Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Path Planning For Autonomous Vehicle In Off Road Scenario
Download Path Planning For Autonomous Vehicle In Off Road Scenario full books in PDF, epub, and Kindle. Read online Path Planning For Autonomous Vehicle In Off Road Scenario ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Path Planning for Autonomous Vehicle in Off-Road Scenario by : Haiping Du
Download or read book Path Planning for Autonomous Vehicle in Off-Road Scenario written by Haiping Du and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The road topography information, such as bank angle and road slope, can significantly affect the trajectory tracking performance of the autonomous vehicle, so this information needs to be considered in the trajectory planning and tracking control for off-road autonomous vehicle. In this chapter, a two-level real-time dynamically integrated spatiotemporal-based trajectory planning and control method for off-road autonomous vehicle is proposed. In the upper-level trajectory planner, the most suitable time-parameterised trajectory with the minimum values of road slope and bank angle can be selected from a set of candidate trajectories. In the lower-level trajectory tracking controller, the sliding-mode control (SMC) technique is applied to control the vehicle and achieve the desired trajectory. Finally, simulation results are presented to verify the proposed integrated trajectory planning and control method and prove that the proposed integrated method has better overall tracking control and dynamics control performance than the conventional method both in the highway scenario and off-road scenario. Furthermore, the four-wheel-independent-steering (4WIS) and four-wheel-independent-driving (4WID) vehicle shows better tracking control performance than vehicle based on two-wheel model.
Book Synopsis Path Planning for Autonomous Vehicle by : Umar Zakir Abdul Hamid
Download or read book Path Planning for Autonomous Vehicle written by Umar Zakir Abdul Hamid and published by BoD – Books on Demand. This book was released on 2019-10-02 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).
Book Synopsis Trajectory Planning of an Autonomous Vehicle in Multi-Vehicle Traffic Scenarios by : Mahdi Morsali
Download or read book Trajectory Planning of an Autonomous Vehicle in Multi-Vehicle Traffic Scenarios written by Mahdi Morsali and published by Linköping University Electronic Press. This book was released on 2021-03-25 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tremendous industrial and academic progress and investments have been made in au-tonomous driving, but still many aspects are unknown and require further investigation,development and testing. A key part of an autonomous driving system is an efficient plan-ning algorithm with potential to reduce accidents, or even unpleasant and stressful drivingexperience. A higher degree of automated planning also makes it possible to have a betterenergy management strategy with improved performance through analysis of surroundingenvironment of autonomous vehicles and taking action in a timely manner. This thesis deals with planning of autonomous vehicles in different urban scenarios, road,and vehicle conditions. The main concerns in designing the planning algorithms, are realtime capability, safety and comfort. The planning algorithms developed in this thesis aretested in simulation traffic situations with multiple moving vehicles as obstacles. The re-search conducted in this thesis falls mainly into two parts, the first part investigates decou-pled trajectory planning algorithms with a focus on speed planning, and the second sectionexplores different coupled planning algorithms in spatiotemporal environments where pathand speed are calculated simultaneously. Additionally, a behavioral analysis is carried outto evaluate different tactical maneuvers the autonomous vehicle can have considering theinitial states of the ego and surrounding vehicles. Particularly relevant for heavy duty vehicles, the issues addressed in designing a safe speedplanner in the first part are road conditions such as banking, friction, road curvature andvehicle characteristics. The vehicle constraints on acceleration, jerk, steering, steer ratelimitations and other safety limitations such as rollover are further considerations in speedplanning algorithms. For real time purposes, a minimum working roll model is identified us-ing roll angle and lateral acceleration data collected in a heavy duty truck. In the decoupledplanners, collision