21,840 research outputs found
FlightGoggles: A Modular Framework for Photorealistic Camera, Exteroceptive Sensor, and Dynamics Simulation
FlightGoggles is a photorealistic sensor simulator for perception-driven
robotic vehicles. The key contributions of FlightGoggles are twofold. First,
FlightGoggles provides photorealistic exteroceptive sensor simulation using
graphics assets generated with photogrammetry. Second, it provides the ability
to combine (i) synthetic exteroceptive measurements generated in silico in real
time and (ii) vehicle dynamics and proprioceptive measurements generated in
motio by vehicle(s) in a motion-capture facility. FlightGoggles is capable of
simulating a virtual-reality environment around autonomous vehicle(s). While a
vehicle is in flight in the FlightGoggles virtual reality environment,
exteroceptive sensors are rendered synthetically in real time while all complex
extrinsic dynamics are generated organically through the natural interactions
of the vehicle. The FlightGoggles framework allows for researchers to
accelerate development by circumventing the need to estimate complex and
hard-to-model interactions such as aerodynamics, motor mechanics, battery
electrochemistry, and behavior of other agents. The ability to perform
vehicle-in-the-loop experiments with photorealistic exteroceptive sensor
simulation facilitates novel research directions involving, e.g., fast and
agile autonomous flight in obstacle-rich environments, safe human interaction,
and flexible sensor selection. FlightGoggles has been utilized as the main test
for selecting nine teams that will advance in the AlphaPilot autonomous drone
racing challenge. We survey approaches and results from the top AlphaPilot
teams, which may be of independent interest.Comment: Initial version appeared at IROS 2019. Supplementary material can be
found at https://flightgoggles.mit.edu. Revision includes description of new
FlightGoggles features, such as a photogrammetric model of the MIT Stata
Center, new rendering settings, and a Python AP
Using colocation to support human memory
The progress of health care in the western world has been
marked by an increase in life expectancy. Advances in life
expectancy have meant that more people are living with
acute health problems, many of which are related to impairment
of memory. This paper describes a pair of scenarios
that use RFID to assist people who may suffer frommemory
defects to extend their capability for independent living. We
present our implementation of an RFID glove, describe its
operation, and show how it enables the application scenarios
Hydrogen leak detection device Patent
Development of device for detecting hydrogen in ambient environment
Object Detection and Sorting using IoT
Color based object sorting has a significant impact in food and processing Industries. Hand picking process in sorting the huge number of objects in industry is very common and laborious task, and time consuming as well, which needs many labors and this conventional method is prone to error. The proposed work aims to replace the hand-picking process by Industrial Internet of Things. The goal of the technique is to sort and count the objects in to different bins accord to their color. A Color sensor, TCS 230 will identify the object and with the help of motors they are made to drop into different bins. The identification of the object is made with the help of frequency concept. As it known that different colors have different wave lengths, so are the different frequencies (f=c/?). For each frequency, the motor rotates to different angles and thus container is attached to motor is also made to rotate to a certain angle, and the object is made to drop into the bin by a jerk. This action details regarding number of objects manufactured are sent to the IoT server, where the vendor and customer will know the details remotely. This proposed work finds a wide range of usage in fruit industry (to pick the unripen fruit), in candy industry, in grain industry (to remove the black stones from the grains), in recycling industry. 
Robust abandoned object detection integrating wide area visual surveillance and social context
This paper presents a video surveillance framework that robustly and efficiently detects abandoned objects in surveillance scenes. The framework is based on a novel threat assessment algorithm which combines the concept of ownership with automatic understanding of social relations in order to infer abandonment of objects. Implementation is achieved through development of a logic-based inference engine based on Prolog. Threat detection performance is conducted by testing against a range of datasets describing realistic situations and demonstrates a reduction in the number of false alarms generated. The proposed system represents the approach employed in the EU SUBITO project (Surveillance of Unattended Baggage and the Identification and Tracking of the Owner)
Potentially Polluting Marine Sites GeoDB: An S-100 Geospatial Database as an Effective Contribution to the Protection of the Marine Environment
Potentially Polluting Marine Sites (PPMS) are objects on, or areas of, the seabed that may release pollution in the future. A rationale for, and design of, a geospatial database to inventory and manipu-late PPMS is presented. Built as an S-100 Product Specification, it is specified through human-readable UML diagrams and implemented through machine-readable GML files, and includes auxiliary information such as pollution-control resources and potentially vulnerable sites in order to support analyses of the core data. The design and some aspects of implementation are presented, along with metadata requirements and structure, and a perspective on potential uses of the database
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