Exploiting Direct Optimal Control For Motion Planning In Unstructured Environments

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Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments

Author : Kristoffer Bergman
Publisher : Linköping University Electronic Press
ISBN 13 : 9179296777
Total Pages : 60 pages
Book Rating : 4.1/5 (792 download)

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Book Synopsis Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments by : Kristoffer Bergman

Download or read book Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments written by Kristoffer Bergman and published by Linköping University Electronic Press. This book was released on 2021-03-16 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. The objective in optimal motion planning problems is to find feasible motion plans that also optimize a performance measure. From a control perspective, the problem is an instance of an optimal control problem. This thesis addresses optimal motion planning problems for complex dynamical systems that operate in unstructured environments, where no prior reference such as road-lane information is available. Some example scenarios are autonomous docking of vessels in harbors and autonomous parking of self-driving tractor-trailer vehicles at loading sites. The focus is to develop optimal motion planning algorithms that can reliably be applied to these types of problems. This is achieved by combining recent ideas from automatic control, numerical optimization and robotics. The first contribution is a systematic approach for computing local solutions to motion planning problems in challenging unstructured environments. The solutions are computed by combining homotopy methods and direct optimal control techniques. The general principle is to define a homotopy that transforms, or preferably relaxes, the original problem to an easily solved problem. The approach is demonstrated in motion planning problems in 2D and 3D environments, where the presented method outperforms a state-of-the-art asymptotically optimal motion planner based on random sampling. The second contribution is an optimization-based framework for automatic generation of motion primitives for lattice-based motion planners. Given a family of systems, the user only needs to specify which principle types of motions that are relevant for the considered system family. Based on the selected principle motions and a selected system instance, the framework computes a library of motion primitives by simultaneously optimizing the motions and the terminal states. The final contribution of this thesis is a motion planning framework that combines the strengths of sampling-based planners with direct optimal control in a novel way. The sampling-based planner is applied to the problem in a first step using a discretized search space, where the system dynamics and objective function are chosen to coincide with those used in a second step based on optimal control. This combination ensures that the sampling-based motion planner provides a feasible motion plan which is highly suitable as warm-start to the optimal control step. Furthermore, the second step is modified such that it also can be applied in a receding-horizon fashion, where the proposed combination of methods is used to provide theoretical guarantees in terms of recursive feasibility, worst-case objective function value and convergence to the terminal state. The proposed motion planning framework is successfully applied to several problems in challenging unstructured environments for tractor-trailer vehicles. The framework is also applied and tailored for maritime navigation for vessels in archipelagos and harbors, where it is able to compute energy-efficient trajectories which complies with the international regulations for preventing collisions at sea.

On Motion Planning Using Numerical Optimal Control

Author : Kristoffer Bergman
Publisher : Linköping University Electronic Press
ISBN 13 : 9176850579
Total Pages : 91 pages
Book Rating : 4.1/5 (768 download)

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Book Synopsis On Motion Planning Using Numerical Optimal Control by : Kristoffer Bergman

Download or read book On Motion Planning Using Numerical Optimal Control written by Kristoffer Bergman and published by Linköping University Electronic Press. This book was released on 2019-05-28 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. In this thesis, the objective is not only to find feasible solutions to a motion planning problem, but solutions that also optimize some kind of performance measure. From a control perspective, the resulting problem is an instance of an optimal control problem. In this thesis, the focus is to further develop optimal control algorithms such that they be can used to obtain improved solutions to motion planning problems. This is achieved by combining ideas from automatic control, numerical optimization and robotics. First, a systematic approach for computing local solutions to motion planning problems in challenging environments is presented. The solutions are computed by combining homotopy methods and numerical optimal control techniques. The general principle is to define a homotopy that transforms, or preferably relaxes, the original problem to an easily solved problem. The approach is demonstrated in motion planning problems in 2D and 3D environments, where the presented method outperforms both a state-of-the-art numerical optimal control method based on standard initialization strategies and a state-of-the-art optimizing sampling-based planner based on random sampling. Second, a framework for automatically generating motion primitives for lattice-based motion planners is proposed. Given a family of systems, the user only needs to specify which principle types of motions that are relevant for the considered system family. Based on the selected principle motions and a selected system instance, the algorithm not only automatically optimizes the motions connecting pre-defined boundary conditions, but also simultaneously optimizes the terminal state constraints as well. In addition to handling static a priori known system parameters such as platform dimensions, the framework also allows for fast automatic re-optimization of motion primitives if the system parameters change while the system is in use. Furthermore, the proposed framework is extended to also allow for an optimization of discretization parameters, that are are used by the lattice-based motion planner to define a state-space discretization. This enables an optimized selection of these parameters for a specific system instance. Finally, a unified optimization-based path planning approach to efficiently compute locally optimal solutions to advanced path planning problems is presented. The main idea is to combine the strengths of sampling-based path planners and numerical optimal control. The lattice-based path planner is applied to the problem in a first step using a discretized search space, where system dynamics and objective function are chosen to coincide with those used in a second numerical optimal control step. This novel tight combination of a sampling-based path planner and numerical optimal control makes, in a structured way, benefit of the former method’s ability to solve combinatorial parts of the problem and the latter method’s ability to obtain locally optimal solutions not constrained to a discretized search space. The proposed approach is shown in several practically relevant path planning problems to provide improvements in terms of computation time, numerical reliability, and objective function value.

