2,424 research outputs found
A Hybrid Controller for Obstacle Avoidance in an n-dimensional Euclidean Space
For a vehicle moving in an -dimensional Euclidean space, we present a
construction of a hybrid feedback that guarantees both global asymptotic
stabilization of a reference position and avoidance of an obstacle
corresponding to a bounded spherical region. The proposed hybrid control
algorithm switches between two modes of operation: stabilization
(motion-to-goal) and avoidance (boundary-following). The geometric construction
of the flow and jump sets of the hybrid controller, exploiting a hysteresis
region, guarantees robust switching (chattering-free) between the stabilization
and avoidance modes. Simulation results illustrate the performance of the
proposed hybrid control approach for a 3-dimensional scenario.Comment: 8 pages, 3 figures, conferenc
On the Construction of Safe Controllable Regions for Affine Systems with Applications to Robotics
This paper studies the problem of constructing in-block controllable (IBC)
regions for affine systems. That is, we are concerned with constructing regions
in the state space of affine systems such that all the states in the interior
of the region are mutually accessible through the region's interior by applying
uniformly bounded inputs. We first show that existing results for checking
in-block controllability on given polytopic regions cannot be easily extended
to address the question of constructing IBC regions. We then explore the
geometry of the problem to provide a computationally efficient algorithm for
constructing IBC regions. We also prove the soundness of the algorithm. We then
use the proposed algorithm to construct safe speed profiles for different
robotic systems, including fully-actuated robots, ground robots modeled as
unicycles with acceleration limits, and unmanned aerial vehicles (UAVs).
Finally, we present several experimental results on UAVs to verify the
effectiveness of the proposed algorithm. For instance, we use the proposed
algorithm for real-time collision avoidance for UAVs.Comment: 17 pages, 18 figures, under review for publication in Automatic
Obstacle Avoidance via Hybrid Feedback
In this paper we present a hybrid feedback approach to solve the navigation
problem of a point mass in the n-dimensional space containing an arbitrary
number of ellipsoidal shape obstacles. The proposed hybrid control algorithm
guarantees both global asymptotic stabilization to a reference and avoidance of
the obstacles. The intuitive idea of the proposed hybrid feedback is to switch
between two modes of control: stabilization and avoidance. The geometric
construction of the flow and jump sets of the proposed hybrid controller,
exploiting hysteresis regions, guarantees Zeno-free switching between the
stabilization and the avoidance modes. Simulation results illustrate the
performance of the proposed hybrid control approach for 2-dimensional and
3-dimensional scenarios
Hybrid Feedback for Autonomous Navigation in Environments with Arbitrary Non-Convex Obstacles
We develop an autonomous navigation algorithm for a robot operating in
two-dimensional environments containing obstacles, with arbitrary non-convex
shapes, which can be in close proximity with each other, as long as there
exists at least one safe path connecting the initial and the target location.
The proposed navigation approach relies on a hybrid feedback to guarantee
global asymptotic stabilization of the robot towards a predefined target
location while ensuring the forward invariance of the obstacle-free workspace.
The proposed hybrid feedback controller guarantees Zeno-free switching between
the move-to-target mode and the obstacle-avoidance mode based on the proximity
of the robot with respect to the obstacle-occupied workspace. An instrumental
transformation that reshapes (virtually) the non-convex obstacles, in a
non-conservative manner, is introduced to facilitate the design of the
obstacle-avoidance strategy. Finally, we provide an algorithmic procedure for
the sensor-based implementation of the proposed hybrid controller and validate
its effectiveness through simulation results.Comment: arXiv admin note: text overlap with arXiv:2111.0938
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Hybrid Control for Robust and Global Tracking on Smooth Manifolds
In this paper, we present a hybrid control strategy that allows for global asymptotic tracking of reference trajectories evolving on smooth manifolds, with nominal robustness. Two different versions of the hybrid controller are presented: One which allows for discontinuities of the plant input and a second one that removes the discontinuities via dynamic extension. By taking an exosystem approach, we provide a general construction of a hybrid controller that guarantees global asymptotic stability of the zero tracking error set. The proposed construction relies on the existence of proper indicators and a transport map-like function for the given manifold. We provide a construction of these functions for the case where each chart in a smooth atlas for the manifold maps its domain onto the Euclidean space. We also provide conditions for exponential convergence to the zero tracking error set. To illustrate these properties, the proposed controller is exercised on three different compact manifolds-the two-dimensional sphere, the unit-quaternion group, and the special orthogonal group of order three- A nd further applied to the problems of obstacle avoidance in the plane and global synchronization on the circle
Forward Stochastic Reachability Analysis for Uncontrolled Linear Systems using Fourier Transforms
We propose a scalable method for forward stochastic reachability analysis for
uncontrolled linear systems with affine disturbance. Our method uses Fourier
transforms to efficiently compute the forward stochastic reach probability
measure (density) and the forward stochastic reach set. This method is
applicable to systems with bounded or unbounded disturbance sets. We also
examine the convexity properties of the forward stochastic reach set and its
probability density. Motivated by the problem of a robot attempting to capture
a stochastically moving, non-adversarial target, we demonstrate our method on
two simple examples. Where traditional approaches provide approximations, our
method provides exact analytical expressions for the densities and probability
of capture.Comment: V3: HSCC 2017 (camera-ready copy), DOI updated, minor changes | V2:
Review comments included | V1: 10 pages, 12 figure
A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES
The work in this thesis is concerned with the development of a novel and practical collision
avoidance system for autonomous underwater vehicles (AUVs). Synergistically,
advanced stochastic motion planning methods, dynamics quantisation approaches,
multivariable tracking controller designs, sonar data processing and workspace representation,
are combined to enhance significantly the survivability of modern AUVs.
The recent proliferation of autonomous AUV deployments for various missions such
as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial
increase in vehicle autonomy. One matching requirement of such missions is
to allow all the AUV to navigate safely in a dynamic and unstructured environment.
Therefore, it is vital that a robust and effective collision avoidance system should be
forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously
increasing its autonomy.
This thesis not only provides a holistic framework but also an arsenal of computational
techniques in the design of a collision avoidance system for AUVs. The
design of an obstacle avoidance system is first addressed. The core paradigm is the
application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly
developed version for use as a motion planning tool. Later, this technique is merged
with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages
of the RRT. A novel multi-node version which can also address time varying
final state is suggested. Clearly, the reference trajectory generated by the aforementioned
embedded planner must be tracked. Hence, the feasibility of employing the
linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent
Ricatti equation (SDRE) controller as trajectory trackers are explored.
The obstacle detection module, which comprises of sonar processing and workspace
representation submodules, is developed and tested on actual sonar data acquired
in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing
techniques applied are fundamentally derived from the image processing perspective.
Likewise, a novel occupancy grid using nonlinear function is proposed for the
workspace representation of the AUV. Results are presented that demonstrate the
ability of an AUV to navigate a complex environment.
To the author's knowledge, it is the first time the above newly developed methodologies
have been applied to an A UV collision avoidance system, and, therefore, it is
considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT
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