Evaluating and Benchmarking the Interactions between a Humanoid Robot and a Virtual Human for a Real-World Social Task

Author(s):  
S. M. Mizanoor Rahman
2012 ◽  
Vol 60 (11) ◽  
pp. 1400-1407 ◽  
Author(s):  
Nicolás Navarro-Guerrero ◽  
Cornelius Weber ◽  
Pascal Schroeter ◽  
Stefan Wermter

Author(s):  
Ivica Ico Bukvic ◽  
Gregory Earle ◽  
Disha Sardana ◽  
Woohun Joo

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.


Author(s):  
Kunio Kojima ◽  
Tatsuhi Karasawa ◽  
Toyotaka Kozuki ◽  
Eisoku Kuroiwa ◽  
Sou Yukizaki ◽  
...  
Keyword(s):  

2020 ◽  
Vol 17 (02) ◽  
pp. 2050005
Author(s):  
Daniel Sánchez ◽  
Weiwei Wan ◽  
Fumio Kanehiro ◽  
Kensuke Harada

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.


2020 ◽  
Vol 21 (2) ◽  
pp. 243-267
Author(s):  
Luke Jai Wood ◽  
Kerstin Dautenhahn ◽  
Austen Rainer ◽  
Ben Robins ◽  
Hagen Lehmann ◽  
...  

Abstract In recent years the possibility of using humanoid robots to perform interviews with children has been explored in a number of studies. This paper details a study in which a potential real-world user trialled a Robot-Mediated Interviewing system with children to establish if this approach could realistically be used in a real-world context. In this study a senior educational psychologist used the humanoid robot Kaspar to interview ten primary school children about a video they had watched prior to the interview. We conducted a pre and post interview with the educational psychologist before and after using the system to establish how the system worked for him and the perceived potential for real-world applications. The educational psychologist successfully used the system to interview the children and believed that principally using a small humanoid robot to interview children could be useful in a real-world setting provided the system was developed further.


2016 ◽  
Vol 17 (2) ◽  
pp. 248-278 ◽  
Author(s):  
Maxime Petit ◽  
Grégoire Pointeau ◽  
Peter Ford Dominey

Abstract The development of reasoning systems exploiting expert knowledge from interactions with humans is a non-trivial problem, particularly when considering how the information can be coded in the knowledge representation. For example, in human development, the acquisition of knowledge at one level requires the consolidation of knowledge from lower levels. How is the accumulated experience structured to allow the individual to apply knowledge to new situations, allowing reasoning and adaptation? We investigate how this can be done automatically by an iCub that interacts with humans to acquire knowledge via demonstration. Once consolidated, this knowledge is used in further acquisitions of experience concerning preconditions and consequences of actions. Finally, this knowledge is translated into rules that allow reasoning and planning for novel problem solving, including a Tower of Hanoi scenario. We thus demonstrate proof of concept for an interaction system that uses knowledge acquired from human interactions to reason about new situations.


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