Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Long-Horizon Motion Planning via Sampling and Segmented Trajectory
  Optimization   This paper presents a hybrid robot motion planner that generates long-horizon
motion plans for robot navigation in environments with obstacles. We propose a
hybrid planner, RRT* with segmented trajectory optimization (RRT*-sOpt), which
combines the merits of sampling-based planning, optimization-based planning,
and trajectory splitting to quickly plan for a collision-free and
dynamically-feasible motion plan. When generating a plan, the RRT* layer
quickly samples a semi-optimal path and sets it as an initial reference path.
Then, the sOpt layer splits the reference path and performs optimization on
each segment. It then splits the new trajectory again and repeats the process
until the whole trajectory converges. We also propose to reduce the number of
segments before convergence with the aim of further reducing computation time.
Simulation results show that RRT*-sOpt benefits from the hybrid structure with
trajectory splitting and performs robustly in various robot platforms and
scenarios.

28
The categories of this paper are: alg-geom
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The categories of this paper are: funct-an
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The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
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The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex