IEEE Robotics & Automation Magazine - September 2018 - 56
ball_detection leaf nodes are pushed to the shared
memory. The targeting keyword then links the following branch to the related memory item. By virtue of the
resulting information flows, the leaf nodes look_at and
walk_to dynamically reconfigure their parameters. Eval-
uations along the subtree may also relate to the targeted
memory item; e.g., time_ago refers to the latest time
stamp of the memory item.
ball_detection
searching
(a)
searching
following
ball_detection
Adaptation for Multiple Targets
As presented in the "Targeting" section, the keyword
targeting commands the online creation of subtrees.
That keyword conditions the runtime instantiation of
targeted subtrees to the creation of their related memory
key. Figure 4(a) shows the instantiation of the tree at
startup. Because no corresponding memory key has yet
been created, the following subtree has not been
instantiated. In Figure 4(b), the robot detected a green
ball, and a corresponding following subtree has
been instantiated.
If the ball_detection node differentiates between
balls (e.g., using color information), it pushes related
information to several memory keys. The memory will
host a separate memory key for each ball detected. The
targeting keyword then results in online instantiation
of several subtrees, one per memory key. The script presented in Algorithm 2 can easily be modified to support
an environment with multiple balls (the updated code is
in bold):
targeting ball: following, whenever time_
ago <2, priority of
2 + 1/distance
(b)
This modification sets the robot to follow the closest ball,
as reevaluated continuously during runtime. In Figure 4(c),
the robot detected a red ball, and a second following
branch has been instantiated.
Filtering
Leaf nodes can be used to implement filters. For example, the
original script shows
following
ball_detection
following
searching
targeting ball: following, whenever
time_ago <2, priority of 2
The following modification implements filtering:
(c)
targeting ball: filter | out=filtered_ball
targeting filtered_ball: following,
whenever time_ago <2, priority of 2
Figure 4. An illustration of dynamic topology updating. (a) The
topology of the behavior tree at runtime prior to any ball detection
by the robot. (b) The robot detects a green ball, and a corresponding
following subtree is instantiated (in green). (c) A red ball is
detected, resulting in the instantiation of a competing following
subtree (in red).
56
*
IEEE ROBOTICS & AUTOMATION MAGAZINE
*
september 2018
This syntax is agnostic to the specifics of the filter
implemented. In our example, the filter combines knowledge about the perceived ball with the odometry functionality provided by the middleware to implement a Kalman
IEEE Robotics & Automation Magazine - September 2018
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