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Articles 1 - 20 of 20
Full-Text Articles in Mechanical Engineering
Path Planning Development Framework For Mobile Robots, Lauren-Ann Elizabeth Graham
Path Planning Development Framework For Mobile Robots, Lauren-Ann Elizabeth Graham
Theses and Dissertations
Planetary exploration relies on methods of path planning to achieve autonomous navigation in hazardous environments. Simulating harsh terrain, real-time varying physics, and robotics applications is vital for testing control algorithms here on Earth. Robotics Operating System (ROS) is a set of software libraries and tools that allow you to build and simulate robotic applications. Utilizing ROS, Gazebo, and Blender, a rough terrain simulation framework is created to explore and compare path planning algorithms using various desired robots and maps. ROS supports multiple path planning algorithms given its open-source abilities. This research focuses on path planning implementation of Proportional-Integral-Derivative (PID) control …
Efficient Navigation And Motion Control For Autonomous Forklifts In Smart Warehouses: Lspb Trajectory Planning And Mpc Implementation, Konchanok Vorasawad, Myoungkuk Park, Changwon Kim
Efficient Navigation And Motion Control For Autonomous Forklifts In Smart Warehouses: Lspb Trajectory Planning And Mpc Implementation, Konchanok Vorasawad, Myoungkuk Park, Changwon Kim
Michigan Tech Publications, Part 2
The rise of smart factories and warehouses has ushered in an era of intelligent manufacturing, with autonomous robots playing a pivotal role. This study focuses on improving the navigation and control of autonomous forklifts in warehouse environments. It introduces an innovative approach that combines a modified Linear Segment with Parabolic Blends (LSPB) trajectory planning with Model Predictive Control (MPC) to ensure efficient and secure robot movement. To validate the performance of our proposed path-planning method, MATLAB-based simulations were conducted in various scenarios, including rectangular and warehouse-like environments, to demonstrate the feasibility and effectiveness of the proposed method. The results demonstrated …
Optimal Path Planning For Aerial Robots Using Genetic Algorithm, Anna Puigvert I Juan
Optimal Path Planning For Aerial Robots Using Genetic Algorithm, Anna Puigvert I Juan
Graduate Theses, Dissertations, and Problem Reports
This thesis presents a path optimization solution for a robot in two different constrained 3-dimensional (3D) environments. The robot is required to travel from its current position to a goal position following minimum cost paths (optimal paths). The first environment has 3D obstacles that interfere with the robot’s path. The path cost for this environment accounts for the minimum distance traveled by the robot from the start to the goal position while avoiding obstacles. The second environment is the atmosphere of Venus, specifically a flyable region of this atmosphere with characteristics similar to Earth’s. This environment has strong westward winds …
Reactive Motion Planning Of Autonomous Vehicles In 3-Dimensional Environments Using Collision And Rendezvous Cones, Kashish Dhal
Reactive Motion Planning Of Autonomous Vehicles In 3-Dimensional Environments Using Collision And Rendezvous Cones, Kashish Dhal
Mechanical and Aerospace Engineering Dissertations
This dissertation presents a collision cone/rendezvous cone-based approach for reactive motion planning in three-dimensional dynamic environments. Collision avoidance is fundamental to robot motion planning. In dynamic environments, the path and velocities of obstacles are not known a-priori, and hence it is a common practice to use reactive planners. Reactive planners should be computationally inexpensive because they need to act fast to avoid potential collisions. To reduce the computational load, a majority of motion planning algorithms model the shapes of the robots and obstacles as a circle/sphere. However, when the objects are elongated more in one direction than another, the spherical …
An Algorithm For Task Allocation And Planning For A Heterogeneous Multi-Robot System To Minimize The Last Task Completion Time, Abhishek Patil, Jungyun Bae, Myoungkuk Park
An Algorithm For Task Allocation And Planning For A Heterogeneous Multi-Robot System To Minimize The Last Task Completion Time, Abhishek Patil, Jungyun Bae, Myoungkuk Park
Michigan Tech Publications