avoiding is treated using a search and optimization based planner. In an autonomous vehicle, the structure of the road network is known to the vehicle throughmapping applications. Therefore, this key property can be used in planning algorithms toincrease efficiency. The second part of the thesis, is focused on handling moving obstaclesin a spatiotemporal environment and collision-free planning in complex urban structures.Spatiotemporal planning holds the benefits of exhaustive search and has advantages com-pared to decoupled planning, but the search space in spatiotemporal planning is complex.Support vector machine is used to simplify the search problem to make it more efficient.A SVM classifies the surrounding obstacles into two categories and efficiently calculate anobstacle free region for the ego vehicle. The formulation achieved by solving SVM, con-tains information about the initial point, destination, stationary and moving obstacles.These features, combined with smoothness property of the Gaussian kernel used in SVMformulation is proven to be able to solve complex planning missions in a safe way. Here, three algorithms are developed by taking advantages of SVM formulation, a greedysearch algorithm, an A* lattice based planner and a geometrical based planner. One general property used in all three algorithms is reduced search space through using SVM. In A*lattice based planner, significant improvement in calculation time, is achieved by using theinformation from SVM formulation to calculate a heuristic for planning. Using this heuristic,the planning algorithm treats a simple driving scenario and a complex urban structureequal, as the structure of the road network is included in SVM solution. Inspired byobserving significant improvements in calculation time using SVM heuristic and combiningthe collision information from SVM surfaces and smoothness property, a geometrical planneris proposed that leads to further improvements in calculation time. Realistic driving scenarios such as roundabouts, intersections and takeover maneuvers areused, to test the performance of the proposed algorithms in simulation. Different roadconditions with large banking, low friction and high curvature, and vehicles prone to safetyissues, specially rollover, are evaluated to calculate the speed profile limits. The trajectoriesachieved by the proposed algorithms are compared to profiles calculated by optimal controlsolutions.
Book Synopsis Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver by : Muhammad Aizzat Zakaria
Download or read book Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver written by Muhammad Aizzat Zakaria and published by . This book was released on 2019 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).
Book Synopsis Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver by : Muhammad Aizzat Zakaria
Download or read book Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation and Control Maneuver written by Muhammad Aizzat Zakaria and published by . This book was released on 2019 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).
Book Synopsis Autonomous Ground Vehicles by : Ümit Özgüner
Download or read book Autonomous Ground Vehicles written by Ümit Özgüner and published by Artech House. This book was released on 2011 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the near future, we will witness vehicles with the ability to provide drivers with several advanced safety and performance assistance features. Autonomous technology in ground vehicles will afford us capabilities like intersection collision warning, lane change warning, backup parking, parallel parking aids, and bus precision parking. Providing you with a practical understanding of this technology area, this innovative resource focuses on basic autonomous control and feedback for stopping and steering ground vehicles.Covering sensors, estimation, and sensor fusion to percept the vehicle motion and surrounding objects, this unique book explains the key aspects that makes autonomous vehicle behavior possible. Moreover, you find detailed examples of fusion and Kalman filtering. From maps, path planning, and obstacle avoidance scenarios...to cooperative mobility among autonomous vehicles, vehicle-to-vehicle communication, and vehicle-to-infrastructure communication, this forward-looking book presents the most critical topics in the field today.
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 Science & Business Media. This book was released on 2009-11-11 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.