Sensor Management for Target Tracking Applications

Author : Per Boström-Rost
Publisher : Linköping University Electronic Press
ISBN 13 : 9179296726
Total Pages : 61 pages
Book Rating : 4.1/5 (792 download)

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Book Synopsis Sensor Management for Target Tracking Applications by : Per Boström-Rost

Download or read book Sensor Management for Target Tracking Applications written by Per Boström-Rost and published by Linköping University Electronic Press. This book was released on 2021-04-12 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many practical applications, such as search and rescue operations and environmental monitoring, involve the use of mobile sensor platforms. The workload of the sensor operators is becoming overwhelming, as both the number of sensors and their complexity are increasing. This thesis addresses the problem of automating sensor systems to support the operators. This is often referred to as sensor management. By planning trajectories for the sensor platforms and exploiting sensor characteristics, the accuracy of the resulting state estimates can be improved. The considered sensor management problems are formulated in the framework of stochastic optimal control, where prior knowledge, sensor models, and environment models can be incorporated. The core challenge lies in making decisions based on the predicted utility of future measurements. In the special case of linear Gaussian measurement and motion models, the estimation performance is independent of the actual measurements. This reduces the problem of computing sensing trajectories to a deterministic optimal control problem, for which standard numerical optimization techniques can be applied. A theorem is formulated that makes it possible to reformulate a class of nonconvex optimization problems with matrix-valued variables as convex optimization problems. This theorem is then used to prove that globally optimal sensing trajectories can be computed using off-the-shelf optimization tools. As in many other fields, nonlinearities make sensor management problems more complicated. Two approaches are derived to handle the randomness inherent in the nonlinear problem of tracking a maneuvering target using a mobile range-bearing sensor with limited field of view. The first approach uses deterministic sampling to predict several candidates of future target trajectories that are taken into account when planning the sensing trajectory. This significantly increases the tracking performance compared to a conventional approach that neglects the uncertainty in the future target trajectory. The second approach is a method to find the optimal range between the sensor and the target. Given the size of the sensor's field of view and an assumption of the maximum acceleration of the target, the optimal range is determined as the one that minimizes the tracking error while satisfying a user-defined constraint on the probability of losing track of the target. While optimization for tracking of a single target may be difficult, planning for jointly maintaining track of discovered targets and searching for yet undetected targets is even more challenging. Conventional approaches are typically based on a traditional tracking method with separate handling of undetected targets. Here, it is shown that the Poisson multi-Bernoulli mixture (PMBM) filter provides a theoretical foundation for a unified search and track method, as it not only provides state estimates of discovered targets, but also maintains an explicit representation of where undetected targets may be located. Furthermore, in an effort to decrease the computational complexity, a version of the PMBM filter which uses a grid-based intensity to represent undetected targets is derived.

Realtime Motion Planning for Manipulator Robots Under Dynamic Environments

Author : Olabanjo Ogunlowore
Publisher :
ISBN 13 :
Total Pages : 113 pages
Book Rating : 4.:/5 (86 download)

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Book Synopsis Realtime Motion Planning for Manipulator Robots Under Dynamic Environments by : Olabanjo Ogunlowore

