Hierarchical spherical distance fields for collision detection

2006 ◽  
Vol 26 (1) ◽  
pp. 64-74 ◽  
Author(s):  
C. Funfzig ◽  
T. Ullrich ◽  
D.W. Fellner
2012 ◽  
Vol 591-593 ◽  
pp. 827-831
Author(s):  
Jin Wei Jia ◽  
Jian Feng Yu ◽  
Jie Zhang

Collision detection is widely used in human motion simulation, however, it is difficult to work in large equipment model. To overcome the problem, this paper studies a collision detection method especially for virtual arm simulation. First, the method simplifies arm and obstacles in its reaching space with the C-space theory, and divides the space into small unit cells to form a distance fields, then extends the surfaces of obstacles to calculate the distances between each cell and its nearest obstacles, so the result of collision detection is depending on the distance fields’ value. Use CAA to redevelop DELMIA and apply it to the virtual assembly simulation of a certain type of aircraft center wing, compared with triangle intersection algorithm and mixed bounding box method, the result shows that the proposed method improves the efficiency of anthropology ergonomics simulation by more than 20% in the same condition.


ROBOT ◽  
2011 ◽  
Vol 33 (1) ◽  
pp. 40-45 ◽  
Author(s):  
Yuntian HUANG ◽  
Weidong CHEN ◽  
Yixiang SUN

Author(s):  
Sebastian Krügel ◽  
Matthias Uhl ◽  
Bryn Balcombe

AbstractWe address the considerations of the European Commission Expert Group on the ethics of connected and automated vehicles regarding data provision in the event of collisions. While human drivers’ appropriate post-collision behavior is clearly defined, regulations for automated driving do not provide for collision detection. We agree it is important to systematically incorporate citizens’ intuitions into the discourse on the ethics of automated vehicles. Therefore, we investigate whether people expect automated vehicles to behave like humans after an accident, even if this behavior does not directly affect the consequences of the accident. We find that appropriate post-collision behavior substantially influences people’s evaluation of the underlying crash scenario. Moreover, people clearly think that automated vehicles can and should record the accident, stop at the site, and call the police. They are even willing to pay for technological features that enable post-collision behavior. Our study might begin a research program on post-collision behavior, enriching the empirically informed study of automated driving ethics that so far exclusively focuses on pre-collision behavior.


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