Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Stochastic and Robust MPC for Bipedal Locomotion: A Comparative Study on
  Robustness and Performance   Linear Model Predictive Control (MPC) has been successfully used for
generating feasible walking motions for humanoid robots. However, the effect of
uncertainties on constraints satisfaction has only been studied using Robust
MPC (RMPC) approaches, which account for the worst-case realization of bounded
disturbances at each time instant. In this letter, we propose for the first
time to use linear stochastic MPC (SMPC) to account for uncertainties in
bipedal walking. We show that SMPC offers more flexibility to the user (or a
high level decision maker) by tolerating small (user-defined) probabilities of
constraint violation. Therefore, SMPC can be tuned to achieve a constraint
satisfaction probability that is arbitrarily close to 100\%, but without
sacrificing performance as much as tube-based RMPC. We compare SMPC against
RMPC in terms of robustness (constraint satisfaction) and performance
(optimality). Our results highlight the benefits of SMPC and its interest for
the robotics community as a powerful mathematical tool for dealing with
uncertainties.

13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
7
The categories of this paper are: hep-th
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph