A Machine Learning Model for Robot Kinematics and Motion Task Planning for Mechanical Assembly Operations PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download A Machine Learning Model for Robot Kinematics and Motion Task Planning for Mechanical Assembly Operations PDF full book. Access full book title A Machine Learning Model for Robot Kinematics and Motion Task Planning for Mechanical Assembly Operations by Bhaskaran Gopalakrishnan. Download full books in PDF and EPUB format.
Author: Bhaskaran Gopalakrishnan
Publisher:
ISBN:
Category : Machine learning
Languages : en
Pages : 11
Get Book Here
Book Description
Author: Bhaskaran Gopalakrishnan
Publisher:
ISBN:
Category : Machine learning
Languages : en
Pages : 11
Get Book Here
Book Description
Author: B. GOPALAKRISHNAN
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
Get Book Here
Book Description
Author: Ajinkya Jain
Publisher:
ISBN:
Category :
Languages : en
Pages : 302
Get Book Here
Book Description
Service robots that can assist humans in performing day-to-day tasks will need to be general-purpose robots that can perform a wide array of tasks without much supervision from end-users. As they will be operating in unstructured and ever-changing human environments, they will need to be capable of adapting to their work environments quickly and learning to perform novel tasks within a few trials. However, current robots fall short of these requirements as they are generally highly specialized, can only perform fixed, predefined tasks reliably, and need to operate in controlled environments. One of the main reasons behind this big gap is that the current robots require complete and accurate information about their surroundings to function effectively, whereas, in human environments, robots will only have access to limited information about their tasks and environments. With incomplete information about its surroundings, a robot using pre-programmed or pre-learned motion policies will fail to adapt to the novel situations encountered during operation and fall short in completing its tasks. Online motion generation methods that do not reason about the lack of information will not suffice either, as the developed policies may be unreliable under incomplete information. Reasoning about the lack of information becomes critical for manipulation tasks a service robot would have to perform. These tasks will often require interacting with multiple objects that make or break contacts during the task. A contact between objects can significantly alter their subsequent motion and lead to sudden transitions in their dynamics. Under these sudden transitions, even minor errors in estimating object poses can cause drastic deviations from the robot's initial motion plan for the task and lead the robot to failure in completing the tasks. Hence, service robots need methods that generate motion policies for manipulation tasks efficiently while accounting for the uncertainty due to incomplete or partial information. Partially Observable Markov Decision Processes (POMDPs) is one such mathematical framework that can model and plan for tasks where the agent lacks complete information about the task. However, POMDPs incur exponentially increasing computational costs with planning time horizon, which restricts the current POMDP-based planning methods to problems having short time horizons. Another challenge for planning-based approaches is that they require a state transition function for the world they are operating in to develop motion plans, which may not always be available to the robot. In control theory terms, a state transition function for the world is analogous to its system plant. In this dissertation, we propose to address these challenges by developing methods that can learn state transition functions for robot manipulation tasks directly from observations and later use them to generate long-horizon motion plans to complete the task under uncertainty. We first model the world state transition functions for robot manipulation tasks involving sudden transitions, such as due to contacts, using hybrid models and develop a novel hierarchical POMDP-planner that leverages the representational power of hybrid models to develop motion plans for long-horizon tasks under uncertainty. Next, we address the requirement of planning-based methods to have access to world state transition functions. We introduce three novel methods for learning kinematic models for articulated objects directly from observations and present an algorithm to construct the state transition functions from the learned kinematics models for manipulating these objects. We focus on learning models for articulated objects as they form one of the biggest sets of household objects that service robots will frequently interact with. The first method, MICAH, focuses on learning kinematic models for articulated objects that exhibit configuration-dependent articulation properties, such as a refrigerator door that stays closed magnetically, from unsegmented sequences of observations of object part poses. Next, we introduce ScrewNet, which removes the requirement of object pose estimation of MICAH and learns articulation properties of objects directly from raw sensory data available to the robot (depth images) without knowing their articulation model category a priori. Extending it further, we introduce DUST-net, which learns distributions over articulation model parameters for objects indicating the network's confidence over the estimated parameters directly from raw depth images. Combining these methods, in this dissertation, we introduce a unified framework that can enable a robot to learn state transition functions for manipulation tasks from observations and later use them to develop long-horizon plans even under uncertainty
Author: Dr.V.Balaji
Publisher: SK Research Group of Companies
ISBN: 8119980638
Category : Technology & Engineering
Languages : en
Pages : 201
Get Book Here
Book Description
Dr. V. Balaji, Professor and Head, Department of Mechanical Engineering, Loyola Institute of Technology, Chennai, Tamil Nadu, India. Mr.D.S.Ezhumalai, Assistant Professor, Department of Mechanical Engineering, Loyola Institute of Technology, Chennai, Tamil Nadu, India. Mr.A.Manigandan, Assistant Professor, Department of Mechanical Engineering, Loyola Institute of Technology, Chennai, Tamil Nadu, India. Ms.D.Asha, Assistant Professor, Department of Information Technology, Loyola Institute of Technology, Chennai, Tamil Nadu, India.