Download or read book Realtime Motion Planning for Manipulator Robots Under Dynamic Environments written by Olabanjo Ogunlowore and published by . This book was released on 2013 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report presents optimal control methods integrated with hierarchical control framework to realize real-time collision-free optimal trajectories for motion control in kinematic chain manipulator (KCM) robot systems under dynamic environments. Recently, they have been increasingly used in applications where manipulators are required to interact with random objects and humans. As a result, more complex trajectory planning schemes are required. The main objective of this research is to develop new motion control strategies that can enable such robots to operate efficiently and optimally in such unknown and dynamic environments. Two direct optimal control methods: The direct collocation method and discrete mechanics for optimal control methods are investigated for solving the related constrained optimal control problem and the results are compared. Using the receding horizon control structure, open-loop sub-optimal trajectories are generated as real-time input to the controller as opposed to the predefined trajectory over the entire time duration. This, in essence, captures the dynamic nature of the obstacles. The closed-loop position controller is then engaged to span the robot end-effector along this desired optimal path by computing appropriate torque commands for the joint actuators. Employing a two-degree of freedom technique, collision-free trajectories and robot environment information are transmitted in real-time by the aid of a bidirectional connectionless datagram transfer. A hierarchical network control platform is designed to condition triggering of precedent activities between a dedicated machine computing the optimal trajectory and the real-time computer running a low-level controller. Experimental results on a 2-link planar robot are presented to validate the main ideas. Real-time implementation of collision-free workspace trajectory control is achieved for cases where obstacles are arbitrarily changing in the robot workspace.

Collision Avoidance Techniques and Optimal Synthesis for Motion Planning Applications

Author : Andrei Marchidan
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Collision Avoidance Techniques and Optimal Synthesis for Motion Planning Applications by : Andrei Marchidan

Download or read book Collision Avoidance Techniques and Optimal Synthesis for Motion Planning Applications written by Andrei Marchidan and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation focuses on the problem of motion planning for autonomous agents that are required to perform fast and reactive maneuvers. In realistic situations, this problem needs to be solved in real-time for environments that are both dynamic and partially known. The success of the provided motion plans also relies on the agent’s ability to accurately perform the prescribed maneuvers and, as such, consideration of the input constraints is often times necessary. The problem can be posed in two different ways: as a controllability problem, where trajectory generation is only concerned with satisfying the given boundary conditions, system constraints (dynamic and input constraints) and state constraints (forbidden areas in the state space); or as an optimal control problem, where the trajectory is also required to optimize some performance measure. The main contributions of this dissertation are two-fold. First, a new numerical technique is proposed for solving time-optimal control problems for an agent moving in a spatiotemporal drift field. The solution technique computes the minimum time function and the corresponding time-optimal feedback control law, while using an extremal front expansion procedure to filter out sub-optimal solutions. This methodology can be applied for a rich class of time-optimal control problems where the control input structure is determined by a parameter family of differential equations. To demonstrate its applicability, the numerical technique is implemented for the Zermelo navigation problem on a sphere and for the steering problem of a self-propelled particle in a flow field. Next, in the second part of this dissertation, the controllability problem in the presence of obstacles can be solved using local reactive collision avoidance vector fields. The proposed approach uses the concept of local parametrized guidance vector fields that are generated directly from the agent model and encode collision avoidance behaviors. Their generation relies on a decomposition of agent kinematics and on a proximity-based velocity modulation determined by specific eigenvalue functions. Further exploiting the modulation properties arising from the nature of these eigenvalue functions, curvature constraints can be guaranteed. Closed-form steering laws are determined in accordance with the computed collision avoidance vector fields and can provide the necessary avoidance maneuvers to guarantee problem feasibility. Throughout this dissertation, examples and simulation results in different types of environments are presented and discussed. In the final part of this dissertation, the motion planning problem is tackled for more complex environments. The two proposed methodologies for optimal control and for collision avoidance are combined to yield a hybrid controller that generates near-optimal feasible plans in the presence of multiple static and moving obstacles and of spatiotemporal drift fields

Efficient Numerical Optimal Control for Motion Planning and Control of Mobile Robots

Author : Michael Neunert
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Efficient Numerical Optimal Control for Motion Planning and Control of Mobile Robots by : Michael Neunert

Download or read book Efficient Numerical Optimal Control for Motion Planning and Control of Mobile Robots written by Michael Neunert and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Recursive Dynamics and Optimal Control Techniques for Human Motion Planning

Author : Janzen Lo
Publisher :
ISBN 13 :
Total Pages : 119 pages
Book Rating : 4.:/5 (187 download)

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Book Synopsis Recursive Dynamics and Optimal Control Techniques for Human Motion Planning by : Janzen Lo

Download or read book Recursive Dynamics and Optimal Control Techniques for Human Motion Planning written by Janzen Lo and published by . This book was released on 1998 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Multi-layer Approach to Motion Planning in Obstacle Rich Environment

