83,683 research outputs found
Towards Full Automated Drive in Urban Environments: A Demonstration in GoMentum Station, California
Each year, millions of motor vehicle traffic accidents all over the world
cause a large number of fatalities, injuries and significant material loss.
Automated Driving (AD) has potential to drastically reduce such accidents. In
this work, we focus on the technical challenges that arise from AD in urban
environments. We present the overall architecture of an AD system and describe
in detail the perception and planning modules. The AD system, built on a
modified Acura RLX, was demonstrated in a course in GoMentum Station in
California. We demonstrated autonomous handling of 4 scenarios: traffic lights,
cross-traffic at intersections, construction zones and pedestrians. The AD
vehicle displayed safe behavior and performed consistently in repeated
demonstrations with slight variations in conditions. Overall, we completed 44
runs, encompassing 110km of automated driving with only 3 cases where the
driver intervened the control of the vehicle, mostly due to error in GPS
positioning. Our demonstration showed that robust and consistent behavior in
urban scenarios is possible, yet more investigation is necessary for full scale
roll-out on public roads.Comment: Accepted to Intelligent Vehicles Conference (IV 2017
Learning Motion Predictors for Smart Wheelchair using Autoregressive Sparse Gaussian Process
Constructing a smart wheelchair on a commercially available powered
wheelchair (PWC) platform avoids a host of seating, mechanical design and
reliability issues but requires methods of predicting and controlling the
motion of a device never intended for robotics. Analog joystick inputs are
subject to black-box transformations which may produce intuitive and adaptable
motion control for human operators, but complicate robotic control approaches;
furthermore, installation of standard axle mounted odometers on a commercial
PWC is difficult. In this work, we present an integrated hardware and software
system for predicting the motion of a commercial PWC platform that does not
require any physical or electronic modification of the chair beyond plugging
into an industry standard auxiliary input port. This system uses an RGB-D
camera and an Arduino interface board to capture motion data, including visual
odometry and joystick signals, via ROS communication. Future motion is
predicted using an autoregressive sparse Gaussian process model. We evaluate
the proposed system on real-world short-term path prediction experiments.
Experimental results demonstrate the system's efficacy when compared to a
baseline neural network model.Comment: The paper has been accepted to the International Conference on
Robotics and Automation (ICRA2018
Developing serious games for cultural heritage: a state-of-the-art review
Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented
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