This paper proposes an algorithm that provides operational strategies for multiple heterogeneous mobile robot systems utilized in many real-world applications, such as deliveries, surveillance, search and rescue, monitoring, and transportation. Specifically, the authors focus on developing an algorithm that solves a min-max multiple depot heterogeneous asymmetric traveling salesperson problem (MDHATSP). The algorithm is designed based on a primal-dual technique to operate given multiple heterogeneous robots located at distinctive depots by finding a tour for each robot such that all the given targets are visited by at least one robot while minimizing the last task completion time. Building on existing work, …
Sea Ice Warning Visualization And Path Planning For Ice Navigation Based On Radar Image Recognition, Tsung-Hsuan Hsieh, Shengzheng Wang, Huijia Gong, Wei Liu, Ning Xu
Sea Ice Warning Visualization And Path Planning For Ice Navigation Based On Radar Image Recognition, Tsung-Hsuan Hsieh, Shengzheng Wang, Huijia Gong, Wei Liu, Ning Xu
Journal of Marine Science and Technology
Ice navigation is currently one of the important issues in path planning studies. Most studies are using sea ice models or ice charts for large-scale path planning, but the weather and ice conditions in the polar waters usually change quickly and are not easy to predict. Under these conditions, small-scale path planning that can be adjusted in time for sea ice collision avoidance is needed. This study uses marine radar imaging to reconstruct the ice navigation scene, and establishes a visual-ization function of sea ice warning on the radar image. We combine the bidirectional rapidly-exploring random tree (B-RRT) algorithm and …
A Framework For Optimal Path Planning And Nonlinear Guidance For Autonomous Mobile Robots, Paul A. Quillen
A Framework For Optimal Path Planning And Nonlinear Guidance For Autonomous Mobile Robots, Paul A. Quillen
Mechanical and Aerospace Engineering Dissertations
The purpose of this research is to investigate methods and technology for enhancing autonomous capabilities for mobile robots. The measures of autonomy which are specifically covered in this dissertation pertain to a mobile robot’s ability to make decisions and act, in other words guidance and control. This dissertation puts forth a framework using optimal path planning and nonlinear guidance techniques to address these matters. The path plans are synthesized using a numerical navigation function algorithm that will form its potential contour levels based on the “minimum control effort” of the system. Additionally, extensions of the path planning algorithm in the …
Integration Of A Complete Detect And Avoid System For Small Unmanned Aircraft Systems, Jared Kevin Wikle
Integration Of A Complete Detect And Avoid System For Small Unmanned Aircraft Systems, Jared Kevin Wikle
Theses and Dissertations
For unmanned aircraft systems to gain full access to the National Airspace System (NAS), they must have the capability to detect and avoid other aircraft. This research focuses on the development of a detect-and-avoid (DAA) system for small unmanned aircraft systems. To safely avoid another aircraft, an unmanned aircraft must detect the intruder aircraft with ample time and distance. Two analytical methods for finding the minimum detection range needed are described. The first method, time-based geometric velocity vectors (TGVV), includes the bank-angle dynamics of the ownship while the second, geometric velocity vectors (GVV), assumes an instantaneous bank-angle maneuver. The solution …
Cushioned Extended-Periphery Avoidance: A Reactive Obstacle Avoidance Plugin, Timothy Mclain, James Jackson, David Wheeler
Cushioned Extended-Periphery Avoidance: A Reactive Obstacle Avoidance Plugin, Timothy Mclain, James Jackson, David Wheeler
Faculty Publications
While collision avoidance and flight stability are generally a micro air vehicle’s (MAVs) highest priority, many map-based path planning algorithms focus on path optimality, often assuming a static, known environment. For many MAV applications a robust navigation solution requires responding quickly to obstacles in dynamic, tight environments with non- negligible disturbances. This article first outlines the Reactive Obstacle Avoidance Plugin framework as a method for leveraging map-based algorithms while providing low-latency, high-bandwidth response to obstacles. Further, we propose and demonstrate the effectiveness of the Cushioned Extended- Periphery Avoidance (CEPA) algorithm. By representing recent laser scans in the current body-fixed polar …
Implementing Dubins Airplane Paths On Fixed-Wing Uavs, Timothy Mclain, Randall W. Beard, Mark Owen
Implementing Dubins Airplane Paths On Fixed-Wing Uavs, Timothy Mclain, Randall W. Beard, Mark Owen
Faculty Publications
