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Georgia Tech Research Institute (GTRI)
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ItemKnowledge Driven Robotics: What the future holds(Georgia Institute of Technology, 2023-11-29) Balakirsky, Stephen
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ItemDeep Segments: Comparisons between Scenes and their Constituent Fragments using Deep Learning(Georgia Institute of Technology, 2014-09) Doshi, Jigar ; Mason, Celeste ; Wagner, Alan ; Kira, ZsoltWe examine the problem of visual scene understanding and abstraction from first person video. This is an important problem and successful approaches would enable complex scene characterization tasks that go beyond classification, for example characterization of novel scenes in terms of previously encountered visual experiences. Our approach utilizes the final layer of a convolutional neural network as a high-level, scene specific, representation which is robust enough to noise to be used with wearable cameras. Researchers have demonstrated the use of convolutional neural networks for object recognition. Inspired by results from cognitive and neuroscience, we use output maps created by a convolutional neural network as a sparse, abstract representation of visual images. Our approach abstracts scenes into constituent segments that can be characterized by the spatial and temporal distribution of objects. We demonstrate the viability of the system on video taken from Google Glass. Experiments examining the ability of the system to determine scene similarity indicate ρ (384) = ±0:498 correlation to human evaluations and 90% accuracy on a category match problem. Finally, we demonstrate high-level scene prediction by showing that the system matches two scenes using only a few initial segments and predicts objects that will appear in subsequent segments.
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ItemAutonomous Robots in the Fog of War(Georgia Institute of Technology, 2011-08) Weiss, Lora
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ItemAn Overview of Autonomous Underwater Vehicle Systems and Sensors at Georgia Tech(Georgia Institute of Technology, 2011-03-16) West, Michael E. ; Collins, Thomas R. ; Bogle, John R. ; Melim, Andrew ; Novitzky, MichaelAs the ocean attracts great attention on environmental issues and resources as well as scientific and military tasks, the need for the use of underwater vehicle systems has become more apparent. Underwater vehicles represent a fast-growing research area and promising industry as advanced technologies in various subsystems develop and potential application areas are explored. Great efforts have been made in developing autonomous underwater vehicles (AUVs) to overcome challenging scientific and engineering problems caused by the unstructured and hazardous ocean environment. With the development of new materials, advanced computing and sensory technology, as well as theoretical advancements, research and development activities in the AUV community have increased. The Georgia Institute of Technology (GIT) is actively involved in three major research efforts: underwater vehicle sensing, underwater communications, and underwater vehicle autonomy including heterogeneous multi-vehicle collaboration. In order to test and experimentally validate the research, GIT has developed a new small man-portable Autonomous Underwater Vehicle called the Yellowfin. This new AUV provides a testbed for real world testing and experimentation of the advanced algorithm development. This paper will show the GIT development in this area.
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ItemThe Yellowfin Autonomous Underwater Vehicle Acoustic Communication Design and Testing(Georgia Institute of Technology, 2011) Bogle, John R. ; Melim, Andrew ; West, Michael E.Over the past two years, the Georgia Tech Research Institute (GTRI) has developed a new Unmanned Underwater Vehicle (UUV) called the Yellowfin. The purpose of the vehicle is to provide a platform for research and development of autonomous, multivehicle underwater technology. This paper documents the design of the vehicle with an emphasis on the acoustic communication system, including the hardware and software. The testing of the ACOMMS hardware and software system is also discussed.
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ItemA Network-based Approach for Assessing Co-Operating Manned and Unmanned Systems (MUMS)(Georgia Institute of Technology, 2010-09) Weiss, Lora G.Traditionally, robots have been programmed to do precisely what their human operators instruct them to do, but more recently, they have become more sophisticated, intelligent, and autonomous. Once they reach a sufficiently high level of intelligent autonomy, they can support more collaborative interactions with each other and with people. As robots become more and more intelligent, we will begin designing systems where robots interact with humans, rather than designing robots that are commanded by people with continual oversight. One approach to assessing how humans and robots will interact in the future is to frame the problem as a collection of intelligent nodes. Multiple, collaborating, and interacting manned and robotic systems can be represented as a collection of dynamic, interacting nodes. This paper develops preliminary metrics to support understanding the extent of preferential attachment that would arise in a system of co-operating manned and unmanned systems (MUMS). The metrics seek to help explain if attachments are localized to specific situations or if they are more pervasive throughout a MUMS society.
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ItemDesign and Development of the Yellowfin UUV for Homogenous Collaborative Missions(Georgia Institute of Technology, 2010) West, Michael E. ; Novitzky, Michael ; Varnell, Jesse P. ; Melim, Andrew ; Sequin, Evan ; Toler, Tedd C. ; Collins, Tomas R. ; Bogle, John R.Georgia Tech Research Institute (GTRI) has developed the Yellowfin, a small man-portable Unmanned Underwater Vehicle (UUV). The mission for Yellowfin is to conduct autonomous collaborative operations. The multi-UUV design allows for a much wider swath of the ocean to be observed and monitored, while collaborative operations allow multiple aspects of a mission to be tackled with distributed systems. Both oceanographic and military missions are aided tremendously by the use of such a UUV network. This paper introduces the modular and flexible design of the Yellowfin system and describes some of the technologies integrated within the system construct. The system and software architectures of Yellowfin leverage COTS technologies, including software whose foundation is MOOS-IvP, expanded to include several aspects of autonomy, communication with the WHOI acoustics modem utilizing the JAUS message standard, mission planning using MissionLab, mission execution via Falcon- ViewTM , front seat control with a microcontroller, and visualization with the Blender open-source, cross-platform suite of tools for 3D graphics.
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ItemKinematics and Verification of a Deboning Device(Georgia Institute of Technology, 2009-08) Zhou, Debao ; Daley, Wayne ; McMurray, GaryPoultry deboning process is one of the largest employers in the United States and mainly involves human workers due to the unstructured nature of the task. For the automation of this process, a cutting device with the adaptive capability has been developed. In this paper, we focused on the kinematics of this device and the accuracy of the actual cutting point location. We validated the kinematic formulation and proofed the confidence of the accurate cutting. The applied verification method can be generalized to be applicable to general kinematics verification.
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ItemIntelligent Cutting of the Bird Shoulder Joint(Georgia Institute of Technology, 2009) Hu, Ai-Ping ; Grullon, Sergio ; Zhou, Debao ; Holmes, Jonathan ; Holcombe, Wiley ; Daley, Wayne ; McMurray, GaryDeboning operations are one of the largest users of on-line labor in today’s poultry plants. Efforts have been made over the years to automate this function, but to date have achieved only limited success. The main difficulty in this task is its unstructured nature due to the natural variability in the sizes of birds and their deformable bodies. To increase product safety and quality, the industry is looking to robotics to help solve these problems. This research has focused on developing a new method of automating the deboning of bird front halves. If this task can be automated, the technology would naturally be extended to other cuts and trimming operations in poultry and red meat. To accomplish this goal, the project team has been working for the past four years on the development of a sensor-based intelligent cutting system. This work is based on the development of a model for the cutting of bio-materials that can be extended to the cutting of meat, tendon, ligaments, and bone. When this model is combined with data from the tendon prediction system, the nominal cutting trajectory can be established and adjusted based on the cutting model in conjunction with knowledge of the bird's anatomy. The value in accomplishing this work would be to not only reduce labor costs but also to increase the yield of breast meat and reduce/eliminate bone chips. It is estimated that an increase in yield of a single percentage point could represent several millions of dollars of additional revenue for each and every plant. Current attempts at automation of the shoulder cut impose several percentage points of yield loss in return for lower labor costs. In the manual process, while generally providing a higher yield of breast meat, the quality of the product varies dramatically based on the skill of the worker, and the labor costs are significantly higher. It is the goal of this work to develop a system that eliminates labor and consistently provides a yield similar to the best manual worker. The overall vision for this project requires the development of various technology components that will be unified into a single operational system. This includes a system to identify the initial cutting point, a system to specify the nominal cutting trajectory based on the size of that specific bird, a model to predict the location of the joint and shoulder tendons given the position/orientation of the wing tip, a mathematical model of the cutting process that allows the control system to interpret force/torque data and make intelligent motion commands to avoid cutting through the bone, and a robotic platform capable of executing these commands in real-time.
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ItemThe System Engineering and Test (TSET) Approach for Unprecedented Systems(Georgia Institute of Technology, 2009) Weiss, Lora G. ; Roberts, Rusty ; Cross, Stephen E.The rapid pace of development of new systems coupled with a strong desire from warfighters to quickly field systems with advanced technologies and innovation poses new Test and Evaluation (T&E) challenges. These challenges start with the realization that most T&E procedures are derived from a historical, requirements-based approach to acquisition, which inherently is a sequential process. For innovative and unprecedented systems, i.e., the kind of system for which there is no experience in building similar systems or in their test or use, T&E cannot follow a sequential approach. Throughout military history, development of unprecedented systems has occurred when there has been a simultaneous advance in technology and operational need such as is occurring now in the domain of unmanned systems. T&E needs to evolve to be integrated with the development process. Waiting for the results of developmental and operational testing will only exacerbate the delay in rapidly fielding advanced capabilities. This article presents the tenets of using the system engineering and test approach for evaluating unprecedented systems and moving testing to the forefront of the system development process.