Author:
Publisher:
ISBN:
Category : Industrial engineering
Languages : en
Pages : 356
Get Book Here
Book Description
Author: Bartlett Mel
Publisher: Elsevier
ISBN: 0323141269
Category : Technology & Engineering
Languages : en
Pages : 183
Get Book Here
Book Description
Connectionist Robot Motion Planning: A Neurally-Inspired Approach to Visually-Guided Reaching is the third series in a cluster of books on robotics and related areas as part of the Perspectives in Artificial Intelligence Series. This series focuses on an experimental paradigm using the MURPHY system to tackle critical issues surrounding robot motion planning. MURPHY is a robot-camera system developed to explore an approach to the kinematics of sensory-motor learning and control for a multi-link arm. Organized into eight chapters, this book describes the guiding of a multi-link arm to visual targets in a cluttered workspace. It primarily focuses on “ecological solutions that are relevant to the typical visually guided reaching behaviors of humans and animals in natural environments. Algorithms that work well in unmodeled workspaces whose effective layouts can change from moment to moment with movements of the eyes, head, limbs, and body are also presented. This book also examines the strengths of neurally inspired connectionist representations and the utility of heuristic search when good performance, even if suboptimal, is adequate for the task. The co-evolution of MURPHY’s design with the brain, presumably in response to similar computational pressures, is described in the concluding chapters, specifically presenting the division of labor between programmed-feedforward and visual-feedback modes of limb control. Design engineers in the fields of biology, neurophysiology, and cognitive psychology will find this book of great value.
Author: Oriol Bohigas
Publisher: Springer
ISBN: 3319329227
Category : Technology & Engineering
Languages : en
Pages : 201
Get Book Here
Book Description
This book presents the singular configurations associated with a robot mechanism, together with robust methods for their computation, interpretation, and avoidance path planning. Having such methods is essential as singularities generally pose problems to the normal operation of a robot, but also determine the workspaces and motion impediments of its underlying mechanical structure. A distinctive feature of this volume is that the methods are applicable to nonredundant mechanisms of general architecture, defined by planar or spatial kinematic chains interconnected in an arbitrary way. Moreover, singularities are interpreted as silhouettes of the configuration space when seen from the input or output spaces. This leads to a powerful image that explains the consequences of traversing singular configurations, and all the rich information that can be extracted from them. The problems are solved by means of effective branch-and-prune and numerical continuation methods that are of independent interest in themselves. The theory can be put into practice as well: a companion web page gives open access to implementations of the algorithms and the corresponding input files. Using them, the reader can gain hands-on experience on the topic, or analyse new mechanisms beyond those examined in the text. Overall, the book contributes new tools for robot design, and constitutes a single reference source of knowledge that is otherwise dispersed in the literature.
Author: Kevin M. Lynch
Publisher: Cambridge University Press
ISBN: 1107156300
Category : Computers
Languages : en
Pages : 545
Get Book Here
Book Description
A modern and unified treatment of the mechanics, planning, and control of robots, suitable for a first course in robotics.
Author: Michael Brady
Publisher: MIT Press
ISBN: 9780262022842
Category : Computers
Languages : en
Pages : 642
Get Book Here
Book Description
These 16 contributions provide a field guide to robotics science today.These 16 contributions provide a field guide to robotics science today. Each takes up current work the problems addressed, and future directions in the areas of perception, planning, control, design, and actuation. In a substantial introduction, Michael Brady summarizes a personal list of 30 problems, problem areas, and issues that lie on the path to development of a science of robotics. These involve sensing vision, mobility, design, control, manipulation, reasoning, geometric reasoning and systems integration.ContentsThe Problems of Robotics, Michael Brady - Perception. A Few Steps Toward Artificial 3-D Vision, Olivier D. Faugeras - Contact Sensing for Robot Active Touch, Paolo Dario - Learning and Recognition in Natural Environments, Alex Pentland and Robert Bolles - 3-D Vision for Outdoor Navigation by an Autonomous Vehicle, Martial Hebert and Takeo Kanade - Planning. Geometric Issues in Planning Robot Tasks, Tomas Lozano Perez and Russell Taylor - Robotic Manipulation: Mechanics and Planning, Matthew Mason - Control. A Survey of Manipulation and Assembly: Development of the Field and Open Research Issues, Daniel Whitney - Control, Suguru Arimoto - Kinematics and Dynamics for Control, John Hollerbach - The Whole Iguana, Rodney Brooks - Design and Actuation. Design and Kinematics for Force and Velocity Control of Manipulators and End Effectors, Bernard Roth - Arm Design, Haruhiko Asada - Behavior Based Design of Robot Effectors, Stephen Jacobsen, Craig Smith, Klaus Biggers, and Edwin Iversen - Using an Articulated Hand to Manipulate Objects, Kenneth Salisbury, David Brock and Patrick O'Donnell - Legged Robots, Marc RaibertRobotics Science is included in the System Development Foundation Benchmark series. System Development Foundation grants have contributed significantly to the development of robotics in the United States during the 1980s.
Author: Luigi Biagiotti
Publisher: Springer Science & Business Media
ISBN: 3540856293
Category : Technology & Engineering
Languages : en
Pages : 515
Get Book Here
Book Description
This book deals with the problems related to planning motion laws and t- jectories for the actuation system of automatic machines, in particular for those based on electric drives, and robots. The problem of planning suitable trajectories is relevant not only for the proper use of these machines, in order to avoid undesired e?ects such as vibrations or even damages on the mech- ical structure, but also in some phases of their design and in the choice and sizing of the actuators. This is particularly true now that the concept of “el- tronic cams” has replaced, in the design of automatic machines, the classical approach based on “mechanical cams”. The choice of a particular trajectory has direct and relevant implications on several aspects of the design and use of an automatic machine, like the dimensioning of the actuators and of the reduction gears, the vibrations and e?orts generated on the machine and on the load, the tracking errors during the motion execution. For these reasons, in order to understand and appreciate the peculiarities of the di?erent techniques available for trajectory planning, besides the ma- ematical aspects of their implementation also a detailed analysis in the time and frequency domains, a comparison of their main properties under di?erent points of view, and general considerations related to their practical use are reported.
