Browse Topic: Navigation and guidance systems
ABSTRACT Global Positioning System (GPS) technology has become absolutely indispensable to today’s warfighter. GPS signals provide Positioning, Navigation, and Timing (PNT) data that are needed by virtually every critical military system. Digital radio networks require precise time to operate. Direct and indirect fires systems need precise coordinates to accurately determine firing data. Individual soldiers and vehicles need positioning and navigation data to coordinate offensive and defensive maneuver. Battle management systems require the location of every friendly unit in order to provide commanders with an understanding of the battlefield. The list goes on and on. In short, PNT has become a critical element in the ability to shoot, move, and communicate. The dependency on PNT is well understood. The Secretary of the Army recently testified to Congress, “Having accurate PNT information is fundamental to our forces’ ability to maintain initiative, coordinate movements, target fires
ABSTRACT As part of an Internal Research and Design effort to take existing disparate technologies and integrate them into a single autonomous vehicle to advance the state-of-the-art in unmanned ground vehicle autonomy, SwRI has developed a data representation and routing algorithm to deal with the complexities of interconnecting urban roadways and the static and dynamic hazards in such an environment. The program was designed to utilize data from a Route Network Definition File (RNDF), which contains a priori roadway network data. Using its known location and a given destination, the vehicle determines the shortest route to completion. If, during traversal of that route, the vehicle detects an obstacle in its path using its on-board sensors, it will dynamically re-route its path whether that requires changing lanes on a multiple lane road or turning around completely and finding a different route if the path is completely blocked
ABSTRACT Robot path-planning is a central task for navigation and most path-planners perform well in mapped environments with explicit obstacle boundaries. However, many obstacle fields are better defined by the probability of obstacles and obstacle geometries rather than by explicit locations. Few tools and data structures exist, other than repeated simulations, to predict robot mobility in these situations. Previously, it was shown that geometric obstacle properties could be used to estimate properties of paths routing around these obstacles, looking only at maps and avoiding the task of path planning [1]. This required knowing obstacle geometries relative to travel direction. This work presents a method for representing obstacle geometry, at arbitrary orientations and positions, and therefore a probabilistic model for determining if space near an obstacle is occupied. This paper explains the theory behind this method, uses this method to calculate the portion of a straight path
ABSTRACT This paper presents a new terrain traversability mapping method integrated into the Robotic Technology Kernel (RTK) that produces ground slope traversability cost information from LiDAR height maps. These ground slope maps are robust to a variety of off-road scenarios including areas of sparse or dense vegetation. A few simple and computationally efficient heuristics are applied to the ground slope maps to produce cost data that can be directly consumed by existing path planners in RTK, improving the navigation performance in the presence of steep terrain. Citation: J. Ramsey, R. Brothers, J. Hernandez, “Creation of a Ground Slope Mapping Methodology Within the Robotic Technology Kernel for Improved Navigation Performance,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022
ABSTRACT Leader-follower autonomous vehicle systems have a vast range of applications which can increase efficiency, reliability, and safety by only requiring one manned-vehicle to lead a fleet of unmanned followers. The proper estimation and duplication of a manned-vehicle’s path is a critical component of the ongoing development of convoying systems. Auburn University’s GAVLAB has developed a UWB-ranging based leader-follower GNC system which does not require an external GPS reference or communication between the vehicles in the convoy. Experimental results have shown path-duplication accuracy between 1-5 meters for following distances of 10 to 50 meters. Citation: K. Thompson, B. Jones, S. Martin, and D. Bevly, “GPS-Independent Autonomous Vehicle Convoying with UWB Ranging and Vehicle Models,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022
