Mixed-initiative collaboration between a humanoid robot and a virtual human through a common platform for a real-world common task: Evaluation and benchmarking

2019 ◽  
Vol 11 (5) ◽  
pp. 429-452
Author(s):  
S.M. Mizanoor Rahman
Keyword(s):  
Real World ◽  
Humanoid Robot ◽  
Virtual Human ◽  
Common Task ◽  
Mixed Initiative ◽  
Common Platform

Virtual Standardized Patients for Interactive Conversational Training

2019 ◽  
pp. 62-86 ◽  
Author(s):  
Thomas B. Talbot ◽  
Albert Skip Rizzo
Keyword(s):  
Language Processing ◽  
Medical Patient ◽  
Standardized Patients ◽  
Virtual Human ◽  
Standardized Patient ◽  
User Training ◽  
Pedagogical Design ◽  
Standard Patient ◽  
Mixed Initiative

The USC Standard Patient is a virtual human-based conversational agent serving in the role of a simulated medical patient, also known as a virtual standardized patient (VSP). This research identified deficiencies of extant VSP systems, defined a robust set of requirements, and successfully achieved nearly all of them. Markedly impressive advancements were made in virtual human technology, techniques to apply natural language processing, automated assessment artificial intelligence, and pedagogical design. The effort succeeded with performance parameters of high conversational performance, accurate assessment, and strongly demonstrated user training effect. Although working well within its confined are of expertise, the ability for computers to create authentic mixed initiative conversations remains elusive. This effort leaves behind many lessons for interactive serious games, clinical virtual humans, and conversational virtual human training applications.

Real-world reinforcement learning for autonomous humanoid robot docking

2012 ◽  
Vol 60 (11) ◽  
pp. 1400-1407 ◽  
Author(s):  
Nicolás Navarro-Guerrero ◽  
Cornelius Weber ◽  
Pascal Schroeter ◽  
Stefan Wermter
Keyword(s):  
Reinforcement Learning ◽  
Real World ◽  
Humanoid Robot ◽  
Autonomous Humanoid

scholarly journals Studies in Spatial Aural Perception: Establishing Foundations for Immersive Sonification

2019 ◽  
Author(s):  
Ivica Ico Bukvic ◽  
Gregory Earle ◽  
Disha Sardana ◽  
Woohun Joo
Keyword(s):  
Real World ◽  
Spatial Perception ◽  
Body Movement ◽  
High Density ◽  
Viable Alternative ◽  
Virtual Human ◽  
Spatial Audio ◽  
Auditory Displays ◽  
Audio Data ◽  
Further Development

The Spatial Audio Data Immersive Experience (SADIE) project aims to identify new foundational relationships pertaining to hu-man spatial aural perception, and to validate existing relation-ships. Our infrastructure consists of an intuitive interaction in-terface, an immersive exocentric sonification environment, and a layer-based amplitude-panning algorithm. Here we highlight the system’s unique capabilities and provide findings from an initial externally funded study that focuses on the assessment of human aural spatial perception capacity. When compared to the existing body of literature focusing on egocentric spatial perception, our data show that an immersive exocentric environment enhances spatial perception, and that the physical implementation using high density loudspeaker arrays enables significantly improved spatial perception accuracy relative to the egocentric and virtual binaural approaches. The preliminary observations suggest that human spatial aural perception capacity in real-world-like immersive exocentric environments that allow for head and body movement is significantly greater than in egocentric scenarios where head and body movement is restricted. Therefore, in the design of immersive auditory displays, the use of immersive exocentric environments is advised. Further, our data identify a significant gap between physical and virtual human spatial aural perception accuracy, which suggests that further development of virtual aural immersion may be necessary before such an approach may be seen as a viable alternative.

Development of life-sized high-power humanoid robot JAXON for real-world use

2015 ◽  
Author(s):  
Kunio Kojima ◽  
Tatsuhi Karasawa ◽  
Toyotaka Kozuki ◽  
Eisoku Kuroiwa ◽  
Sou Yukizaki ◽  
...  
Keyword(s):  
High Power ◽  
Real World ◽  
Humanoid Robot

Re-posing Objects Considering Bipedal Stability Constraints: An Approach for Stability Preservation During Humanoid Manipulation

2020 ◽  
Vol 17 (02) ◽  
pp. 2050005
Author(s):  
Daniel Sánchez ◽  
Weiwei Wan ◽  
Fumio Kanehiro ◽  
Kensuke Harada
Keyword(s):  
Real World ◽  
Humanoid Robot ◽  
Center Of Mass ◽  
Stability Margin ◽  
Object Manipulation ◽  
Upper Body ◽  
Manipulation Planning ◽  
Stability Estimation

This paper presents a balance-centered planner for object re-posing. It uses Center-of-Mass (CoM) constraints to preserve robot stability and provides stable, IK-feasible, and collision-free upper-body poses, allowing the robot to complete dexterous object manipulation tasks with different objects. The technical contributions of the planner are two-fold. First, it evaluates the robot stability margin for each robot pose during manipulation planning to find a stable manipulation motion. Second, it provides an RRT-inspired task-related stability estimation used to compare different bipedal stances. Simulations and real-world experiments are performed with the HRP-5P humanoid robot, the 5th generation of the HRP robot family, to validate the planner and compare different robot stances and approaches for object re-posing. The experiment results suggest that the proposed planner provides robust behavior for the humanoid robot while performing re-posing tasks.

scholarly journals Emotions in texts

2020 ◽  
Vol 4 (2) ◽  
pp. 59-69
Author(s):  
Leeveshkumar Pokhun ◽  
M Yasser Chuttur
Keyword(s):  
Real World ◽  
Gold Standard ◽  
Relevant Research ◽  
Emotion Analysis ◽  
Real World Applications ◽  
Emotion Model ◽  
No Gold Standard ◽  
Further Development ◽  
Emotion Models ◽  
Common Platform

Several studies have used different techniques to detect and identify emotions expressed in various sets of texts corpora. In this paper, we review different emotion models, emotion datasets and the corresponding techniques used for emotion analysis in past studies. We observe that researchers have been using a wide variety of techniques to detect emotions in texts and that there is currently no gold standard on which dataset or which emotion model to use. Consequently, although the field of emotion analysis has gained much momentum in previous years, there seems to be little progress into relevant research with findings that may be useful in real world applications. From our analysis and findings, we urge researchers to consider the development of datasets, evaluation benchmarks and a common platform for sharing achievements in emotion analysis to see further development in the field.

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