\section{Conclusions}
  \label{sec:concls}

This article has presented a robotic system to control the six-legged
Ambler planetary rover.  The approach presented here integrates perception,
planning, real-time control and task-level control to reliably and
autonomously navigate the Ambler long distances over rugged terrain.  These
are capabilities that are essential for operating in remote, natural
environments, such as on Mars.

\begin{itemize}

\item Self-reliant control: the rover must depend on its own resources for
planning, taking actions, and maintaining its safety and integrity.

\item Limited power: the rover must carry its own power source, forcing it
to make energy efficient moves.

\item Rugged terrain traversal: the rover must be capable of traversing a
wide variety of terrain, to get to points of geologic interest.

\end{itemize}

These challenges have influenced our approach to the problem.  In
particular, the resultant system is quite deliberative, where actions are
highly goal-directed, steps are planned out in advance using explicit
models of the terrain and the vehicle's kinematics and geometry, and moves
are checked multiple times by different modules for safety prior to
execution.  We believe that this approach to walking is well-suited to
meeting the three challenges stated above.  For reasons of reliability, we
want the robot to avoid making potentially hazardous moves; for reasons of
efficiency, we want the robot to take steps that minimize transfer of
energy to the environment and maximize progress along the prescribed path;
for reasons of rugged terrain traversal, we desire that the robot
accurately perceive its environment and take it into account when walking.

This approach carries a price, however: it is both computationally and
perceptually intensive.  For the Ambler, this is not a problem.  Since the
mechanism is inherently quite slow (for reasons of power efficiency
\cite{Bares92ijrr}), the system has sufficient time to perceive and plan
while the controller concurrently executes steps.  For faster robot
mechanisms, there is a tradeoff to be made.  In general, we would advocate
our deliberative approach to walking for applications in which reliability
and safety are more important than speed, and/or if the mechanism will
typically be operating in fairly rugged or hazardous environments.

The research reported here is continuing.  We are striving to increase the
range and reliability of autonomous walking systems by including more
monitoring and error recovery strategies in both the low-level controller
and higher-level planners.  We are also extending system autonomy to higher
levels of cognition, including route planning and global navigation, and
are trying to better characterize our perception, planning and task-level
control algorithms.  The aim is to produce a walking system capable of
multi-kilometer, multi-day unattended operation in rugged, natural
environments, whether on Earth or on other planets.
