Download or read book A Probabilistic Roadmap Based Path Planning for Visual Servo of Robotic Manipulators written by Farid Arvani and published by . This book was released on 2008 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Randomized Path Planning for Visual Servoing written by Moslem Kazemi and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual servoing has been introduced as a promising solution for sensor-based robotic applications. The basic visual servoing task is to guide the motion of a robot with respect to a target object based on the feedback obtained through a vision system. Despite their popularity, Image-Based Visual Servoing (IBVS) schemes suffer from stability and convergence issues. Moreover, in IBVS techniques, there is no direct control over the image/camera/robot trajectories induced by the servoing loop in the image and physical spaces. Therefore, these trajectories might violate the image and/or physical constraints usually encountered in visual servoing tasks. Incorporating path planning strategies into the visual servo loop is a promising effort towards accounting for a variety of constraints. In this thesis, we propose a general and global path planning framework for image-based control built on the efficiency and success of randomized sampling-based path planning techniques. The proposed planner explores the camera planning space for permissible camera trajectories satisfying image constraints (e.g., camera field of view and occlusions) and simultaneously tracks these trajectories in the robot configuration space to check for robot kinematic constraints and collision with obstacles. The exploration in camera planning space follows a tree-based randomized planning scheme and a local controller is used to track camera trajectories in the robot configuration space. The proposed framework yields global trajectories for the whole robotic system. The solution trajectory is projected into the image space to obtain the corresponding feature trajectories pertinent to a target object. An image-based visual servoing scheme is then adopted to execute the solution feature trajectories. We implemented the proposed framework on a 6 degrees of freedom (DOF) robotic arm and a 9-DOF wheeled mobile manipulator. The effectiveness of the proposed planning scheme in accounting for a variety of image and physical constraints is shown through a number of real world experiments. We also provide an empirical study on the performance of the image-based trajectory tracking scheme under modeling and calibration uncertainties.

Download or read book Trajectory Planning for Hyper Redundant Manipulators in Constrained Workspaces written by Mahdi Fallahinejad Ghajari and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Practical Motion Planning in Robotics written by Kamal Gupta and published by Chichester, England ; Toronto : J. Wiley. This book was released on 1998-10-15 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Motion Planning in Robotics Current Approaches and Future Directions Edited by Kamal Gupta Simon Fraser University, Burnaby, Canada Angel P. del Pobil Jaume-l University, Castellon, Spain Designed to bridge the gap between research and industry, Practical Motion Planning in Robotics brings theoretical advances to bear on real-world applications. Capitalizing on recent progress, this comprehensive study emphasizes the practical aspects of techniques for collision detection, obstacle avoidance, path planning and manipulation planning. The broad approach spans both model- and sensor-based motion planning, collision detection and geometric complexity, and future directions. Features include: - Review of state-of-the-art techniques and coverage of the main issues to be considered in the development of motion planners for use in real applications - Focus on gross motion planning for articulated arms enabling robots to perform non-contact tasks with relatively high tolerances plus brief consideration of mobile robots - The use of efficient algorithms to tackle incremental changes in the environment - Illlustration of robot motion planning applications in virtual prototyping and the shipbuilding industry - Demonstration of efficient path planners combining both local and global planning approaches in conjunction with efficient techniques for collision detection and distance computations - International contributions from academia and industry Combining theory and practice, this timely book will appeal to academic researchers and practising engineers in the fields of robotic systems, mechatronics and computer science.

Download or read book Repetitive Motion Planning and Control of Redundant Robot Manipulators written by Yunong Zhang and published by Springer Science & Business Media. This book was released on 2014-07-08 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Repetitive Motion Planning and Control of Redundant Robot Manipulators presents four typical motion planning schemes based on optimization techniques, including the fundamental RMP scheme and its extensions. These schemes are unified as quadratic programs (QPs), which are solved by neural networks or numerical algorithms. The RMP schemes are demonstrated effectively by the simulation results based on various robotic models; the experiments applying the fundamental RMP scheme to a physical robot manipulator are also presented. As the schemes and the corresponding solvers presented in the book have solved the non-repetitive motion problems existing in redundant robot manipulators, it is of particular use in applying theoretical research based on the quadratic program for redundant robot manipulators in industrial situations. This book will be a valuable reference work for engineers, researchers, advanced undergraduate and graduate students in robotics fields. Yunong Zhang is a professor at The School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China; Zhijun Zhang is a research fellow working at the same institute.

Download or read book Probabilistic roadmap based path planning for mobile robots written by and published by . This book was released on 2014 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Spatio temporal Probabilistic Path Planning for Autonomous Robot Navigation written by Om Krishna Gupta and published by . This book was released on 2011 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Path Planning of Robot Manipulator Using Bezier Technique written by Alaa Hassan and published by LAP Lambert Academic Publishing. This book was released on 2014-05-28 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robot manipulator is one of the motivation disciplines in industrial and educational applications. It is designed to be flexible in general motion to move objects from one position to another with smooth movement. In this work the motion planning is based on modeling and analysis of 5 degree of freedom (DOF), robot manipulator is the main objective of this thesis, solving the modeling problem is necessary before applying any motion techniques to guarantee the execution of any task according to a desired input with minimum error. Deriving both forward and inverse kinematics equations is an important step in robot modeling, an analytical solution for the robot manipulator has been worked in this thesis to obtain a path control using forward and inverse kinematics methods. By these methods manipulator's joints angles are determined from the required target given in Cartesian space. This work tests some vital tasks in industry, these are: pick and place operation, geometric path-based path planning, obstacle avoidance, and path tracking.

