  Advances in planetary robotics have led to wheeled robots that have beamed
back invaluable science data from the surface of the Moon and Mars. However,
these large wheeled robots are unable to access rugged environments such as
cliffs, canyons and crater walls that contain exposed rock-faces and are
geological time-capsules into the early Moon and Mars. We have proposed the
SphereX robot with a mass of 3 kg, 30 cm diameter that can hop, roll and fly
short distances. A single robot may slip and fall, however, a multirobot system
can work cooperatively by being interlinked using spring-tethers and work much
like a team of mountaineers to systematically climb a slope. We consider a team
of four or more robots that are interlinked with tethers in an 'x'
configuration. Each robot secures itself to a slope using spiny gripping
actuators, and one by one each robot moves upwards by crawling, rolling or
hopping up the slope. In this paper, we present a human devised autonomous
climbing algorithm and evaluate it using a high-fidelity dynamics simulator.
The climbing surfaces contain impassable obstacles and some loosely held rocks
that can dislodge. Under these conditions, the robots need to autonomously map,
plan and navigate up or down these steep environments. Autonomous mapping and
navigation capability is evaluated using simulated lasers, vision sensors. The
human devised planning algorithm uses a new algorithm called bounded-leg A*.
Our early simulation results show much promise in these techniques and our
future plans include demonstration on real robots in a controlled laboratory
environment and outdoors in the canyons of Arizona.
