We survey research on self-driving cars published in the literature focusing on autonomous cars developed since the DARPA challenges, which are equipped with an autonomy system that can be categorized as SAE level 3 or higher. The architecture of the autonomy system of self-driving cars is typically organized into the perception system and the decision-making system. The perception system is generally divided into many subsystems responsible for tasks such as self-driving-car localization, static obstacles mapping, moving obstacles detection and tracking, road mapping, traffic signalization detection and recognition, among others. The decision-making system is commonly partitioned as well into many subsystems responsible for tasks such as route planning, path planning, behavior selection, motion planning, and control. In this survey, we present the typical architecture of the autonomy system of self-driving cars. We also review research on relevant methods for perception and decision making. Furthermore, we present a detailed description of the architecture of the autonomy system of the self-driving car developed at the Universidade Federal do Espirito Santo (UFES), named Intelligent Autonomous Robotics Automobile (IARA). Finally, we list prominent self-driving car research platforms developed by academia and technology companies, and reported in the media.

Self-driving cars: A survey

We review crane models available in the literature, classify them, and discuss their applications and limitations. A generalized formulation of the most widely used crane model is analyzed using th...

Dynamics and Control of Cranes: A Review:

Virtual reality exposure therapy (VRET) is a promising intervention for the treatment of the anxiety disorders. The main objective of this meta-analysis is to compare the efficacy of VRET, used in a behavioral or cognitive-behavioral framework, with that of the classical evidence-based treatments, in anxiety disorders. A comprehensive search of the literature identified 23 studies (n = 608) that were included in the final analysis. The results show that in the case of anxiety disorders, (1) VRET does far better than the waitlist control; (2) the post-treatment results show similar efficacy between the behavioral and the cognitive behavioral interventions incorporating a virtual reality exposure component and the classical evidence-based interventions, with no virtual reality exposure component; (3) VRET has a powerful real-life impact, similar to that of the classical evidence-based treatments; (4) VRET has a good stability of results over time, similar to that of the classical evidence-based treatments; (5) there is a dose-response relationship for VRET; and (6) there is no difference in the dropout rate between the virtual reality exposure and the in vivo exposure. Implications are discussed.

Virtual reality exposure therapy in anxiety disorders: a quantitative meta-analysis.

After participating in this activity, learners should be better able to:• Evaluate the literature regarding the effectiveness of incorporating virtual reality (VR) in the treatment of psychiatric disorders• Assess the use of exposure-based intervention for anxiety disorders ABSTRACT: Virtual reality (VR) allows users to experience a sense of presence in a computer-generated, three-dimensional environment. Sensory information is delivered through a head-mounted display and specialized interface devices. These devices track head movements so that the movements and images change in a natural way with head motion, allowing for a sense of immersion. VR, which allows for controlled delivery of sensory stimulation via the therapist, is a convenient and cost-effective treatment. This review focuses on the available literature regarding the effectiveness of incorporating VR within the treatment of various psychiatric disorders, with particular attention to exposure-based intervention for anxiety disorders. A systematic literature search was conducted in order to identify studies implementing VR-based treatment for anxiety or other psychiatric disorders. This article reviews the history of the development of VR-based technology and its use within psychiatric treatment, the empirical evidence for VR-based treatment, and the benefits for using VR for psychiatric research and treatment. It also presents recommendations for how to incorporate VR into psychiatric care and discusses future directions for VR-based treatment and clinical research.

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The Use of Virtual Reality Technology in the Treatment of Anxiety and Other Psychiatric Disorders.

Learning new motor tasks from physical interactions is an important goal for both robotics and machine learning. However, when moving beyond basic skills, most monolithic machine learning approaches fail to scale. For more complex skills, methods that are tailored for the domain of skill learning are needed. In this paper, we take the task of learning table tennis as an example and present a new framework that allows a robot to learn cooperative table tennis from physical interaction with a human. The robot first learns a set of elementary table tennis hitting movements from a human table tennis teacher by kinesthetic teach-in, which is compiled into a set of motor primitives represented by dynamical systems. The robot subsequently generalizes these movements to a wider range of situations using our mixture of motor primitives approach. The resulting policy enables the robot to select appropriate motor primitives as well as to generalize between them. Finally, the robot plays with a human table tennis partner and learns online to improve its behavior. We show that the resulting setup is capable of playing table tennis using an anthropomorphic robot arm.

/pdf/learning-to-select-and-generalize-striking-movements-in-2od9fjhno1.pdf

Learning to select and generalize striking movements in robot table tennis

In this paper, a low-cost robot capable of playing ping-pong against human opponent using a vision system to detect the ball is presented. In the subsequent sections, the three main subsystems of the robot, i.e., the vision system, mechanical structure, and the control systems, are described. A prototype has been designed with lightweight and resistant materials to increase the response time and accurateness of the shot. One of the important features of this system is that it uses only one camera to detect the ball, thus reducing the computational time and hardware requirements. To detect the location of the ball, the robot combines the information about the ball and about the shadow it casts on the table. The expert module control defines the game strategy. Orienting the bat in order to return the ball to the desired position on the table does this. In these experiments, the success rate in returning balls was greater than 80%.

Ping-pong player prototype

Obstacle avoidance for a mobile robot: A neuro-fuzzy approach

In this article a new tool for control engineering teaching is presented. The tool was implemented using Java applets and is freely accessible through Web. It allows the analysis and simulation of linear control systems and was created to complement the theoretical lectures in basic control engineering courses. The article is not only centered in the description of the tool but also in the methodology to use it and its evaluation in an electrical engineering degree. Two practical problems are included in the manuscript to illustrate the use of the main functions implemented. The developed web-based tool can be accessed through the link http://www.controlweb.cyc.ull.es. © 2006 Wiley Periodicals, Inc. Comput Appl Eng Educ 14: 178–187, 2006; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20080

A web‐based tool for control engineering teaching

Solving the forward kinematics problem in parallel robots using Support Vector Regression

An accurate method to detect obstacles and dangerous areas is the key to the safe performance of autonomous robots. Time of flight sensors can report their existence through the emission, reflection, and measurement of wave patterns, but large wavelength light projection is often unreliable in outdoors environments, due to solar radiation contamination. In this paper, a specific Microsoft Kinect arrangement on a robotic vehicle is proposed, such that outdoors detection is possible. The main contribution of this paper is the description of a sequence of filtering techniques, which translate the depth image provided by the sensor into definite obstacle projections in the navigability map used by the vehicle. A series of experiments proves that the Kinect device is more accurate at detecting obstacles using this procedure than a camera pair using two different stereovision techniques.

Leopoldo Acosta

Papers

Ping-pong player prototype

Obstacle avoidance for a mobile robot: A neuro-fuzzy approach

A web‐based tool for control engineering teaching

Solving the forward kinematics problem in parallel robots using Support Vector Regression

Using Kinect on an Autonomous Vehicle for Outdoors Obstacle Detection