ABSTRACT The Vehicular Integration for Command, Control, Communication, Computers, Intelligence, Surveillance and Reconnaissance / Electronic Warfare (C4ISR/EW) Interoperability (VICTORY) standards is an open architecture that defines how software and hardware are shared as common resources among services that make up a platform’s capabilities such as Ethernet switches and routers, end nodes, processing units, as well as functionality such as position and navigation systems, radios, health monitoring, and automotive. The VICTORY standard enables reducing the total Size, Weight, and Power (SWaP), and Costs (SWaP-C) on a platform. As part of the Information Assurance (IA) capabilities of the VICTORY standard, the VICTORY Access Control Framework (VACF) provides protection to these shared resources in the form of an Attribute-Based Access Control (ABAC) system. The VACF is composed of five VICTORY component types: Authentication, Attribute Store, Policy Store, Policy Decision, and Policy
ABSTRACT Semi-autonomous behaviors, such as leader-following and “point-and-go” navigation, have the potential to significantly increase the value of squad-level UGVs by freeing operators to perform other tasks. A variety of technologies have been designed in recent years to enable such semi-autonomous behaviors on board mobile robots; however, most current solutions use custom payloads comprising sensors such as stereo cameras, LIDAR, GPS, or active transmitters. While effective, these approaches tend to be restricted to UGV platforms capable of supporting the payload’s space, weight, and power (SWaP), and may be cost-prohibitive to large-scale deployment. Charles River has developed a system that enables both leader-following and “point-and-go” navigation behaviors using only a single monocular camera. The system allows a user to control a mobile robot by leading the way and issuing commands through arm/hand gestures, and is capable of following an operator both on foot and aboard a
ABSTRACT Autonomous robots can maneuver into dangerous situations without endangering Soldiers. The Soldier tasked with the supervision of a route clearing robot vehicle must be located beyond the physical effect of an exploding IED but close enough to understand the environment in which the robot is operating. Additionally, mission duration requirements discourage the use of low level, fatigue inducing, teleoperation. Techniques are needed to reduce the Soldier’s mental stress in this demanding situation, as well as to blend the high level reasoning of a remote human supervisor with the local autonomous capability of a robot to provide effective, long term mission performance. GDRS has developed an advanced supervised autonomy version of its Robotics Kit (GDRK) under the Robotic Mounted Detection System (RMDS) program that provides a cost effective, high-utility automation solution that overcomes the limitations and burden of a purely teleoperated system. GDRK is a modular robotic
ABSTRACT Automatic guided vehicles (AGV) have made big inroads in the automation of assembly plants and warehouse operations. There are thousands of AGV units in operation at OEM supplier and service facilities worldwide in virtually every major manufacturing and distribution sector. Although today’s AGV systems can be reconfigured and adapted to meet changes in operation and need, their adaptability is often limited because of inadequacies in current systems. This paper describes a wireless navigated (WN) omni-directional (OD) autonomous guided vehicle (AGV) that incorporates three technical innovations that address the shortfalls. The AGV features consist of: 1) A newly developed integrated wireless navigation technology to allow rapid rerouting of navigation pathways; 2) Omnidirectional wheels to move independently in different directions; 3) Modular space frame construction to conveniently resize and reshape the AGV platform. It includes an overview of the AGVs technical features
ABSTRACT This research proposes a human-multirobot system with semi-autonomous ground robots and UAV view for contaminant localization tasks. A novel Augmented Reality based operator interface has been developed. The interface uses an over-watch camera view of the robotic environment and allows the operator to direct each robot individually or in groups. It uses an A* path planning algorithm to ensure obstacles are avoided and frees the operator for higher-level tasks. It also displays sensor information from each individual robot directly on the robot in the video view. In addition, a combined sensor view can also be displayed which helps the user pin point source information. The sensors on each robot monitor the contaminant levels and a virtual display of the levels is given to the user and allows him to direct the multiple ground robots towards the hidden target. This paper reviews the user interface and describes several initial usability tests that were performed. This research