Book Synopsis Autonomous Vehicle Obstacle Avoidance Maneuvers by :
Download or read book Autonomous Vehicle Obstacle Avoidance Maneuvers written by and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : Full market penetration for autonomous vehicle requires complete solutions for operation during winter driving conditions. This work addresses three key issues relevant to the dynamic response of an autonomous vehicle when faced with reduced friction due to snow and ice on the road when attempting a double lane change obstacle avoidance maneuver. Two low friction scenarios as well as an improvement to simulation methods are presented. The first low friction scenario an autonomous vehicle may encounter is one in which the road surface friction coefficient is incorrectly assumed to be dry pavement. This scenario could occur in the presence of clear ice on the road which is undetectable by the vehicle until it begins traversing the effected area. In this case, the vehicle must react in a way which maintains vehicle control during the maneuver by adapting to the loss of tractive force at the wheels. This work presents a method for altering the look ahead distance of the common pure pursuit lateral control method for autonomous vehicles. This method stabilizes the vehicle during the maneuvers by dynamically changing the look ahead distance based on cross track error in addition to vehicle velocity. Implementation in the autonomous test vehicle used in this work shows an elimination of off-road occurrences during double lane changes on ice and a 46\% reduction of off-read occurrences during single lane changes. The second low friction scenario an autonomous vehicle may encounter is one in which the road surface friction coefficient is known by the autonomous vehicle through it's own perception or through vehicle to vehicle/infrastructure communication. In this case the vehicle must plan it's path accordingly to ensure the vehicle successfully avoids the obstacle while maintaining control and passenger comfort. This work presents an optimization method which results in a minimum maneuver length across a profile of friction surfaces at a single velocity. This work also investigates the lack of correlation between the autonomous test platform operating on an icy surface and a simulation using a constant coefficient for low friction surfaces. The simulation environment used accurately predicts vehicle dynamic response when simulating operation on dry pavement with a divergence in response on friction values below that of packed snow ($\mu=0.3$). On lower friction surfaces the test vehicle exhibits significant variation in response to steering input. This work presents a stochastic method for representing friction surface in simulation across a grid map to bring simulation vehicle position prediction in line with test vehicle behavior on icy surfaces. This method shows a strong correlation between the simulation and test vehicle during rapid double lane changes and is further validation through the application of previously developed control and path planning methods.
Book Synopsis Path-Planning and Optimization of a High-speed 1/5-Scale Off-Road Autonomous Vehicle by : Andres Esparragoza
Download or read book Path-Planning and Optimization of a High-speed 1/5-Scale Off-Road Autonomous Vehicle written by Andres Esparragoza and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis investigates path-planning for a high-speed off-road autonomous vehicle. A 1/5th scale Remote Control (RC) vehicle was modified with sensors to be able to track vehicle position, trajectory, velocity, and other parameters necessary while performing traversals on a specifically designed off-road course that challenges the vehicles maneuverability and velocity. Advanced global position system (GPS) and encoder algorithms are implemented into the vehicles onboard microcontrollers to determine real time data necessary to dictate the necessary steering and throttle inputs. The sensor algorithms allow for the vehicle to measure its position and velocity, thereby enabling the foundation of path-following. Using algorithms to control the two receiving functions, steering and throttle, the vehicle must traverse the course autonomously with the aim of increasing speed per traversal until reaching an optimal steady-state velocity profile. Using iterative learning control (ILC) and similar control strategies, the vehicle learns from prior traversals to find limiting levels of velocity to be able to repeatedly produce traversals faster with each lap. The foundation for a 1/5th scale high-speed off-road vehicle path following simulation is created on MATLAB prior to vehicle implementation. The simulation successfully models constant speed along a path for both large-scale and 1/5th scale vehicles. The simulation is prepared for the implementation of ILC to determine the optimal steady-state velocity profile. The goal is for the simulation to achieve lap navigation faster than if a human were to control the vehicle via its remote-control unit. This research discussion concludes by outlining the next steps for algorithm development and field testing. The overall goal is to contribute to the development of autonomous off-road vehicles for use in a range of applications, including agriculture, mining, and search and rescue. The findings of this thesis seek to advance core algorithms and deployment technologies for autonomous systems in challenging off-road environments.
Book Synopsis Creating Autonomous Vehicle Systems by : Shaoshan Liu
Download or read book Creating Autonomous Vehicle Systems written by Shaoshan Liu and published by Morgan & Claypool Publishers. This book was released on 2017-10-25 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.