A well-known path-planning technique for mobile robots or planar aerial vehicles is to use Dubins paths, which are minimum-distance paths between two configurations subject to the constraints of the Dubins car model. An extension of this method to a three-dimensional Dubins airplane model has recently been proposed. This chapter builds on that work showing a complete architecture for implementing Dubins airplane paths on small fixed-wing UAVs. The existing Dubins airplane model is modified to be more consistent with the kinematics of a fixed-wing aircraft. The chapter then shows how a recently proposed vector-field method can be used to design a …
Scalable Autonomous Operations Of Unmanned Assets, Sunghun Jung
Scalable Autonomous Operations Of Unmanned Assets, Sunghun Jung
Open Access Dissertations
Although there have been great theoretical advances in the region of Unmanned Aerial Vehicle (UAV) autonomy, applications of those theories into real world are still hesitated due to unexpected disturbances. Most of UAVs which are currently used are mainly, strictly speaking, Remotely Piloted Vehicles (RPA) since most works related with the flight control, sensor data analysis, and decision makings are done by human operators. To increase the degree of autonomy, many researches are focused on developing Unmanned Autonomous Aerial Vehicle (UAAV) which can takeoff, fly to the interested area by avoiding unexpected obstacles, perform various missions with decision makings, come …
Development Of A Sense And Avoid System For Small Unmanned Aircraft Systems, Robert Andrew Klaus
Development Of A Sense And Avoid System For Small Unmanned Aircraft Systems, Robert Andrew Klaus
Theses and Dissertations
Unmanned aircraft systems (UAS) represent the future of modern aviation. Over the past 10 years their use abroad by the military has become commonplace for surveillance and combat. Unfortunately, their use at home has been far more restrictive. Due to safety and regulatory concerns, UAS are prohibited from flying in the National Airspace System without special authorization from the FAA. One main reason for this is the lack of an on-board pilot to "see and avoid" other air traffic and thereby maintain the safety of the skies. Development of a comparable capability, known as "Sense and Avoid" (SAA), has therefore …
Multi-Resolution Obstacle Mapping With Rapidly-Exploring Random Tree Path Planning For Unmanned Air Vehicles, Brett Wayne Millar
Multi-Resolution Obstacle Mapping With Rapidly-Exploring Random Tree Path Planning For Unmanned Air Vehicles, Brett Wayne Millar
Theses and Dissertations
Unmanned air vehicles (UAVs) have become an important area of research. UAVs are used in many environments which may have previously unknown obstacles or sources of danger. This research addresses the problem of obstacle mapping and path planning while the UAV is in flight. Online obstacle mapping is achieved through the use of a multi-resolution map. As sensor information is received, a quadtree is built up to hold the information based upon the uncertainty associated with the measurement. Once a quadtree map of obstacles is built up, we desire online path re-planning to occur as quickly as possible. We introduce …
Search Pattern Generation And Path Management For Search Over Rough Terrain With A Small Uav, Jacob L. Bishop
Search Pattern Generation And Path Management For Search Over Rough Terrain With A Small Uav, Jacob L. Bishop
Theses and Dissertations
Search operations can be described by the interaction between three entities: the target, the sensor, and the environment. Past treatments of the search problem have focused primarily on the interaction between the sensor and the target. The effects that the environment has on the target and sensor have been greatly simplified or ignored completely. The wilderness search and rescue scenario is one case in which these interactions cannot be safely ignored. Using the wilderness search and rescue problem as our motivating example, we develop an algorithm for planning search paths for a small unmanned aerial vehicle (UAV) over rough terrain …
Consistency Based Error Evaluation For Deep Sea Bathymetric Mapping With Robotic Vehicles, Christopher Roman, Hanumant Singh
Consistency Based Error Evaluation For Deep Sea Bathymetric Mapping With Robotic Vehicles, Christopher Roman, Hanumant Singh
Christopher N. Roman
This paper presents a method to evaluate the mapping error present in point cloud terrain maps created using robotic vehicles and range sensors. This work focuses on mapping environments where no a priori ground truth is available and self consistency is the only available check against false artifacts and errors. The proposed error measure is based on a disparity measurement between common sections of the environment that have been imaged multiple times. This disparity measure highlights inconsistency in the terrain map by showing regions where multiple overlapping point clouds do not fit together well. This error measure provides the map …
