implementation, and testing of several navigation algorithms and feature extraction algorithms using an inertial measurement unit (IMU) and an image capture device (camera) mounted on a ground robot and a quadrotor UAV. The vision-aided navigation algorithms are implemented on data-collected from sensors on an unmanned ground vehicle and a quadrotor, and the results are validated by comparison with GPS data. The thesis investigates sensor fusion techniques for integrating measured IMU data with information extracted from image processing algorithms in order to provide accurate vehicle state estimation. This image-based information takes the forms of features, such as corners, that are tracked over multiple image frames. An extended Kalman filter (EKF) in implemented to fuse vision and IMU data. The main goal of the work is to provide navigation of mobile robots in GPS-denied environments such as indoor environments, cluttered urban environments, or space environments such as asteroids, other planets or the moon. The experimental results show that combining pose information extracted from IMU readings along with pose information extracted from a vision-based algorithm managed to solve the drift problem that comes from using IMU alone and the scale problem that comes from using a monocular vision-based algorithm alone.
| Author | : Mohammad Osman Tokhi |
| Publisher | : World Scientific |
| Total Pages | : 741 |
| Release | : 2014-07-07 |
| Genre | : Technology & Engineering |
| ISBN | : 9814623369 |
Download Mobile Service Robotics Book in PDF, ePub and Kindle
Interest in control of climbing and walking robots has remarkably increased over the years. Novel solutions of complex mechanical systems such as climbing, walking, flying and running robots with different kinds of locomotion and the technologies that support them and their applications are the evidence of significant progress in the area of robotics. Supporting technologies include the means by which robots use to sense, model, and navigate through their environments and, of course, actuation and control technologies. Human interaction including exoskeletons, prostheses and orthoses, as well as service robots, are increasingly active important pertinent areas of research. In addition, legged machines and tracked platforms with software architecture seem to be currently the research idea of most interest to the robotics community.