ABSTRACT Geotechnical site characterization is the process of collecting geophysical and geospatial characteristics about the surface and subsurface to create a 3-dimensional (3D) model. Current Robot Operating System (ROS) world models are designed primarily for navigation in unknown environments; however, they do not store the geotechnical characteristics requisite for environmental assessment, archaeology, construction engineering, or disaster response. The automotive industry is researching High Definition (HD) Maps, which contain more information and are currently being used by autonomous vehicles for ground truth localization, but they are static and primarily used for navigation in highly regulated infrastructure. Modern site characterization and HD mapping methods involve survey engineers working on-site followed by lengthy post processing. This research addresses the shortcomings for current world models and site characterization by introducing Site Model Geospatial System
ABSTRACT Geotechnical site characterization is the process of collecting geophysical and geospatial characteristics about the surface and subsurface to create a 3-dimensional (3D) model. Current Robot Operating System (ROS) world models are designed primarily for navigation in unknown environments; however, they do not store the geotechnical characteristics requisite for environmental assessment, archaeology, construction engineering, or disaster response. The automotive industry is researching High Definition (HD) Maps, which contain more information and are currently being used by autonomous vehicles for ground truth localization, but they are static and primarily used for navigation in highly regulated infrastructure. Modern site characterization and HD mapping methods involve survey engineers working on-site followed by lengthy post processing. This research addresses the shortcomings for current world models and site characterization by introducing Site Model Geospatial System
ABSTRACT U.S. Army Combat Capabilities Development Command (CCDC) Ground Vehicle Systems Center (GVSC) has been managing and developing a variety of autonomous systems throughout its existence. Two of the most important from the past decade include the Autonomous Mobility Appliqué System (AMAS) developed by Lockheed Martin Corporation (LMC) and the Robotic Technology Kernel (RTK) developed by GVSC in collaboration with DCS Corp and Southwest Research Institute (SwRI). Rather than continuing to develop and maintain two separate autonomous software systems, GVSC has decided to integrate any capabilities that were unique to AMAS into RTK and devote efforts to developing RTK going forward. The goal of integrating AMAS into RTK is to leverage the best features of each system. The process of this integration involves multiple steps. This paper describes the historical and current efforts involved in the integration of AMAS into RTK. Citation: D. Pirozzo, J.P. Hecker, A. Dickinson, T
ABSTRACT Off-road autonomous navigation poses a challenging problem, as the surrounding terrain is usually unknown, the support surface the vehicle must traverse cannot be considered flat, and environmental features (such as vegetation and water) make it difficult to estimate the support surface elevation. This paper will focus on Robotic Research’s suite of off-road autonomous planning and obstacle avoidance tools. Specifically, this paper will provide an overview of our terrain detection system, which utilizes advanced LADAR processing techniques to provide an estimate of the surface. Additionally, it will describe the kino-dynamic off-road planner which can, in real-time, calculate the optimal route, taking into account the support surface, obstacles sensed in the environment, and more. Finally, the paper will explore how these technologies have been applied to a wide variety of different robotic applications
ABSTRACT The Advanced Systems Engineering Capability (ASEC) developed by TARDEC Systems Engineering & Integration (SE&I) group is an integrated Systems Engineering (SE) knowledge creation and capture framework built on a decision centric method, high quality data visualizations, intuitive navigation and systems information management that enable continuous data traceability, real time collaboration and knowledge pattern leverage to support the entire system lifecycle. The ASEC framework has evolved significantly over the past year. New tools have been added for capturing lessons learned from warfighter experiences in theater and for analyzing and validating the needs of ground domains platforms/systems. These stakeholder needs analysis tools may be used to refine the ground domain capability model (functional decomposition) and to help identify opportunities for common solutions across platforms. On-going development of ASEC will migrate all tools to a single virtual desktop to promote
ABSTRACT The VICTORY initiative has been broadly adopted across the US Defense ground vehicle community. Last year, PEO GCS generated Acquisition Decision Memorandums (ADM) guiding the Platform community to incorporate VICTORY architecture in many vehicle modernization efforts, as well as new start vehicle programs. The community can generally agree that VICTORY is driving the vehicle architecture in a positive direction, providing a much more efficient architecture to enable current, and future, technology integration. A major component of the VICTORY standards addresses the distribution of GPS-supplied information for position, heading, elevation, and timing. The vast majority of major subsystems on today’s military ground vehicles utilize GPS data in some form. These systems include fire control computers, navigation and blue force tracking equipment, ISR assets, electronic warfare devices, personal navigation equipment, laser range finders, command & control (C2) computers, UAV’s