Learning Real-Time A* Path Planner For Unmanned Air Vehicle Target Sensing, Jason K. Howlett, Timothy W. Mclain, Michael A. Goodrich
Learning Real-Time A* Path Planner For Unmanned Air Vehicle Target Sensing, Jason K. Howlett, Timothy W. Mclain, Michael A. Goodrich
Faculty Publications
This paper presents a path planner for sensing closely-spaced targets from a fixed-wing unmanned air vehicle (UAV) having a specified sensor footprint. The planner is based on the learning real-time A* (LRTA*) search algorithm and produces dynamically feasible paths that accomplish the sensing objectives in the shortest possible distance. A tree of candidate paths that span the area of interest is created by assembling primitive turn and straight sections of a specified step size in a sequential fashion from the starting position of the UAV. An LRTA* search of the tree produces feasible paths any time during its execution and …
Coordinated Uav Target Assignment Using Distributed Calculation Of Target-Task Tours, David H. Walker
Coordinated Uav Target Assignment Using Distributed Calculation Of Target-Task Tours, David H. Walker
Theses and Dissertations
This thesis addresses the improvement of cooperative task allocation to vehicles in multiple-vehicle, multiple-target scenarios through the use of more effective preplanned tours. Effective allocation of vehicles to targets requires knowledge of both the team objectives and the contributions that individual vehicles can make toward accomplishing team goals. This is primarily an issue of individual vehicle path planning --- determining the path the vehicles will follow to accomplish individual and team goals. Conventional methods plan optimal point-to-point path segments that often result in lengthy and suboptimal tours because the trajectory neither considers future tasks nor the overall path. However, cooperation …
Autonomous Vehicle Technologies For Small Fixed Wing Uavs, Derek B. Kingston, Randal Beard, Timothy Mclain, Michael Larsen, Wei Ren
Autonomous Vehicle Technologies For Small Fixed Wing Uavs, Derek B. Kingston, Randal Beard, Timothy Mclain, Michael Larsen, Wei Ren
Faculty Publications
Autonomous unmanned air vehicle flight control systems require robust path generation to account for terrain obstructions, weather, and moving threats such as radar, jammers, and unfriendly aircraft. In this paper, we outline a feasible, hierarchal approach for real-time motion planning of small autonomous fixed-wing UAVs. The approach divides the trajectory generation into four tasks: waypoint path planning, dynamic trajectory smoothing, trajectory tracking, and low-level autopilot compensation. The waypoint path planner determines the vehicle's route without regard for the dynamic constraints of the vehicle. This results in a significant reduction in the path search space, enabling the generation of complicated paths …
Learning Real-Time A* Path Planner For Sensing Closely-Spaced Targets From An Aircraft, Jason K. Howlett, Michael A. Goodrich, Timothy W. Mclain
Learning Real-Time A* Path Planner For Sensing Closely-Spaced Targets From An Aircraft, Jason K. Howlett, Michael A. Goodrich, Timothy W. Mclain
Faculty Publications
This work develops an any-time path planner, based on the learning real-time A* (LRTA*) search, for generating flyable paths that allow an aircraft with a specified sensor footprint to sense a group of closely-spaced targets. The LRTA* algorithm searches a tree of flyable paths for the branch that accomplishes the desired objectives in the shortest distance. The tree of paths is created by assembling primitive turn and straight sections of a specified step size. The operating parameters for the LRTA* search directly influence the running time and path-length performance of the search. A modified LRTA* search is presented that terminates …
Spline Based Path Planning For Unmanned Air Vehicles, Kevin B. Judd, Timothy W. Mclain
Spline Based Path Planning For Unmanned Air Vehicles, Kevin B. Judd, Timothy W. Mclain
Faculty Publications
A trajectory planning scheme that generates feasible flight routes for an unmanned air vehicle (UAV) is developed. A preliminary path is generated from a Voronoi diagram based on threat locations. This path consists of a series of straight-line segments that cannot be followed exactly by the UAV. Using a series of cubic splines to connect these straight-line segments, this path is refined into an optimum path that is flyable by the UAV. Utilizing a decomposition strategy, both the full path (coarse detail) to the target and the proximate optimum path (fine detail) near the UAV can be quickly computed. The …