Book Synopsis Autonomous Vehicle Path Planning Using MPC and APF by : Zahra Elmi
Download or read book Autonomous Vehicle Path Planning Using MPC and APF written by Zahra Elmi and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous vehicles have been at the forefront of academic and industrial research in recent decades. This study,Äôs aim is to reduce traffic congestion, improve safety, and accidents. Path planning algorithms are one of the main elements in autonomous vehicles that make critical decisions. Motion planning methods are required when transporting passengers from one point to another. These methods have incorporated several methods such as generating the best trajectory while considering the constraints of vehicle dynamics and obstacles, searching a path to follow, and avoiding obstacles that guarantee comfort, safety, and efficiency. We suggested an effective path planning algorithm based on Model Predictive Controller that determines the maneuvers mode such as lane-keeping and lane-changing automatically. We utilized two different artificial potential field functions for the road boundary, obstacles, and lane center to ensure safety. On the four scenarios, we examined the proposed path planning controller. The obtained results show that when a path planning controller is used, the vehicle avoids colliding with obstacles and follows the rules of the road by adjusting the vehicle,Äôs dynamics. An autonomous vehicle,Äôs safety is ensured by the path planning controller.
Book Synopsis Multiple-path Generation to Improve Autonomous Vehicle Planning by : Vishnu Penubarthi
Download or read book Multiple-path Generation to Improve Autonomous Vehicle Planning written by Vishnu Penubarthi and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path planning is an integral part of ensuring autonomous vehicles become more safe and efficient in order to facilitate greater adoption of the technology and make it a viable option for an increased number of applications. While there are many documented approaches to path planning on roads, the challenge of path planning in an off-road environment is less studied and presents additional challenges including traversing an unknown and unstructured map environment. This can result in scenarios where previously unknown obstacles are discovered along a path a vehicle is traversing, forcing the vehicle to re-route and take a potentially inefficient route to its final destination. We present an extensible framework to mitigate this issue in which we generate multiple paths, select an efficient path for the vehicle with respect to its navigation to the final destination, and incentivize the vehicle to adhere to the selected path. We also implement this framework within the Nebula team's ROS-based autonomous vehicle software stack for DARPA's Racer challenge and compare its performance to the current implementation. Through testing performed in simulation on topologies of interest to the Nebula group, we find that the proposed framework results in a 37% increase in average speed and a 24% decrease in time to reach the final destination compared to the current implementation.
Book Synopsis Path Planning and Robust Control of Autonomous Vehicles by : Sheng Zhu (Mechanical engineer)
Download or read book Path Planning and Robust Control of Autonomous Vehicles written by Sheng Zhu (Mechanical engineer) and published by . This book was released on 2020 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous driving is gaining popularity in research interest and industry investment over the last decade, due to its potential to increase driving safety to avoid driver errors which account for over 90% of all motor vehicle crashes. It could also help to improve public mobility especially for the disabled, and to boost the productivity due to enlarged traffic capacity and accelerated traffic flows. The path planning and following control, as the two essential modules for autonomous driving, still face critical challenges in implementations in a dynamically changing driving environment. For the local path/trajectory planning, multifold requirements need to be satisfied including reactivity to avoid collision with other objects, smooth curvature variation for passenger comfort, feasibility in terms of vehicle control, and the computation efficiency for real-time implementations. The feedback control is required afterward to accurately follow the planned path or trajectory by deciding appropriate actuator inputs, and favors smooth control variations to avoid sudden jerks. The control may also subject to instability or performance deterioration due to continuously changing operating conditions along with the model uncertainties. The dissertation contributes by raising the framework of path planning and control to address these challenges. Local on-road path planning methods from two-dimensional (2D) geometric path to the model-based state trajectory is explored. The latter one is emphasized due to its advantages in considering the vehicle model, state and control constraints to ensure dynamic feasibility. The real-time simulation is made possible with the adoption of control parameterization and lookup tables to reduce computation cost, with scenarios showing its smooth planning and the reactivity in collision avoidance with other traffic agents. The dissertation also explores both robust gain-scheduling law and model predictive control (MPC) for path following. The parameter-space approach is introduced in the former with validated robust performance under the uncertainty of vehicle load, speed and tire saturation parameter through hardware-in-the-loop and vehicle experiments. The focus is also put on improving the safety of the intended functionality (SOTIF) to account for the potential risks caused by lack of situational awareness in the absence of a system failure. Such safety hazards include the functional inability to comprehend the situation and the insufficient robustness to diverse conditions. The dissertation enhanced the SOTIF with parameter estimation through sensor fusion to increase the vehicle situational awareness of its internal and external conditions, such as the road friction coefficient. The estimated road friction coefficient helps in planning a dynamically feasible trajectory under adverse road condition. The integration of vehicle stability control with autonomous driving functions is also explored in the case that the road friction coefficient estimation is not responsive due to insufficiency in time and excitations.
