Browse Topic: Automation
LIDAR-based autonomous mobile robots (AMRs) are gradually being used for gas detection in industries. They detect tiny changes in the composition of the environment in indoor areas that is too risky for humans, making it ideal for the detection of gases. This current work focusses on the basic aspect of gas detection and avoiding unwanted accidents in industrial sectors by using an AMR with LIDAR sensor capable of autonomous navigation and MQ2 a gas detection sensor for identifying the leakages including toxic and explosive gases, and can alert the necessary personnel in real-time by using simultaneous localization and mapping (SLAM) algorithm and gas distribution mapping (GDM). GDM in accordance with SLAM algorithm directs the robot towards the leakage point immediately thereby avoiding accidents. Raspberry Pi 4 is used for efficient data processing and hardware part accomplished with PGM45775 DC motor for movements with 2D LIDAR allowing 360° mapping. The adoption of LIDAR-based AMRs
To establish and validate new systems incorporated into next generation vehicles, it is important to understand actual scenarios which the autonomous vehicles will likely encounter. Consequently, to do this, it is important to run Field Operational Tests (FOT). FOT is undertaken with many vehicles and large acquisition areas ensuing the capability and suitability of a continuous function, thus guaranteeing the randomization of test conditions. FOT and Use case(a software testing technique designed to ensure that the system under test meets and exceeds the stakeholders' expectations) scenario recordings capture is very expensive, due to the amount of necessary material (vehicles, measurement equipment/objectives, headcount, data storage capacity/complexity, trained drivers/professionals) and all-time robust working vehicle setup is not always available, moreover mileage is directly proportional to time, along with that it cannot be scaled up due to physical limitations. During the early
Spot welds are integral to automotive body construction, influencing vehicle performance and durability. Spot welding ensures structural integrity by creating strong bonds between metal sheets, crucial for maintaining vehicle safety and performance. It is highly compatible with automation, allowing for streamlined production processes and increased efficiency in automotive assembly lines. The number and distribution of spot welds directly impact the vehicle's ability to withstand various loads and stresses, including impacts, vibrations, and torsion. Manufacturers adhere to strict quality control standards to ensure the integrity of spot welds in automotive production. Monitoring spot weld count and weld quality during manufacturing processes through advanced inspection techniques such as Image processing by YOLOv8 helps identify the number of spots and quality that could compromise safety. Automating quality control processes is paramount, and machine vision offers a promising
Liebherr and Fortescue unveiled their first autonomous battery-electric T 264 haul truck at MINExpo 2024, garnering a steady stream of attendees eyeing and climbing on the giant machine. The truck is the culmination of nearly three years of development work and collaboration among the autonomy and zero-emission units of Liebherr and Fortescue. The T 264 electric hauler features a 3.2-MWh battery system, comprising eight sub-packs, developed by Fortescue Zero. Fortescue also developed a stationary fast-charging solution to support the new T 264. The charger will be available in both manual and robotic versions. An automated quick charger of up to 6 MW with two megawatt charging system (MCS) plugs can reportedly charge the current battery-electric T 264 in 30 minutes
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 The importance of hardening robotic and autonomous systems (RAS) considered for field deployment against cyber threats has been recognized by organizations across the Department of Defense (DoD). Among these needs is the ability to securely provide these modern military vehicles with software updates containing critical new functionality and security improvements. A secure update process and system for military RAS has been implemented building on a framework designed for the automotive industry. Demonstrations of the capabilities and mitigations against possible attacks on the update process will be performed on a RAS MRZR in a mock field environment. Citation: S. Pereira, C. Mott, D. Mikulski, “Secure Update Process For Robotic And Autonomous Systems,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 15-17, 2023