Author : Sung Hyun Kim
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (68 download)

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Book Synopsis Multi-layer Approach to Motion Planning in Obstacle Rich Environment by : Sung Hyun Kim

Download or read book Multi-layer Approach to Motion Planning in Obstacle Rich Environment written by Sung Hyun Kim and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A widespread use of robotic technology in civilian and military applications has generated a need for advanced motion planning algorithms that are real-time implementable. These algorithms are required to navigate autonomous vehicles through obstacle-rich environments. This research has led to the development of the multilayer trajectory generation approach. It is built on the principle of separation of concerns, which partitions a given problem into multiple independent layers, and addresses complexity that is inherent at each level. We partition the motion planning algorithm into a roadmap layer and an optimal control layer. At the roadmap layer, elements of computational geometry are used to process the obstacle rich environment and generate feasible sets. These are used by the optimal control layer to generate trajectories while satisfying dynamics of the vehicle. The roadmap layer ignores the dynamics of the system, and the optimal control layer ignores the complexity of the environment, thus achieving a separation of concern. This decomposition enables computationally tractable methods to be developed for addressing motion planning in complex environments. The approach is applied in known and unknown environments. The methodology developed in this thesis has been successfully applied to a 6 DOF planar robotic testbed. Simulation results suggest that the planner can generate trajectories that navigate through obstacles while satisfying dynamical constraints.

Perception-driven Optimal Motion Planning Under Resource Constraints

Author : Thomas Sayre-McCord
Publisher :
ISBN 13 :
Total Pages : 112 pages
Book Rating : 4.:/5 (18 download)

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Book Synopsis Perception-driven Optimal Motion Planning Under Resource Constraints by : Thomas Sayre-McCord

Download or read book Perception-driven Optimal Motion Planning Under Resource Constraints written by Thomas Sayre-McCord and published by . This book was released on 2019 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past few years there has been a new wave of interest in fully autonomous robots operating in the real world, with applications from autonomous driving to search and rescue. These robots are expected to operate at high speeds in unknown, unstructured environments using only onboard sensing and computation, presenting significant challenges for high performance autonomous navigation. To enable research in these challenging scenarios, the first part of this thesis focuses on the development of a custom high-performance research UAV capable of high speed autonomous flight using only vision and inertial sensors. This research platform was used to develop stateof-the-art onboard visual inertial state estimation at high speeds in challenging scenarios such as flying through window gaps. While this platform is capable of high performance state estimation and control, its capabilities in unknown environments are severely limited by the computational costs of running traditional vision-based mapping and motion planning algorithms on an embedded platform. Motivated by these challenges, the second part of this thesis presents an algorithmic approach to the problem of motion planning in an unknown environment when the computational costs of mapping all available sensor data is prohibitively high. The algorithm is built around a tree of dynamically feasible and free space optimal trajectories to the goal state in configuration space. As the algorithm progresses it iteratively switches between processing new sensor data and locally updating the search tree. We show that the algorithm produces globally optimal motion plans, matching the optimal solution for the case with the full (unprocessed) sensor data, while only processing a subset of the data. The mapping and motion planning algorithm is demonstrated on a number of test systems, with a particular focus on a six-dimensional thrust limited model of a quadrotor.

Optimality and Optimal Control in Robot Motion Planning

Author : Marion Leibold
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)

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Book Synopsis Optimality and Optimal Control in Robot Motion Planning by : Marion Leibold

Download or read book Optimality and Optimal Control in Robot Motion Planning written by Marion Leibold and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Motion Planning in Dynamic Environments

Author : Kikuo Fujimura
Publisher : Springer Science & Business Media
ISBN 13 : 4431681655
Total Pages : 190 pages
Book Rating : 4.4/5 (316 download)

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Book Synopsis Motion Planning in Dynamic Environments by : Kikuo Fujimura

Download or read book Motion Planning in Dynamic Environments written by Kikuo Fujimura and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Workbench represents an important new contribution in the field of practical computer technology. TOSIYASU L. KUNII To my parents Kenjiro and Nori Fujimura Preface Motion planning is an area in robotics that has received much attention recently. Much of the past research focuses on static environments - various methods have been developed and their characteristics have been well investigated. Although it is essential for autonomous intelligent robots to be able to navigate within dynamic worlds, the problem of motion planning in dynamic domains is relatively little understood compared with static problems.