Book Synopsis Robust Motion Planning for Autonomous Tracked Vehicles in Deformable Terrain by : Sang Uk Lee (S.M.)
Download or read book Robust Motion Planning for Autonomous Tracked Vehicles in Deformable Terrain written by Sang Uk Lee (S.M.) and published by . This book was released on 2016 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ensuring the safety of autonomous vehicles during operation is a challenging task. Numerous factors such as process noise, sensor noise, incorrect model etc. can yield uncertainty in robot's state. Especially for tracked vehicles operating on rough terrain, vehicle slip due to vehicle terrain interaction affects the vehicle system significantly. In such cases, the motion planning of the autonomous vehicle must be performed robustly, considering the uncertain factors in advance of the real-time navigation. The primary contribution of this thesis is to present a robust optimal global planner for autonomous tracked vehicles operating in off-road terrain with uncertain slip. In order to achieve this goal, three tasks must be completed. First, the motion planner must be able to work efficiently under the non-holonomic vehicle system model. An approximate method is applied to the tracked vehicle system ensuring both optimality and efficiency. Second, the motion planner should ensure robustness. For this, a robust incremental sampling based motion planning algorithm (CC-RRT*) is combined with the LQG-MP algorithm. CC-RRT* yields the optimal and probabilistically feasible trajectory by using a chance constrained approach under the RRT* framework. LQG-MP provides the capability of considering the role of compensator in the motion planning phase and bounds the degree of uncertainty to appropriate size. Third, the effect of slip on the vehicle system must be modeled properly. This can be done in advance of operation if we have experimental data and full information about the environment. However, in case where such knowledge is not available, the online slip estimation can be performed using system identification method such as the IPEM algorithm. Simulation results shows that the resulting algorithms are efficient, optimal, and robust. The simulation was performed on a realistic scenario with several important factors that can increase the uncertainty of the vehicle. Experimental results are also provided to support the validity of the proposed algorithm. The proposed framework can be applied to other robotic systems where robustness is an important issue.
Book Synopsis On Semantic Segmentation and Path Planning for Autonomous Vehicles Within Off-road Environments by : Christopher John Holder
Download or read book On Semantic Segmentation and Path Planning for Autonomous Vehicles Within Off-road Environments written by Christopher John Holder and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Path Planning for Vehicles Operating in Uncertain 2D Environments by : Viacheslav Pshikhopov
Download or read book Path Planning for Vehicles Operating in Uncertain 2D Environments written by Viacheslav Pshikhopov and published by Butterworth-Heinemann. This book was released on 2017-01-28 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Path Planning for Vehicles Operating in Uncertain 2D-environments presents a survey that includes several path planning methods developed using fuzzy logic, grapho-analytical search, neural networks, and neural-like structures, procedures of genetic search, and unstable motion modes. Presents a survey of accounting limitations imposed by vehicle dynamics Proposes modified and new original methods, including neural networking, grapho-analytical, and nature-inspired Gives tools for a novice researcher to select a method that would suit their needs or help to synthesize new hybrid methods
Book Synopsis Development, Analysis and Implementation of a Spline Based, Obstacle Avoiding, Path Planning Algorithm for Autonomous Ground Vehicles by : John Connors
Download or read book Development, Analysis and Implementation of a Spline Based, Obstacle Avoiding, Path Planning Algorithm for Autonomous Ground Vehicles written by John Connors and published by . This book was released on 2007 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:
