Projective Virtual Reality

yardbellΤεχνίτη Νοημοσύνη και Ρομποτική

14 Νοε 2013 (πριν από 4 χρόνια και 8 μήνες)

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Projective Virtual Reality

Freund and Rossmann

Summarized by Geb Thomas


Create a scalable approach to graphically
oriented man
manchine interfaces

Suited for robotics and automation in a
factory environment and for robot control
over long distances

Projective Virtual Reality

“project” actions from the virtual world into
the real world through robots

VR automatically translates actions in VR
to change the real world

Changes in the real world change things in

Basic of Projective VR

Quality of man machine interface depends
on the user

“The less the user in the virtual world
needs to know about the means of
automation which carry out the task
physically, the better is the design of the
man machine interface.”

A Straightforward Approach

Teleoperation or hand
tracking mode

directly track the data
glove with the
robot’s TCP

flexible, OK if there is no direct contact

Three modes:


generating robot programs

direct on
line connection

Disadvantages of Teleoperation

Time delays

precision of graphical model

precise position and orientation information

hand tremble

Online collision avoidance is necessary

Versatile sensor control is necessary to
avoid unwanted tensions

Task Deduction

Inspired by listening to transcripts from
ground control “move sample A into slot B”
or “replace battery in facility C”

Objective: give commands to the robot
system on different levels of abstraction

Subtasks are automatically recognized
through task deduction

Principles of Task Deduction

3 Different classes of action

interactions with the environment

events related to user movements

events related to VR/robot communication


User is out of “realtime control loop”

Subtasks are carried out safely with sensor control

Sensors compensate for VR inaccuracies

Accuracy of data
glove less important

IRCS planning allows multi
robot coordination

Multi users

No longer a need to show robots

Multi automation controlled in a single environment


Must know the type of task in advance

Example tasks set by German Space
Agency were 95% successful

Action Planning

Translate high level goals to specific actions

generates an ordered set of elementary

Demands are represented by a constraint net

Selection is performed by task’s subject or
by a selection rule

Images and Metaphors
Simplifying the Work

Locations of physical objects

Visualizing Sensor Information

Placement Aids

Virtual Time

view into reality