A Generalized Label Correcting Method for Optimal Kinodynamic Motion Planning

Author : Brian Paden
Publisher :
ISBN 13 :
Total Pages : 122 pages
Book Rating : 4.:/5 (12 download)

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Book Synopsis A Generalized Label Correcting Method for Optimal Kinodynamic Motion Planning by : Brian Paden

Download or read book A Generalized Label Correcting Method for Optimal Kinodynamic Motion Planning written by Brian Paden and published by . This book was released on 2017 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nearly all autonomous robotic systems use some form of motion planning to compute reference motions through their environment. An increasing use of autonomous robots in a broad range of applications creates a need for efficient, general purpose motion planning algorithms that are applicable in any of these new application domains. This thesis presents a resolution complete optimal kinodynamic motion planning algorithm based on a direct forward search of the set of admissible input signals to a dynamical model. The advantage of this generalized label correcting method is that it does not require a local planning subroutine as in the case of related methods. Preliminary material focuses on new topological properties of the canonical problem formulation that are used to show continuity of the performance objective. These observations are used to derive a generalization of Bellman's principle of optimality in the context of kinodynamic motion planning. A generalized label correcting algorithm is then proposed which leverages these results to prune candidate input signals from the search when their cost is greater than related signals. The second part of this thesis addresses admissible heuristics for kinodynamic motion planning. An admissibility condition is derived that can be used to verify the admissibility of candidate heuristics for a particular problem. This condition also characterizes a convex set of admissible heuristics. A linear program is formulated to obtain a heuristic which is as close to the optimal cost-to-go as possible while remaining admissible. This optimization is justified by showing its solution coincides with the solution to the Hamilton-Jacobi-Bellman equation. Lastly, a sum-of-squares relaxation of this infinite-dimensional linear program is proposed for obtaining provably admissible approximate solutions.

Planning Algorithms

Author : Steven M. LaValle
Publisher : Cambridge University Press
ISBN 13 : 9780521862059
Total Pages : 844 pages
Book Rating : 4.8/5 (62 download)

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Book Synopsis Planning Algorithms by : Steven M. LaValle

Download or read book Planning Algorithms written by Steven M. LaValle and published by Cambridge University Press. This book was released on 2006-05-29 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.

On motion planning and control for truck and trailer systems

Author : Oskar Ljungqvist
Publisher : Linköping University Electronic Press
ISBN 13 : 9176851303
Total Pages : 78 pages
Book Rating : 4.1/5 (768 download)

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Book Synopsis On motion planning and control for truck and trailer systems by : Oskar Ljungqvist

Download or read book On motion planning and control for truck and trailer systems written by Oskar Ljungqvist and published by Linköping University Electronic Press. This book was released on 2019-01-22 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decades, improved sensor and hardware technologies as well as new methods and algorithms have made self-driving vehicles a realistic possibility in the near future. Thanks to this technology enhancement, many leading automotive and technology companies have turned their attention towards developing advanced driver assistance systems (ADAS) and self-driving vehicles. Autonomous vehicles are expected to have their first big impact in closed areas, such as mines, harbors and loading/offloading sites. In such areas, the legal requirements are less restrictive and the surrounding environment is more controlled and predictable compared to urban areas. Expected positive outcomes include increased productivity and safety, reduced emissions and the possibility to relieve the human from performing complex or dangerous tasks. Within these sites, different truck and trailer systems are used to transport materials. These systems are composed of several interconnected modules, and are thus large and highly unstable while reversing. This thesis addresses the problem of designing efficient motion planning and feedback control frameworks for such systems. First, a cascade controller for a reversing truck with a dolly-steered trailer is presented. The unstable modes of the system is stabilized around circular equilibrium configurations using a gain-scheduled linear quadratic (LQ) controller together with a higher-level pure pursuit controller to enable path following of piecewise linear reference paths. The cascade controller is then used within a rapidly-exploring random tree (RRT) framework and the complete motion planning and control framework is demonstrated on a small-scale test vehicle. Second, a path following controller for a reversing truck with a dolly-steered trailer is proposed for the case when the obtained motion plan is kinematically feasible. The control errors of the system are modeled in terms of their deviation from the nominal path and a stabilizing LQ controller with feedforward action is designed based on the linearization of the control error model. Stability of the closed-loop system is proven by combining global optimization, theory from linear differential inclusions and linear matrix inequality techniques. Third, a systematic framework is presented for analyzing stability of the closed-loop system consisting of a controlled vehicle and a feedback controller, executing a motion plan computed by a lattice planner. When this motion planner is considered, it is shown that the closed-loop system can be modeled as a nonlinear hybrid system. Based on this, a novel method is presented for analyzing the behavior of the tracking error, how to design the feedback controller and how to potentially impose constraints on the motion planner in order to guarantee that the tracking error is bounded and decays towards zero. Fourth, a complete motion planning and control solution for a truck with a dolly-steered trailer is presented. A lattice-based motion planner is proposed, where a novel parametrization of the vehicle’s state-space is proposed to improve online planning time. A time-symmetry result is established that enhance the numerical stability of the numerical optimal control solver used for generating the motion primitives. Moreover, a nonlinear observer for state estimation is developed which only utilizes information from sensors that are mounted on the truck, making the system independent of additional trailer sensors. The proposed framework is implemented on a full-scale truck with a dolly-steered trailer and results from a series of field experiments are presented.