Download or read book Motion Planning with Localization and Mapping Uncertainties for a Mobile Manipulator in Exploration and Inspection Tasks written by Yifeng Huang and published by . This book was released on 2009 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: We address the motion planning (MP) problem in real world robotic exploration and inspection tasks, where robot localization and mapping uncertainties have to be incorporated into the planned motions. The robot considered in this work is a mobile manipulator system, which combines the mobility of the base with the dexterousness of the manipulator. The first part of this work considers localization and mapping uncertainties in the motion planning problem. We propose RRT-SLAM, which uses a rapidly exploring random tree (RRT) in conjunction with a simulated particle based simultaneous localization and mapping (SLAM) algorithm to expand the tree. The simulated SLAM explicitly accounts for localization and mapping uncertainties in the planning stage. Moreover, the RRT itself is represented in the uncertainty-configuration space (UC-space), which is an augmented configuration space with an extra dimension of uncertainty. The collision probability along a planned path is explicitly calculated and is used to select a planned path. We further address the efficiency of the RRT-SLAM in the UC-space. We treat the issue from a data clustering point of view and propose a fractal dimension (FD) based checking criterion for efficient node generation,and demonstrate the positive results in simulations. The second part of this research addresses planning motions for the manipulator with the base staying stationary. Therefore, no sensor observation is available during the motion. We extend the probabilistic roadmap (PRM) algorithm to plan motions. Since the base pose of the manipulator is not precisely known due to the localization uncertainty, the path query of the roadmap becomes a constrained shortest path problem. We prove that this path query is an NP-hard problem, and propose an lazy path query algorithm that judiciously combines a k-shortest path algorithm with a labeling algorithm to achieve efficiency. The RRT-SLAM is tested on an actual PowerBot and the experimental results show the effectiveness and benefits of our integrated approach. We also implemented and tested our integrated planner for the mobile manipulator in simulations. The effectiveness of the combined integrated planner is demonstrated via these simulations.

Download or read book Probabilistic Roadmaps for Path Planning in High dimensional Configuration Spaces written by Lydia Kavraki and published by . This book was released on 1994 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new motion planning method for robots in static workspaces is presented. This method proceeds according to two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collision-free configurations and edges to feasible paths between these configurations. These paths are computed using a simple and fast local planner. In the query phase, any given start and goal configurations of the robot are connected to two nodes of the roadmap; the roadmap is then searched for a path joining these two nodes. The method is general and easy to implement. It can be applied to virtually any type of holonomic robot. It requires selecting certain parameters (e.g., the duration of the learning phase) whose values depend on the considered scenes, that is the robots and their workspaces. But these values turn out to be relatively easy to choose. Increased efficiency can also be achieved by tailoring some components of the method (e.g., the local planner) to the considered robots. In this paper the method is applied to planar articulated robots with many degrees of freedom. Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation (approximately 150 MIPS), after learning for relatively short periods of time (a few dozen seconds).

Download or read book Time optimal Path Planning of Robotic Manipulators written by Chia-Ju Wu and published by . This book was released on 1990 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Probability based Path Planning for Stochastic Nonholonomic Systems with Obstacle Avoidance written by Jianping Lin and published by . This book was released on 2015 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: There exist various path planning methods in robotics. The Probabilistic Roadmap and Rapidly-exploring Random Tree (RRT) became popular in recent decades. It is known that the RRT is more suitable for nonholonomic systems. The RRT is a sampling-based algorithm which is designed for path planning problem and is efficient to handle high-dimensional configuration space (C-space) and nonholonomic constraints. Under the constraints, the RRT can generate paths between an initial state and a goal state while avoiding obstacles. However it does not guarantee that the resulting path is optimal. In systems with stochasticity, targeting error and closeness of the obstacle to the planned path can be considered to obtain the optimal path. In this thesis, the targeting error is defined as the root-mean-square (RMS) distance from the path samples to the desired target and the closeness is defined as probability of obstacle collision. Then, a cost function is defined as a sum of the targeting error and the obstacle closeness, and numerically minimized to find the path. The RRT result serves as an initial starting point for this subsequent optimization.

Download or read book Robot Dynamics And Control written by Mark W Spong and published by John Wiley & Sons. This book was released on 2008-08-04 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained introduction to practical robot kinematics and dynamics includes a comprehensive treatment of robot control. It provides background material on terminology and linear transformations, followed by coverage of kinematics and inverse kinematics, dynamics, manipulator control, robust control, force control, use of feedback in nonlinear systems, and adaptive control. Each topic is supported by examples of specific applications. Derivations and proofs are included in many cases. The book includes many worked examples, examples illustrating all aspects of the theory, and problems.