ABSTRACT This work presents the development of a high fidelity Simulation In the Loop/Hardware In the Loop simulation environment using add-ons to Autonomous Navigation Virtual Environment Laboratory (ANVEL) and a navigation unit developed by Auburn University’s GPS and Vehicle Dynamics Lab (GAVLAB) in support of the United States Army’s Autonomous Ground Resupply Science Technology Objective. The developed add-ons include a real time interface for ANVEL, Inertial Measurement Unit module, Wheel Speed Sensor module, and a GPS module that allows simulated signals or generated Radio Frequency signals. The developed add-ons allow for faster development of navigation algorithms and controllers due to a readily available, highly accurate truth from ANVEL and can be configured to introduce realistic errors from sensors, hardware, and GPS signals such that algorithm and controller robustness can be easily examined
ABSTRACT This paper presents a new concept in GNSS navigation: Sequential Lock GPS (GPS-SL). The new concept and prototype provide a variety of advantages for robustness, solution maintenance, and jamming resistance. Under normal circumstances, GNSS receivers need to receive signals from four satellites simultaneously to get a fix on position and the receiver time bias. If three or less satellites are visible given the occlusions provided by the environment, or because someone/something is intentionally or unintentionally jamming the space, no benefit is provided to the navigation solution. In other words, four or more simultaneous satellites give you a fix, three or less simultaneous satellites usually do not contribute (with some caveats) at all
ABSTRACT Cold regions are becoming increasingly more important for off-road vehicle mobility, including autonomous navigation. Most of the time, these regions are covered by snow, and vehicles are forced to operate under active snowfall conditions. In such scenarios, realistic and effective models to predict performance of on-board sensors during snowfalls become of paramount importance. This paper describes a stochastic approach for two-dimensional numerical simulation of dynamic snow scenes that eventually will be used for driving condition visualization and vehicle sensor performance predictions. The model captures realistic snow particle size distribution, terminal near-surface particle speeds, and adequately describes interactions with wind. Citation: S. N. Vecherin, M. E. Tedesche, M. W. Parker, “Dynamic Snowfall Scene Simulations for Autonomous Vehicle Sensor Performance”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI
ABSTRACT Global Positioning System (GPS) technology has seen increased use in many different military applications worldwide, beyond navigation. The Warfighter uses GPS to enhance Situational Awareness on the battle field with systems such as Land Warrior, Blue Force Tracker, TIGR, and various electronic mission planning tools in locations where the GPS signals are normally not available. For example, this includes the inside of a HMMWV, Stryker, or MRAP. GPS retransmission, or the art of repeating a live GPS signal, has evolved into a technically advanced solution to provide GPS signals to the Warfighter mounted inside ground vehicles, protecting themselves from sniper and IED threats, while providing mobility and Situational Awareness from vehicle mounted communication & navigation systems. The objective of this technical paper is to communicate a relevant understanding of how this technology is being embraced by the Warfighter to accomplish their mission safer and more efficiently
ABSTRACT New generations of ground vehicles are required to perform tasks with an increased level of autonomy. Autonomous navigation and Artificial Intelligence on the edge are growing fields that require more sensors and more computational power to perform these missions. Furthermore, new sensors in the market produce better quality data at higher rates while new processors can increase substantially the computational power. Therefore, near-future ground vehicles will be equipped with large number of sensors that will produce data at rates that has not been seen before, while at the same time, data processing power will be significantly increased. This new scenario of advanced ground vehicles applications and increase in data amount and processing power, has brought new challenges with it: low determinism, excessive power needs, data losses and large response latency. In this article, a novel approach to on-board artificial intelligence (AI) is presented that is based on state-of-the
