We present the Motion Grammar: an approach to
represent and verify robot control policies based on Context-Free
Grammars. The production rules of the grammar represent a
top-down task decomposition of robot behavior. The terminal
symbols of this language represent sensor readings that are
parsed in real-time. Efficient algorithms for context-free parsing
guarantee that online parsing is computationally tractable. We
analyze verification properties and language constraints of this
linguistic modeling approach, show a linguistic basis that unifies
several existing methods, and demonstrate effectiveness through
experiments on a 14-DOF manipulator interacting with 32 objects
(chess pieces) and an unpredictable human adversary. We provide
many of the algorithms discussed as Open Source, permissively
licensed software. ¹
We demonstrate the automatic transfer of an
assembly task from human to robot. This work extends efforts
showing the utility of linguistic models in verifiable robot
control policies by now performing real visual analysis of
human demonstrations to automatically extract a policy for the
task. This method tokenizes each human demonstration into a
sequence of object connection symbols, then transforms the set
of sequences from all demonstrations into an automaton, which
represents the task-language for assembling a desired object.
Finally, we combine this assembly automaton with a kinematic
model of a robot arm to reproduce the demonstrated task.
Grey, M .X.
Lofaro, Daniel M.
Bobick, Aaron F.
Egerstedt, Magnus B.
Humanoid robots require greater software reliability than traditional mechantronic systems if they are to
perform useful tasks in typical human-oriented environments.
This paper covers a software architecture which distributes the
load of computation and control tasks over multiple processes,
enabling fail-safes within the software. These fail-safes ensure
that unexpected crashes or latency do not produce damaging
behavior in the robot. The distribution also offers benefits for
future software development by making the architecture modular
and extensible. Utilizing a low-latency inter-process communication protocol (Ach), processes are able to communicate with
high control frequencies. The key motivation of this software
architecture is to provide a practical framework for safe and
reliable humanoid robot software development. The authors test
and verify this framework on a HUBO2 Plus humanoid robot.
Christensen, Henrik I.
This work combines semantic maps with hybrid control models, generating a direct link between action and environment models to produce a control
policy for mobile manipulation in unstructured environments. First, we generate
a semantic map for our environment and design a base model of robot action.
Then, we combine this map and action model using the Motion Grammar Calculus to produce a combined robot-environment model. Using this combined model,
we apply supervisory control to produce a policy for the manipulation task. We
demonstrate this approach on a Segway RMP-200 mobile platform.
We present a new Interprocess Communication
(IPC) mechanism and library. Ach is uniquely suited for
coordinating drivers, controllers, and algorithms in complex
robotic systems such as humanoid robots. Ach eliminates the
Head-of-Line Blocking problem for applications that always
require access to the newest message. Ach is efficient, robust,
and formally verified. It has been tested and demonstrated
on a variety of physical robotic systems, and we discuss the
implementation on our humanoid robot Golem Krang. Finally,
the source code for Ach is available under an Open Source