Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Composable Behavior Embeddings for Long-horizon Visual
  Navigation   Learning high-level navigation behaviors has important implications: it
enables robots to build compact visual memory for repeating demonstrations and
to build sparse topological maps for planning in novel environments. Existing
approaches only learn discrete, short-horizon behaviors. These standalone
behaviors usually assume a discrete action space with simple robot dynamics,
thus they cannot capture the intricacy and complexity of real-world
trajectories. To this end, we propose Composable Behavior Embedding (CBE), a
continuous behavior representation for long-horizon visual navigation. CBE is
learned in an end-to-end fashion; it effectively captures path geometry and is
robust to unseen obstacles. We show that CBE can be used to performing
memory-efficient path following and topological mapping, saving more than an
order of magnitude of memory than behavior-less approaches.

35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
16
The categories of this paper are: stat