ELSEVIER Robotics and Autonomous Systems 19 (1997) 259-271
Robotics and
Autonomous
Systems
Hierarchical refinement of skills and skill application
for autonomous robots
Michael Kaiser*, Riidiger Dillmann
University of lfarlsruhe, Institute for Real-Time ComputerSystems and Robotics, D-76128Karlsruhe, Germany
Abstract
One of the major goals in designing learning robots is to let these robots develop useful skills over time. These skills are
not only related to physical actions of the robot, but also to the coordination of activities, communication with humans, and
active sensing. Throughout this paper, the interdependency between these different kinds of skills is analyzed. For the case of
elementary action skills and coordination skills, methods for inegration of skill application and refinement are developed. It
is shown that this integration has the potential to support long-term learning and autonomous experimentation.
1. Introduction
The complexity of tasks that autonomous manipu-
lation robots as well as autonomous mobile platforms
have to solve is usually tackled through task decom-
position. Here, two characteristic modes of operation
can always be distinguished:
Model-based operation, including path planing or
assembly planning and execution on the base of an
a priori giveri and possibly continuously refined geo-
metrical world model. This incldes also mission plan-
ning, which might be based on a given model of the
world's "semantics".
Reactive operation such as collision avoidance or
compliant motion that involves a direct coupling be-
tween the robot's sen~;ors and its actuators. The next
action of the robot is determined by the current sen-
sor readings - possibly - their history, and the current
goal. These operations will from now on be referred
to as the basic or elementary action skills of the robot.
They are complemented by basic sensing skills that
* Corresponding author. E-mail: kaiser@ira.uka.de.
allow for a targeted use of the robot's sensors in the
framework of plan and mission execution.
As modeling and planning makes only sense down
to a certain level of abstraction, both modes of
operation are usually combined. Then, elementary
skills represent the interface between the planning
and the control level in the robot's architecture. They
also determine the basic operators available for plan-
ning: Only if the robot is able to associate a symbolic
operator with a sequence of actions that are possibly
dependent on its perceptions, i.e., only if the robot
can operationalize the operator by applying a partic-
ular skill, using this operator on the planning level
makes sense [18]. In addition, coordination skills are
required to foster the efficient use of the available
elementary sensing and actions skills.
To realize elementary sensing and action skills re-
qures to map perceptions to actions by means of a
strategy that is goal-oriented. Several possibilities to
encode such a strategy exist (Fig. 1). The "traditional"
approach is the model-based one, which tries to deter-
mine the skill's application conditions a priori and to
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