1,538 research outputs found
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
PAMPC: Perception-Aware Model Predictive Control for Quadrotors
We present the first perception-aware model predictive control framework for
quadrotors that unifies control and planning with respect to action and
perception objectives. Our framework leverages numerical optimization to
compute trajectories that satisfy the system dynamics and require control
inputs within the limits of the platform. Simultaneously, it optimizes
perception objectives for robust and reliable sens- ing by maximizing the
visibility of a point of interest and minimizing its velocity in the image
plane. Considering both perception and action objectives for motion planning
and control is challenging due to the possible conflicts arising from their
respective requirements. For example, for a quadrotor to track a reference
trajectory, it needs to rotate to align its thrust with the direction of the
desired acceleration. However, the perception objective might require to
minimize such rotation to maximize the visibility of a point of interest. A
model-based optimization framework, able to consider both perception and action
objectives and couple them through the system dynamics, is therefore necessary.
Our perception-aware model predictive control framework works in a
receding-horizon fashion by iteratively solving a non-linear optimization
problem. It is capable of running in real-time, fully onboard our lightweight,
small-scale quadrotor using a low-power ARM computer, to- gether with a
visual-inertial odometry pipeline. We validate our approach in experiments
demonstrating (I) the contradiction between perception and action objectives,
and (II) improved behavior in extremely challenging lighting conditions
Topology-Guided Path Integral Approach for Stochastic Optimal Control in Cluttered Environment
This paper addresses planning and control of robot motion under uncertainty
that is formulated as a continuous-time, continuous-space stochastic optimal
control problem, by developing a topology-guided path integral control method.
The path integral control framework, which forms the backbone of the proposed
method, re-writes the Hamilton-Jacobi-Bellman equation as a statistical
inference problem; the resulting inference problem is solved by a sampling
procedure that computes the distribution of controlled trajectories around the
trajectory by the passive dynamics. For motion control of robots in a highly
cluttered environment, however, this sampling can easily be trapped in a local
minimum unless the sample size is very large, since the global optimality of
local minima depends on the degree of uncertainty. Thus, a homology-embedded
sampling-based planner that identifies many (potentially) local-minimum
trajectories in different homology classes is developed to aid the sampling
process. In combination with a receding-horizon fashion of the optimal control
the proposed method produces a dynamically feasible and collision-free motion
plans without being trapped in a local minimum. Numerical examples on a
synthetic toy problem and on quadrotor control in a complex obstacle field
demonstrate the validity of the proposed method.Comment: arXiv admin note: text overlap with arXiv:1510.0534
Differential-Flatness and Control of Quadrotor(s) with a Payload Suspended through Flexible Cable(s)
We present the coordinate-free dynamics of three different quadrotor systems
: (a) single quadrotor with a point-mass payload suspended through a flexible
cable; (b) multiple quadrotors with a shared point-mass payload suspended
through flexible cables; and (c) multiple quadrotors with a shared rigid-body
payload suspended through flexible cables. We model the flexible cable(s) as a
finite series of links with spherical joints with mass concentrated at the end
of each link. The resulting systems are thus high-dimensional with high
degree-of-underactuation. For each of these systems, we show that the dynamics
are differentially-flat, enabling planning of dynamically feasible
trajectories. For the single quadrotor with a point-mass payload suspended
through a flexible cable with five links (16 degrees-of-freedom and 12
degrees-of-underactuation), we use the coordinate-free dynamics to develop a
geometric variation-based linearized equations of motion about a desired
trajectory. We show that a finite-horizon linear quadratic regulator can be
used to track a desired trajectory with a relatively large region of
attraction
A survey on fractional order control techniques for unmanned aerial and ground vehicles
In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade
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