83 research outputs found
Task-driven Compression for Collision Encoding based on Depth Images
This paper contributes a novel learning-based method for aggressive
task-driven compression of depth images and their encoding as images tailored
to collision prediction for robotic systems. A novel 3D image processing
methodology is proposed that accounts for the robot's size in order to
appropriately "inflate" the obstacles represented in the depth image and thus
obtain the distance that can be traversed by the robot in a collision-free
manner along any given ray within the camera frustum. Such depth-and-collision
image pairs are used to train a neural network that follows the architecture of
Variational Autoencoders to compress-and-transform the information in the
original depth image to derive a latent representation that encodes the
collision information for the given depth image. We compare our proposed
task-driven encoding method with classical task-agnostic methods and
demonstrate superior performance for the task of collision image prediction
from extremely low-dimensional latent spaces. A set of comparative studies show
that the proposed approach is capable of encoding depth image-and-collision
image tuples from complex scenes with thin obstacles at long distances better
than the classical methods at compression ratios as high as 4050:1.Comment: 14 pages, 5, figures. Accepted to the International Symposium on
Visual Computing 202
Martian Lava Tube Exploration Using Jumping Legged Robots: A Concept Study
In recent years, robotic exploration has become increasingly important in
planetary exploration. One area of particular interest for exploration is
Martian lava tubes, which have several distinct features of interest. First, it
is theorized that they contain more easily accessible resources such as water
ice, needed for in-situ utilization on Mars. Second, lava tubes of significant
size can provide radiation and impact shelter for possible future human
missions to Mars. Third, lava tubes may offer a protected and preserved view
into Mars' geological and possible biological past. However, exploration of
these lava tubes poses significant challenges due to their sheer size,
geometric complexity, uneven terrain, steep slopes, collapsed sections,
significant obstacles, and unstable surfaces. Such challenges may hinder
traditional wheeled rover exploration. To overcome these challenges, legged
robots and particularly jumping systems have been proposed as potential
solutions. Jumping legged robots utilize legs to both walk and jump. This
allows them to traverse uneven terrain and steep slopes more easily compared to
wheeled or tracked systems. In the context of Martian lava tube exploration,
jumping legged robots would be particularly useful due to their ability to jump
over big boulders, gaps, and obstacles, as well as to descend and climb steep
slopes. This would allow them to explore and map such caves, and possibly
collect samples from areas that may otherwise be inaccessible. This paper
presents the specifications, design, capabilities, and possible mission
profiles for state-of-the-art legged robots tailored to space exploration.
Additionally, it presents the design, capabilities, and possible mission
profiles of a new jumping legged robot for Martian lava tube exploration that
is being developed at the Norwegian University of Science and Technology.Comment: 74rd International Astronautical Congress (IAC
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