ABSTRACT Autonomous vehicles rely on path planning to guide them towards their destination. These paths are susceptible to interruption by impassable hazards detected at the local scale via on-board sensors, and malicious disruption. We define robustness as an additional parameter which can be incorporated into multi-objective optimization functions for path planning. The robustness at any point is the output of a function of the isochrone map at that point for a set travel time. The function calculates the sum of the difference in area between the isochrone map and the isochrone map with an impassable semi-circle hazard inserted in each of the four cardinal directions. We calculate and compare two different Pareto paths which use robustness as an input parameter with different weights. Citation: T. Jonsson Damgaard, M. Rittri, P. Franz, A. Halota “Robust Path Planning in the Battlefield,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA
ABSTRACT We present the results of an exploratory investigation of applying a hybrid quantum-classical architecture to an off-road vehicle mobility problem, namely the generation of go/no-go maps posed as a machine learning problem. The premise of this work rests on two observations. First, quantum computing allows in principle for algorithms that provide a speedup over the best known classical counterparts. However, as it is to be expected of such novel and complex tools (both hardware and algorithmic) at this early developmental stage, current quantum algorithms do not always perform well on real-world problems. Second, complex physics-based vehicle and terramechanics models and simulations, currently advocated for high-fidelity high-accuracy ground vehicle–terrain interaction analyses, pose significant computational burden, especially when applied to mobility studies which may require numerous simulation runs. We describe the Quantum-Assisted Helmholtz Machine formulation, suitable
ABSTRACT Ultra-wideband (UWB) radio ranging technology was integrated into a local positioning system (LPS) for tracking mobile robots. A practical issue was the occasional large sporadic errors in the radio range data due to multipath due to reflections and attenuation effect caused by radio penetration through mediums. In this paper, we present a filtering and system integration of the radios with vehicle sensors to produce location and orientation of a moving object being tracked. We introduced a fuzzy neighborhood filter to remove outliers from range data, a progressive trilateration filter to improve update rate and produce a fused estimate of vehicle location with a compass and wheel speed sensors. Experiments were recorded and estimated position and orientation were validated against the video recording of vehicle ground truth. The UWB LPS can be used for navigation and guidance of multiple mobile robots around a command vehicle, and employed for tracking of assets of interest
ABSTRACT Localization refers to the process of estimating ones location (and often orientation) within an environment. Ground vehicle automation, which offers the potential for substantial safety and logistical benefits, requires accurate, robust localization. Current localization solutions, including GPS/INS, LIDAR, and image registration, are all inherently limited in adverse conditions. This paper presents a method of localization that is robust to most conditions that hinder existing techniques. MIT Lincoln Laboratory has developed a new class of ground penetrating radar (GPR) with a novel antenna array design that allows mapping of the subsurface domain for the purpose of localization. A vehicle driving through the mapped area uses a novel real-time correlation-based registration algorithm to estimate the location and orientation of the vehicle with respect to the subsurface map. A demonstration system has achieved localization accuracy of 2 cm. We also discuss tracking results
ABSTRACT The NAUS ATO (2004-2009) was a follow-on program to the Robotic Follower ATO (2000- 2004) and built on the concept of semi-autonomous leader follower technology to achieve dynamic robotic movement in tactical formations. The NAUS ATO also developed and tested an Unmanned Ground Vehicle (UGV) Self-Security system capable of detecting, tracking, and predicting the intent of human beings in the vicinity of the vehicle. The ATO concluded its Engineering and Evaluation Testing (EET) with a capstone demonstration in October 2008. This paper will detail the technology developed and utilized under the program as well as report on the EET results to the robotic community
Southwest Research Institute has developed off-road autonomous driving tools with a focus on stealth for the military and agility for space and agriculture clients. The vision-based system pairs stereo cameras with novel algorithms, eliminating the need for LiDAR and active sensors
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