IMPROV: A system for real-time animation of behavior-based interactive synthetic actors

1997 ◽  
pp. 58-73 ◽  
Author(s):  
Athomas Goldberg
Keyword(s):  
Real Time ◽  
Behavior Based ◽  
Synthetic Actors

Industry First AI-Powered Fully Automated Safety Observation System Deployed to Global Offshore Fleet

2021 ◽  
Author(s):  
Nassima Brown ◽  
Adrian Brown ◽  
Abhijeet Degupta ◽  
Barry Quinn ◽  
Dustin Stringer ◽  
...  
Keyword(s):  
Real Time ◽  
Safety Culture ◽  
Safety Management ◽  
Digital Technologies ◽  
Observation System ◽  
Safety Program ◽  
Effective Application ◽  
Behavior Based ◽  
Global Operations ◽  
The Impact

Abstract As the oil and gas industry is facing tumultuous challenges, adoption of cutting-edge digital technologies has been accelerated to deliver safer, more efficient operations with less impact on the environment. While advanced AI and other digital technologies have been rapidly evolving in many fields in the industry, the HSE sector is playing catch-up. With the increasing complexity of risks and safety management processes, the effective application of data-driven technologies has become significantly harder, particularly for international organizations with varying levels of digital readiness across diverse global operations. Leaders are more cautious to implement solutions that are not fit-for purpose, due to concerns over inconsistencies in rolling out the program across international markets and the impact this may have on ongoing operations. This paper describes how the effective application of Artificial intelligence (AI) and Machine Learning (ML) technologies have been used to engineer a solution that fully digitizes and automates the end-to-end offshore behavior-based safety program across a global offshore fleet; optimizing a critical safety process used by many leading oil & gas organization to drive positive workplace safety culture. The complex safety program has been transformed into clear, efficient and automated workflow, with real-time analytics and live transparent dashboards which detail critical safety indicators in real time, aiding decision-making and improving operational performance. The novel behavior-based safety digital solution, referred to as 3C observation tool within Noble drilling, has been built to be fully aligned with the organization's safety management system requirements and procedures, using modern and agile tools and applications for fully scalability and easy deployment. It has been critical in sharpening the offshore safety observation program across global operations, resulting in a boost of the workforce engagement by 30%, and subsequently increasing safety awareness skill set attainment; improving overall offshore safety culture, all while reducing operating costs by up to 70% and cutting carbon footprint through the elimination of 15,000 manhours and half a million paper cards each year, when compared to previously used methods and workflows

scholarly journals Using Sun’s Java Real-Time System to Manage Behavior-Based Mobile Robot Controllers

2011 ◽  
Vol 2011 ◽  
pp. 1-11
Author(s):  
Andrew McKenzie ◽  
Shameka Dawson ◽  
Fei Hu ◽  
Monica Anderson
Keyword(s):  
Mobile Robot ◽  
Real Time ◽  
Challenging Behavior ◽  
Timing Constraints ◽  
Time System ◽  
Real Time System ◽  
Garbage Collector ◽  
The Real ◽  
Robot Controller ◽  
Behavior Based

Implementing a robot controller that can effectively manage limited resources in a deterministic, real-time manner is challenging. Behavior-based architectures that decompose autonomy into levels of intelligence are popular due to their robustness but do not provide real-time features that enforce timing constraints or support determinism. We propose an architecture and approach for using the real-time features of the Real-Time Specification for Java (RTSJ) in a behavior-based mobile robot controller to show that timing constraints affect performance. This is accomplished by extending a real-time aware architecture that explicitly enumerates timing requirements for each behavior. It is not enough to reduce latency. The usefulness of this approach is demonstrated via an implementation on Solaris 10 and the Sun Java Real-Time System (Java RTS). Experimental results are obtained using a K-team Koala robot performing path following with four composite behaviors. Experiments were conducted using several task period sets in three cases: real-time threads with the real-time garbage collector, real-time threads with the non- real-time garbage collector, and non-real-time threads with the non-real-time garbage collector. Results show that even if latency and determinism are improved, the timing of each individual behavior significantly affects task performance.

Augmented Affective-Cognition for Usability Study of In-Vehicle System User Interface

2014 ◽  
Vol 14 (2) ◽  
Author(s):  
Feng Zhou ◽  
Yangjian Ji ◽  
Roger J. Jiao
Keyword(s):  
User Interface ◽  
Real Time ◽  
Coherent System ◽  
Emotional States ◽  
Usability Study ◽  
Subjective Data ◽  
Vehicle System ◽  
Vehicle Systems ◽  
Behavior Based ◽  
And Behavior

Usability of in-vehicle systems has become increasingly important for ease of operations and safety of driving. The user interface (UI) of in-vehicle systems is a critical focus of usability study. This paper studies how to use advanced computational, physiology- and behavior-based tools and methodologies to determine affective/emotional states and behavior of an individual in real time and in turn how to adapt the human-vehicle interaction to meet users' cognitive needs based on the real-time assessment. Specifically, we set up a set of physiological sensors that are capable of collecting EEG, facial EMG, skin conductance response, and respiration data and a set of motion sensing and tracking equipment that is capable of capturing eye ball movement and objects which the user is interacting with. All hardware components and software are integrated into an augmented sensor platform that can perform as “one coherent system” to enable multimodal data processing and information inference for context-aware analysis of emotional states and cognitive behavior based on the rough set inference engine. Meanwhile subjective data are also recorded for comparison. A usability study of in-vehicle system UI is shown to demonstrate the potential of the proposed methodology.

scholarly journals The Grateful Don’t Cheat: Gratitude as a Fount of Virtue

2019 ◽  
Vol 30 (7) ◽  
pp. 979-988 ◽  
Author(s):  
David DeSteno ◽  
Fred Duong ◽  
Daniel Lim ◽  
Shanyu Kates
Keyword(s):  
Real Time ◽  
Emotional State ◽  
Self Control ◽  
Time Behavior ◽  
Laboratory Setting ◽  
Online Setting ◽  
Moral Qualities ◽  
Behavior Based

Gratitude has been linked to behaviors involving the exchange of resources; it motivates people to repay debts to benefactors. However, given its links to self-control—itself a necessary factor for repaying debts—the possibility arises that gratitude might enhance other virtues unrelated to exchange that depend on an ability to resist temptation. Here, we examined gratitude’s ability to function as a “parent” virtue by focusing on its ability to reduce cheating. Using real-time behavior-based measures of cheating, we demonstrated that gratitude, as opposed to neutrality and the more general positive emotional state of happiness, reduces cheating in both a controlled laboratory setting ( N = 156) and a more anonymous online setting ( N = 141). This finding suggests that not all moral qualities need to be studied in silos but, rather, that hierarchies exist wherein certain virtues might give rise to seemingly unrelated others.

Camera movement for chasing a subject with unknown behavior based on real-time viewpoint goodness evaluation

2010 ◽  
Vol 26 (6-8) ◽  
pp. 629-638 ◽  
Author(s):  
Maya Ozaki ◽  
Like Gobeawan ◽  
Shinya Kitaoka ◽  
Hirofumi Hamazaki ◽  
Yoshifumi Kitamura ◽  
...  
Keyword(s):  
Real Time ◽  
Behavior Based
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