13,959 research outputs found
Priority-based intersection management with kinodynamic constraints
We consider the problem of coordinating a collection of robots at an
intersection area taking into account dynamical constraints due to actuator
limitations. We adopt the coordination space approach, which is standard in
multiple robot motion planning. Assuming the priorities between robots are
assigned in advance and the existence of a collision-free trajectory respecting
those priorities, we propose a provably safe trajectory planner satisfying
kinodynamic constraints. The algorithm is shown to run in real time and to
return safe (collision-free) trajectories. Simulation results on synthetic data
illustrate the benefits of the approach.Comment: to be presented at ECC2014; 6 page
Fine-grained acceleration control for autonomous intersection management using deep reinforcement learning
Recent advances in combining deep learning and Reinforcement Learning have
shown a promising path for designing new control agents that can learn optimal
policies for challenging control tasks. These new methods address the main
limitations of conventional Reinforcement Learning methods such as customized
feature engineering and small action/state space dimension requirements. In
this paper, we leverage one of the state-of-the-art Reinforcement Learning
methods, known as Trust Region Policy Optimization, to tackle intersection
management for autonomous vehicles. We show that using this method, we can
perform fine-grained acceleration control of autonomous vehicles in a grid
street plan to achieve a global design objective.Comment: Accepted in IEEE Smart World Congress 201
On the Complexity of an Unregulated Traffic Crossing
The steady development of motor vehicle technology will enable cars of the
near future to assume an ever increasing role in the decision making and
control of the vehicle itself. In the foreseeable future, cars will have the
ability to communicate with one another in order to better coordinate their
motion. This motivates a number of interesting algorithmic problems. One of the
most challenging aspects of traffic coordination involves traffic
intersections. In this paper we consider two formulations of a simple and
fundamental geometric optimization problem involving coordinating the motion of
vehicles through an intersection.
We are given a set of vehicles in the plane, each modeled as a unit
length line segment that moves monotonically, either horizontally or
vertically, subject to a maximum speed limit. Each vehicle is described by a
start and goal position and a start time and deadline. The question is whether,
subject to the speed limit, there exists a collision-free motion plan so that
each vehicle travels from its start position to its goal position prior to its
deadline.
We present three results. We begin by showing that this problem is
NP-complete with a reduction from 3-SAT. Second, we consider a constrained
version in which cars traveling horizontally can alter their speeds while cars
traveling vertically cannot. We present a simple algorithm that solves this
problem in time. Finally, we provide a solution to the discrete
version of the problem and prove its asymptotic optimality in terms of the
maximum delay of a vehicle
Adaptive Path Planning for Depth Constrained Bathymetric Mapping with an Autonomous Surface Vessel
This paper describes the design, implementation and testing of a suite of
algorithms to enable depth constrained autonomous bathymetric (underwater
topography) mapping by an Autonomous Surface Vessel (ASV). Given a target depth
and a bounding polygon, the ASV will find and follow the intersection of the
bounding polygon and the depth contour as modeled online with a Gaussian
Process (GP). This intersection, once mapped, will then be used as a boundary
within which a path will be planned for coverage to build a map of the
Bathymetry. Methods for sequential updates to GP's are described allowing
online fitting, prediction and hyper-parameter optimisation on a small embedded
PC. New algorithms are introduced for the partitioning of convex polygons to
allow efficient path planning for coverage. These algorithms are tested both in
simulation and in the field with a small twin hull differential thrust vessel
built for the task.Comment: 21 pages, 9 Figures, 1 Table. Submitted to The Journal of Field
Robotic
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