13,150 research outputs found
Barrier Functions in Cascaded Controller: Safe Quadrotor Control
Safe control for inherently unstable systems such as quadrotors is crucial.
Imposing multiple dynamic constraints simultaneously on the states for safety
regulation can be a challenging problem. In this paper, we propose a quadratic
programming (QP) based approach on a cascaded control architecture for
quadrotors to enforce safety. Safety regions are constructed using control
barrier functions (CBF) while explicitly considering the nonlinear
underactuated dynamics of the quadrotor. The safety regions constructed using
CBFs establish a non-conservative forward invariant safe region for quadrotor
navigation. Barriers imposed across the cascaded architecture allows
independent safety regulation in quadrotor's altitude and lateral domains.
Despite barriers appearing in a cascaded fashion, we show preservation of
safety for quadrotor motion in SE(3). We demonstrate the feasibility of our
method on a quadrotor in simulation with static and dynamic constraints
enforced on position and velocity spaces simultaneously.Comment: Submitted to ACC 2020, 8 pages, 7 figure
Feedback MPC for Torque-Controlled Legged Robots
The computational power of mobile robots is currently insufficient to achieve
torque level whole-body Model Predictive Control (MPC) at the update rates
required for complex dynamic systems such as legged robots. This problem is
commonly circumvented by using a fast tracking controller to compensate for
model errors between updates. In this work, we show that the feedback policy
from a Differential Dynamic Programming (DDP) based MPC algorithm is a viable
alternative to bridge the gap between the low MPC update rate and the actuation
command rate. We propose to augment the DDP approach with a relaxed barrier
function to address inequality constraints arising from the friction cone. A
frequency-dependent cost function is used to reduce the sensitivity to
high-frequency model errors and actuator bandwidth limits. We demonstrate that
our approach can find stable locomotion policies for the torque-controlled
quadruped, ANYmal, both in simulation and on hardware.Comment: Paper accepted to IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS 2019
Safety Control Synthesis with Input Limits: a Hybrid Approach
We introduce a hybrid (discrete--continuous) safety controller which enforces
strict state and input constraints on a system---but only acts when necessary,
preserving transparent operation of the original system within some safe region
of the state space. We define this space using a Min-Quadratic Barrier
function, which we construct along the equilibrium manifold using the Lyapunov
functions which result from linear matrix inequality controller synthesis for
locally valid uncertain linearizations. We also introduce the concept of a
barrier pair, which makes it easy to extend the approach to include
trajectory-based augmentations to the safe region, in the style of LQR-Trees.
We demonstrate our controller and barrier pair synthesis method in
simulation-based examples.Comment: 6 pages, 7 figures. Accepted for publication at the 2018 American
Controls Conference. Copyright IEEE 201
Minimum-time trajectory generation for quadrotors in constrained environments
In this paper, we present a novel strategy to compute minimum-time
trajectories for quadrotors in constrained environments. In particular, we
consider the motion in a given flying region with obstacles and take into
account the physical limitations of the vehicle. Instead of approaching the
optimization problem in its standard time-parameterized formulation, the
proposed strategy is based on an appealing re-formulation. Transverse
coordinates, expressing the distance from a frame path, are used to
parameterise the vehicle position and a spatial parameter is used as
independent variable. This re-formulation allows us to (i) obtain a fixed
horizon problem and (ii) easily formulate (fairly complex) position
constraints. The effectiveness of the proposed strategy is proven by numerical
computations on two different illustrative scenarios. Moreover, the optimal
trajectory generated in the second scenario is experimentally executed with a
real nano-quadrotor in order to show its feasibility.Comment: arXiv admin note: text overlap with arXiv:1702.0427
On-line Joint Limit Avoidance for Torque Controlled Robots by Joint Space Parametrization
This paper proposes control laws ensuring the stabilization of a time-varying
desired joint trajectory, as well as joint limit avoidance, in the case of
fully-actuated manipulators. The key idea is to perform a parametrization of
the feasible joint space in terms of exogenous states. It follows that the
control of these states allows for joint limit avoidance. One of the main
outcomes of this paper is that position terms in control laws are replaced by
parametrized terms, where joint limits must be avoided. Stability and
convergence of time-varying reference trajectories obtained with the proposed
method are demonstrated to be in the sense of Lyapunov. The introduced control
laws are verified by carrying out experiments on two degrees-of-freedom of the
humanoid robot iCub.Comment: 8 pages, 4 figures. Submitted to the 2016 IEEE-RAS International
Conference on Humanoid Robot
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