ABSTRACT Significant Design for Reliability (DfR) methodology challenges are created with the integration of autonomous vehicle technologies via applique systems in a ground military vehicle domain. Voice of the customer data indicates current passenger vehicle usage cycles are typically 5% or less (approximately 72 minutes of use in a twenty-four hour period) [2]. The time during which vehicles currently lay dormant due to drivers being otherwise occupied could change with autonomous vehicles. Within the context of the fully mature autonomous military vehicle environment, the daily vehicle usage rate could grow to 95% or more. Due to this potential increase in the duty or usage cycle of an autonomous military vehicle by an order of magnitude, several issues which impact reliability are worth exploring. Citation: M. Majcher, J. Wasiloff, “New Design for Reliability (DfR) Needs and Strategies for Emerging Autonomous Ground Vehicles”, In Proceedings of the Ground Vehicle Systems
ABSTRACT Future autonomous combat vehicles will need to travel off-road through poorly mapped environments. Three-dimensional topography may be known only to a limited extent (e.g. coarse height), but this will likely be noisy and of limited resolution. For ground vehicles, 3D topography will impact how far ahead the vehicle can “see”. Higher vantage points and clear views provide much more useful path planning data than lower vantage points and occluded views from trees and structures. The challenge is incorporating this knowledge into a path planning solution. When should the robot climb higher to get a better view or else continue moving along the shortest path predicted by current information? We investigated the use of Deep Q-Networks (DQN) to reason over this decision space, comparing performance to conventional methods. In the presence of significant sensor noise, the DQN was more successful in finding a path to the target than A* for all but one type of terrain. Citation: E
ABSTRACT The University of Delaware (UD) and the US Army DEVCOM-GVSC (GVSC) have partnered to show the feasibility of fabricating mission specific, man-packable, autonomous vehicles that are created by Computer Aided Design (CAD) and are then produced, from start-to-finish, in a single manufacturing unit-cell without human intervention in the manufacturing process. This unit-cell contains many manufacturing processes (e.g., additive manufacturing (AM), pick-and-place, circuit printing, and subtractive manufacturing) that work in concert to fabricate functional devices. Together, UD and GVSC have developed the very first mission specific autonomous vehicle that is fully fabricated in a single manufacturing unit-cell without being touched by human hand. Citation: Jacob W. Robinson, Thomas W. Lum, Zachary J. Larimore, Matthew P. Ludkey, Larry (LJ) R. Holmes, Jr. “AUTOMATED MANUFACTURING FOR AUTONOMOUS SYSTEMS SOLUTIONS (AMASS)”, In Proceedings of the Ground Vehicle Systems Engineering and
ABSTRACT The Soar Cognitive Architecture is a reasoning system that enables knowledge-rich, mission focused reasoning including integration of bottom-up, sensor-driven reasoning and top-down, context-driven reasoning, and more intelligent use of existing sensors. This reasoning is a combination of deliberate (e.g., planning) and reactive (e.g., hard-coded) behaviors. We are applying Soar on a current effort to (1) increase autonomy and (2) achieve equivalent or superior performance while controlling weight, energy, and costs
ABSTRACT Main Battle Tanks (MBTs) remain a key component of most modern militaries. While the best way to ‘kill a tank’ is via the employment of another tank, matching enemy armor formations one-for one is not always possible. Light infantry lack organic armor and their shoulder launched anti-tank capabilities do not defeat the latest generation of MBTs. To compensate for this capability gap, the U.S. Army has employed precision guided anti-tank munitions, such as the “Javelin.” However, these are expensive to produce in quantity and require risking the forward presence of dismounted Soldiers to employ. Mine fields offer another option but are immobile once employed. The ‘Guillotine’ Attack System proposes to change the equation by pairing an AI enabled, adaptive unmanned delivery system with a shaped charge payload. Guillotine can loiter for hours, reposition itself to hunt for targets, and- when ready- deliver a precision shaped charge strike from the air. Citation: “The ‘Guillotine
ABSTRACT FEV North America will discuss application of advanced automotive cybersecurity to smart vehicle projects, - software safety - software architecture and how it applies to similar features and capabilities across the fleet of DoD combat and tactical vehicles. The analogous system architectures of automotive and military vehicles with advanced architectures, distributed electronic control units, connectivity to networks, user interfaces and maintenance networks and interface points clearly open an opportunity for DoD to leverage the technology techniques, hardware, software, management and human resources to drive implementation costs down while implementing fleet modifications, infrastructure methodology and many of the features of the automotive cyber security spectrum. Two of the primary automotive and DoD subsystems most relevant to Cyber Security threat and protection are the automotive connected vehicles analogous to the DoD Command, Control, Communications, Computers
ABSTRACT The Army Operating Concept and the Cross Domain Maneuver Concept describe more capable Brigade Combat Teams that can operate semi-independently across wide areas on the future battlefield. Robotics and Autonomous Systems can increase capabilities of Brigade Combat Teams by increasing situational awareness, facilitating movement and maneuver, improving protection, extending a small unit’s area of operations, and sustaining the force with increased distribution, throughput, and efficiency. Army industry partners, in concert with Army labs, must provide the affordable technologies that can provide these autonomous and semi-autonomous operational capabilities to the future force. While acknowledging that there must be significant technology development to realize this vision, this concept paper aims to take a realistic look at enabling Brigade Combat Teams with third-offset capabilities by 2035
ABSTRACT The objective is to develop a human-multiple robot system that is optimized for teams of heterogeneous robots control. A new human-robot system permits to ease the execution of remote tasks. An operator can efficiently control the physical multi-robots using the high level command, Drag-to-Move method, on the virtual interface. The innovative virtual interface has been integrated with Augmented Reality that is able to track the location and sensory information from the video feed of ground and aerial robots in the virtual and real environment. The advanced feature of the virtual interface is guarded teleoperation that can be used to prevent operators from accidently driving multiple robots into walls and other objects
ABSTRACT The IGVC offers a design experience that is at the very cutting edge of engineering education. It is multidisciplinary, theory-based, hands-on, team implemented, outcome assessed, and based on product realization. It encompasses the very latest technologies impacting industrial development and taps subjects of high interest to students. Design and construction of an Intelligent Vehicle fits well in a two semester senior year design capstone course, or an extracurricular activity earning design credit. The deadline of an end-of-term competition is a real-world constraint that includes the excitement of potential winning recognition and financial gain. Students at all levels of undergraduate and graduate education can contribute to the team effort, and those at the lower levels benefit greatly from the experience and mentoring of those at higher levels. Team organization and leadership are practiced, and there are even roles for team members from business and engineering
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 Today we have autonomous vehicles already on select road-ways and regions of this country operating in and around humans and human operated vehicles. The companies developing and testing these systems have experienced varied degrees of success and failure with regard to safe operations within this public space. There have been safety incidents that have made national headlines (when human fatalities have occurred) and their also exist a litany of other physical incidents, usually with human operated systems, that have not grabbed the headlines. Some of the select communities where these autonomous systems have been operationally tested have revoked access to their roadways (kicked out) some of these companies. As a result of these incidents recent data suggests that the public trust in autonomous vehicles is eroding [1]. This situation is couponed by the fact that there are no established safety standards, measures or technological methods to help local, state or national
ABSTRACT The automotive and defense industries are going through a period of disruption with the advent of Connected and Automated Vehicles (CAV) driven primarily by innovations in affordable sensor technologies, drive-by-wire systems, and Artificial Intelligence-based decision support systems. One of the primary tools in the testing and validation of these systems is a comparison between virtual and physical-based simulations, which provides a low-cost, systems-approach testing of frequently occurring driving scenarios such as vehicle platooning and edge cases and sensor-spoofing in congested areas. Consequently, the project team developed a robotic vehicle platform—Scaled Testbed for Automated and Robotic Systems (STARS)—to be used for accelerated testing elements of Automated Driving Systems (ADS) including data acquisition through sensor-fusion practices typically observed in the field of robotics. This paper will highlight the implementation of STARS as a scaled testbed for rapid
ABSTRACT A simple, quantitative measure for encapsulating the autonomous capabilities of unmanned ground vehicles (UGVs) has yet to be established. Current models for measuring a UGV’s autonomy level require extensive, operational level testing, and provide a means for assessing the autonomy level for a specific mission and operational environment. A more elegant technique for quantifying UGV autonomy using component level testing of the UGV platform alone, outside of mission and environment contexts, is desirable. Using a high level framework for UGV architectures, such a model for determining a UGV’s level of autonomy has been developed. The model uses a combination of developmental and component level testing for each aspect of the UGV architecture to define a non-contextual autonomous potential (NCAP). The NCAP provides an autonomy level, ranging from fully non-autonomous to fully autonomous, in the form of a single numeric parameter describing the UGV’s performance capabilities
ABSTRACT System and software requirements provide a definition of what the system implementation is required to do, and are a necessary component to independent requirement based testing for safety critical systems. However as vital as these requirements are, the requirements often are not analyzed until a safety assessment is performed, or the system fails during testing. Automating the system analysis and testing can be used to help to shift left the software life cycle, particularly when the automation augments, rather than replaces, human test developers. This paper presents a method to convert textual requirements into a logical model of the system. This logical model can be used for various automated system analysis procedures, as well as automated test generation. We show this automation can provide significant insight into possible issues in the system, as well as significantly accelerating the time required for test development. Citation: M. Lingg, H. Paul, S. Kushwaha, J
ABSTRACT Gas metal arc pulse directed energy deposition (GMA-P DED) offers large-scale additive manufacturing (AM) capabilities and lower cost systems compared to laser or electron beam DED. These advantages position GMA-DED as a promising manufacturing process for widespread industrial adoption. To enable this “digital” manufacturing of a component from a computer-aided design (CAD) file, a computer-aided manufacturing (CAM) solver is necessary to generate build plans and utilize welding parameter sets based on feature and application requirements. Scalable and robot-agnostic computer-aided robotics (CAR) software is therefore essential to provide automated toolpath generation. This work establishes the use of Autodesk PowerMill Ultimate software as a CAM/CAR solution for arc-based DED processes across robot manufacturers. Preferred aluminum GMA-P DED welding parameters were developed for single-pass wide “walls” and multi-pass wide “blocks” that can be configured to build a wide
ABSTRACT In this paper, we will present the results of our efforts developing the Autonomy Kit for the Tank Automotive Research Development and Engineering Center’s (TARDEC) Autonomous Ground Resupply (AGR) Sustainment Operations (SO) program. Robotic Research, LLC was responsible for the design, build, and implementation of the “Autonomy Kit” for the AGR SO. The Autonomy Kit is designed to be a fault-tolerant, vehicle-agnostic applique kit that provides the hardware and software needed to perform higher-level autonomous driving and planning functions. In the first Increment, the main focus was developing a “Leader/Follower” capability, where a manned “Leader” vehicle could perform a mission with a number of unmanned “Followers” reproducing its trajectory, maintaining convoy constraints, and avoiding obstacles in the path
ABSTRACT This paper surveys the state of autonomous systems and outlines a novel command and control (C2) paradigm that seeks to accommodate the environmental challenges facing warfighters and their robotic counterparts in the future. New interface techniques will be necessary to reinforce the paradigm that supports the C2 of multiple human-machine teams completing diverse missions as part of the Third Offset Strategy. Realizing this future will require a new approach to teaming and interfaces that fully enable the potential of independent and cooperative decision-making abilities of fully autonomous machines while maximizing the effectiveness of human operators on the battlefield
ABSTRACT Militaries worldwide are increasing their Research and Development (R&D) into RAS. Within the next 10 – 15 years RAS will play an active part in operations as the future battlefield becomes more complex. CRT technology can significantly reduce platform weight, fuel consumption, noise and vibration levels[1][2][3]. Armies and vehicle manufacturers have initiated a series of independent trials that confirmed the benefits and reliability of CRT on a tracked military vehicle. With the increase in RAS technologies comes a desire to utilize the proven benefits identified from manned platforms. The author’s objective is to highlight the findings of these trials[1][2][3] and provide substantiated data on how CRT technology can benefit RAS in terms of weight saving, whilst reducing maintenance and vibration. Citation: Fabien Lagier, Ing. MBA, “Composite Rubber Track (CRT) for Robotic & Autonomous System (RAS)”, In Proceedings of the Ground Vehicle Systems Engineering and Technology
ABSTRACT This paper presents the conceptual design, development, and implementation of the Robotic Technology Kernel (RTK) in a Polaris GEM e2 by the United States Military Academy's autonomy research team. RTK is the autonomous software suite of the U.S. Army Combat Capabilities Development Command Ground Vehicles Systems Center and to this point has primarily been used within off-road environments. The research team's primary objectives were to verify RTK's platform-agnostic characteristic by implementing the control software on a small, low-speed electric vehicle and augmenting the software to provide the additional capability of operating within an established infrastructure rule set. Citation: J. Cymerman, S. Yim, D. Larkin, K. Pegues, W. Gengler, S. Norman, Z. Maxwell, N. Gasparri, M. Pollin, C. Calderon, J. Angle, J. Collier, “Evolving the Robotic Technology Kernal to Expand Future Force Autonomous Ground Vehicle Capabilities,” In Proceedings of the Ground Vehicle Systems
ABSTRACT Presented are two designs for compact, low-profile UGVs with high cross-country mobility, intended for underbody operations with heavy manned vehicles. These UGVs are designed to remotely detect and assess combat damage incurred during combat operations, and analyze wear, leaks, and cracks, without the need for a human technician to be exposed to enemy fire, allowing crews to rapidly assess the conditions of their vehicles. Since robots required for underbody inspection would necessarily maintain a low, compact profile, they could also perform effective last-mile resupply in a contested environment, their small size allowing them to hide behind terrain and battlefield debris much more effectively than a heavy logistics robot. Naturally, a robotic vehicle that is capable of rapid underbody inspection of friendly vehicles or last-mile resupply could also be easily adapted as a combat platform to be used against enemy vehicles. Citation: A. Washington, et al., “Expendable Low
ABSTRACT The utilization of model-based systems engineering (MBSE) is a key enabler for high quality system design and application of Modular Open Systems Approach (MOSA) principles. The Autonomous Ground Vehicle Reference Architecture (AGVRA) provides meta-models, architectural guidelines, best practices, and a library of reusable model content for the Army Robotics and Autonomous Systems (RAS) community to facilitate the MBSE development of autonomous systems. This paper provides a summary of AGVRA’s models, detailing the categories of model elements along with their overall utility, and describes key applications of AGVRA currently being utilized across the DoD. The applications of the AGVRA MBSE work products are contributing to high quality outcomes in RAS systems, providing new and improved functional and operational autonomous ground vehicle capability. Citation: C. Cheung, S. Griffith, L. Wells, D. Gregory, M. Moore, M. Johannes, D. Hetherington, J. Walters, S. Kang
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 The IGVC offers a design experience that is at the very cutting edge of engineering education, with a particular focus in developing engineering control/sensor integration experience for the college student participants. A main challenge area for teams is the proper processing of all the vehicle sensor feeds, optimal integration of the sensor feeds into a world map and the vehicle leveraging that world map to plot a safe course using robust control algorithms. This has been an ongoing challenge throughout the 26 year history of the competition and is a challenge shared with the growing autonomous vehicle industry. High consistency, reliability and redundancy of sensor feeds, accurate sensor fusion and fault-tolerant vehicle controls are critical, as even small misinterpretations can cause catastrophic results, as evidenced by the recent serious vehicle crashes experienced by self-driving companies including Tesla and Uber Optimal control techniques & sensor selection
ABSTRACT Over time, the National Institute of Standards and Technology (NIST) has refined the 4Dimension / Real-time Control System (4D/RCS) architecture for use in Unmanned Ground Vehicles (UGVs). This architecture, when applied to a fully autonomous vehicle designed for missions in urban environments, can greatly assist in the process of saving time and lives by creating a more intelligent vehicle that acts in a safer and more efficient manner. Southwest Research Institute (SwRI®) has undertaken the Southwest Safe Transport Initiative (SSTI) aimed at investigating the development and commercialization of vehicle autonomy as well as vehicle-based telemetry systems to improve active safety systems and autonomy. This paper will discuss the implementation of the 4D/RCS architecture to the SSTI autonomous vehicle, a 2006 Ford Explorer
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
Items per page:
50
1 – 50 of 2939