The DARPA Urban Challenge

Author : Martin Buehler
Publisher : Springer
ISBN 13 : 364203991X
Total Pages : 651 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis The DARPA Urban Challenge by : Martin Buehler

Download or read book The DARPA Urban Challenge written by Martin Buehler and published by Springer. This book was released on 2009-11-26 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: By the dawn of the new millennium, robotics has undergone a major transformation in scope and dimensions. This expansion has been brought about by the maturity of the field and the advances in its related technologies. From a largely dominant industrial focus, robotics has been rapidly expanding into the challenges of the human world. The new generation of robots is expected to safely and dependably co-habitat with humans in homes, workplaces, and communities, providing support in services, entertainment, education, healthcare, manufacturing, and assistance. Beyond its impact on physical robots, the body of knowledge robotics has produced is revealing a much wider range of applications reaching across diverse research areas and scientific disciplines, such as: biomechanics, haptics, neurosciences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are proving an abundant source of stimulation and insights for the field of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. The goal of the series of Springer Tracts in Advanced Robotics (STAR) is to bring, in a timely fashion, the latest advances and developments in robotics on the basis of their significance and quality. It is our hope that the wider dissemination of research developments will stimulate more exchanges and collaborations among the research community and contribute to further advancement of this rapidly growing field.

Principles of Robot Motion

Author : Howie Choset
Publisher : MIT Press
ISBN 13 : 9780262033275
Total Pages : 642 pages
Book Rating : 4.0/5 (332 download)

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Book Synopsis Principles of Robot Motion by : Howie Choset

Download or read book Principles of Robot Motion written by Howie Choset and published by MIT Press. This book was released on 2005-05-20 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts. Robot motion planning has become a major focus of robotics. Research findings can be applied not only to robotics but to planning routes on circuit boards, directing digital actors in computer graphics, robot-assisted surgery and medicine, and in novel areas such as drug design and protein folding. This text reflects the great advances that have taken place in the last ten years, including sensor-based planning, probabalistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, rleating low-level implementation details to high-level algorithmic concepts.

Unmanned Aircraft Systems

Author : Ella Atkins
Publisher : John Wiley & Sons
ISBN 13 : 1118866452
Total Pages : 740 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Unmanned Aircraft Systems by : Ella Atkins

Download or read book Unmanned Aircraft Systems written by Ella Atkins and published by John Wiley & Sons. This book was released on 2017-01-17 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: UNMANNED AIRCRAF T SYSTEMS UNMANNED AIRCRAF T SYSTEMS An unmanned aircraft system (UAS), sometimes called a drone, is an aircraft without a human pilot on board ??? instead, the UAS can be controlled by an operator station on the ground or may be autonomous in operation. UAS are capable of addressing a broad range of applications in diverse, complex environments. Traditionally employed in mainly military applications, recent regulatory changes around the world are leading to an explosion of interest and wide-ranging new applications for UAS in civil airspace. Covering the design, development, operation, and mission profiles of unmanned aircraft systems, this single, comprehensive volume forms a complete, stand-alone reference on the topic. The volume integrates with the online Wiley Encyclopedia of Aerospace Engineering, providing many new and updated articles for existing subscribers to that work. The chapters cover the following items: Airframe configurations and design (launch systems, power generation, propulsion) Operations (missions, integration issues, and airspace access) Coordination (multivehicle cooperation and human oversight) With contributions from leading experts, this volume is intended to be a valuable addition, and a useful resource, for aerospace manufacturers and suppliers, governmental and industrial aerospace research establishments, airline and aviation industries, university engineering and science departments, and industry analysts, consultants, and researchers.