Download or read book Task Based Global Motion Planning of Multiple Manipulators in Time varying Environments written by Achint Aggarwal and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of robotics is clearly seen to be heading towards a world in which humans and robots can exist together safely and coherently be it in industries, households or battlefields. The primary obstacle for this harmonistic coexistence is the inability of robots to interact effectively and safely with the environment. Human machine interaction still seems to be far off until the development of effective and reliable robots that understand their environment and interact with it safely. The application of robots in industrial environments has over the last two decades received a significant impetus, such that the robots can now perform pre-programmed and repetitive low-valued tasks almost to perfection. However, the need of the hour is to make robots go beyond this level and practically start augmenting human capability and reducing human drudgery even outside the factory floor. This makes robot motion planning one of the most important areas in robotics research. Without a motion planner for manipulators and mobile robots, human operators have to constantly monitor and define their detailed motion. An automatic motion planner will relieve the operators from this tedious job and enable them to exercise control at a supervisory level. This in turn, increases efficiency by eliminating human errors. Further, path planning can be considered to be the backbone of any motion planning algorithm. An efficient path planner with added performance criteria and constraints makes an efficient motion planner. This specific research effort of developing a motion planner falls within the broader goal of developing a safety architecture that enables high performance intelligent machines that coexist and cooperate safely with other systems and humans. A large body of research in the area of robotics focuses on the path planning of mobile robots while the manipulators' ability to effectively operate autonomously in cluttered and dynamically changing environments stays relatively under explored. This work will rely on the past achievements in collision detection, obstacle avoidance and motion planning of the Robotics Research Group (RRG) at the University of Texas at Austin (UT Austin). This area of research offers chances for a wide breadth of advancement in robotics as it can be applied to traditional stationary robots, both redundant and non-redundant manipulators, as well as to mobile manipulators where both the path of the manipulator itself and the path of the manipulator's mobile base must be accounted for when attempting to plan collision free paths.

Download or read book Incremental High Quality Probabilistic Roadmap Construction for Robot Path Planning written by Yueqiao Li and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Probabilistic Motion Planning and Optimization Incorporating Chance Constraints written by Siyu Dai (S.M.) and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: For high-dimensional robots, motion planning is still a challenging problem, especially for manipulators mounted to underwater vehicles or human support robots where uncertainties and risks of plan failure can have severe impact. However, existing risk-aware planners mostly focus on low-dimensional planning tasks, meanwhile planners that can account for uncertainties and react fast in high degree-of-freedom (DOF) robot planning tasks are lacking. In this thesis, a risk-aware motion planning and execution system called Probabilistic Chekov (p-Chekov) is introduced, which includes a deterministic stage and a risk-aware stage. A systematic set of experiments on existing motion planners as well as p-Chekov is also presented. The deterministic stage of p-Chekov leverages the recent advances in obstacle-aware trajectory optimization to improve the original tube-based-roadmap Chekov planner. Through experiments in 4 common application scenarios with 5000 test cases each, we show that using sampling-based planners alone on high DOF robots can not achieve a high enough reaction speed, whereas the popular trajectory optimizer TrajOpt with naive straight-line seed trajectories has very high collision rate despite its high planning speed. To the best of our knowledge, this is the first work that presents such a systematic and comprehensive evaluation of state-of-the-art motion planners, which are based on a significant amount of experiments. We then combine different stand-alone planners with trajectory optimization. The results show that the deterministic planning part of p-Chekov, which combines a roadmap approach that caches the all pair shortest paths solutions and an online obstacle-aware trajectory optimizer, provides superior performance over other standard sampling-based planners' combinations. Simulation results show that, in typical real-life applications, this "roadmap + TrajOpt" approach takes about 1 s to plan and the failure rate of its solutions is under 1%. The risk-aware stage of p-Chekov accounts for chance constraints through state probability distribution and collision probability estimation. Based on the deterministic Chekov planner, p-Chekov incorporates a linear-quadratic Gaussian motion planning (LQG-MP) approach into robot state probability distribution estimation, applies quadrature-sampling theories to collision risk estimation, and adapts risk allocation approaches for chance constraint satisfaction. It overcomes existing risk-aware planners' limitation in real-time motion planning tasks with high-DOF robots in 3- dimensional non-convex environments. The experimental results in this thesis show that this new risk-aware motion planning and execution system can effectively reduce collision risk and satisfy chance constraints in typical real-world planning scenarios for high-DOF robots. This thesis makes the following three main contributions: (1) a systematic evaluation of several state-of-the-art motion planners in realistic planning scenarios, including popular sampling-based motion planners and trajectory optimization type motion planners, (2) the establishment of a "roadmap + TrajOpt" deterministic motion planning system that shows superior performance in many practical planning tasks in terms of solution feasibility, optimality and reaction time, and (3) the development of a risk-aware motion planning and execution system that can handle high-DOF robotic planning tasks in 3-dimensional non-convex environments.

Download or read book Optimal Path Planning for Robotic Manipulators written by Michael Robert Madden and published by . This book was released on 1986 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: