17,497 research outputs found
Manipulator system man-machine interface evaluation program
Application and requirements for remote manipulator systems for future space missions were investigated. A manipulator evaluation program was established to study the effects of various systems parameters on operator performance of tasks necessary for remotely manned missions. The program and laboratory facilities are described. Evaluation criteria and philosophy are discussed
Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review
Animals play a profoundly important and intricate role in our lives today.
Dogs have been human companions for thousands of years, but they now work
closely with us to assist the disabled, and in combat and search and rescue
situations. Farm animals are a critical part of the global food supply chain,
and there is increasing consumer interest in organically fed and humanely
raised livestock, and how it impacts our health and environmental footprint.
Wild animals are threatened with extinction by human induced factors, and
shrinking and compromised habitat. This review sets the goal to systematically
survey the existing literature in smart computing and sensing technologies for
domestic, farm and wild animal welfare. We use the notion of \emph{animal
welfare} in broad terms, to review the technologies for assessing whether
animals are healthy, free of pain and suffering, and also positively stimulated
in their environment. Also the notion of \emph{smart computing and sensing} is
used in broad terms, to refer to computing and sensing systems that are not
isolated but interconnected with communication networks, and capable of remote
data collection, processing, exchange and analysis. We review smart
technologies for domestic animals, indoor and outdoor animal farming, as well
as animals in the wild and zoos. The findings of this review are expected to
motivate future research and contribute to data, information and communication
management as well as policy for animal welfare
A preliminary experiment definition for video landmark acquisition and tracking
Six scientific objectives/experiments were derived which consisted of agriculture/forestry/range resources, land use, geology/mineral resources, water resources, marine resources and environmental surveys. Computer calculations were then made of the spectral radiance signature of each of 25 candidate targets as seen by a satellite sensor system. An imaging system capable of recognizing, acquiring and tracking specific generic type surface features was defined. A preliminary experiment definition and design of a video Landmark Acquisition and Tracking system is given. This device will search a 10-mile swath while orbiting the earth, looking for land/water interfaces such as coastlines and rivers
Non-contact Multimodal Indoor Human Monitoring Systems: A Survey
Indoor human monitoring systems leverage a wide range of sensors, including
cameras, radio devices, and inertial measurement units, to collect extensive
data from users and the environment. These sensors contribute diverse data
modalities, such as video feeds from cameras, received signal strength
indicators and channel state information from WiFi devices, and three-axis
acceleration data from inertial measurement units. In this context, we present
a comprehensive survey of multimodal approaches for indoor human monitoring
systems, with a specific focus on their relevance in elderly care. Our survey
primarily highlights non-contact technologies, particularly cameras and radio
devices, as key components in the development of indoor human monitoring
systems. Throughout this article, we explore well-established techniques for
extracting features from multimodal data sources. Our exploration extends to
methodologies for fusing these features and harnessing multiple modalities to
improve the accuracy and robustness of machine learning models. Furthermore, we
conduct comparative analysis across different data modalities in diverse human
monitoring tasks and undertake a comprehensive examination of existing
multimodal datasets. This extensive survey not only highlights the significance
of indoor human monitoring systems but also affirms their versatile
applications. In particular, we emphasize their critical role in enhancing the
quality of elderly care, offering valuable insights into the development of
non-contact monitoring solutions applicable to the needs of aging populations.Comment: 19 pages, 5 figure
Learning by observation through system identification
In our previous works, we present a new method
to program mobile robots —“code identification by
demonstration”— based on algorithmically transferring
human behaviours to robot control code using
transparent mathematical functions. Our approach
has three stages: i) first extracting the trajectory of the
desired behaviour by observing the human, ii) making
the robot follow the human trajectory blindly to
log the robot’s own perception perceived along that
trajectory, and finally iii) linking the robot’s perception
to the desired behaviour to obtain a generalised,
sensor-based model.
So far we used an external, camera based motion
tracking system to log the trajectory of the human
demonstrator during his initial demonstration of the
desired motion. Because such tracking systems are
complicated to set up and expensive, we propose an alternative method to obtain trajectory information, using the robot’s own sensor perception.
In this method, we train a mathematical polynomial using the NARMAX system identification methodology which maps the position of the “red jacket” worn by the demonstrator in the image captured by the robot’s camera, to the relative position of the demonstrator in the real world according to the robot.
We demonstrate the viability of this approach by teaching a Scitos G5 mobile robot to achieve door traversal behaviour
Cognitive visual tracking and camera control
Cognitive visual tracking is the process of observing and understanding the behaviour of a moving person. This paper presents an efficient solution to extract, in real-time, high-level information from an observed scene, and generate the most appropriate commands for a set of pan-tilt-zoom (PTZ) cameras in a surveillance scenario. Such a high-level feedback control loop, which is the main novelty of our work, will serve to reduce uncertainties in the observed scene and to maximize the amount of information extracted from it. It is implemented with a distributed camera system using SQL tables as virtual communication channels, and Situation Graph Trees for knowledge representation, inference and high-level camera control. A set of experiments in a surveillance scenario show the effectiveness of our approach and its potential for real applications of cognitive vision
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