TORCS Dataset Papers With Code
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Descrição
TORCS (The Open Racing Car Simulator) is a driving simulator. It is capable of simulating the essential elements of vehicular dynamics such as mass, rotational inertia, collision, mechanics of suspensions, links and differentials, friction and aerodynamics. Physics simulation is simplified and is carried out through Euler integration of differential equations at a temporal discretization level of 0.002 seconds. The rendering pipeline is lightweight and based on OpenGL that can be turned off for faster training. TORCS offers a large variety of tracks and cars as free assets. It also provides a number of programmed robot cars with different levels of performance that can be used to benchmark the performance of human players and software driving agents. TORCS was built with the goal of developing Artificial Intelligence for vehicular control and has been used extensively by the machine learning community ever since its inception.
Using Keras and Deep Deterministic Policy Gradient to play TORCS
Frontiers Single Shot Corrective CNN for Anatomically Correct 3D Hand Pose Estimation
Newsletters Papers With Code
TO-Scene: A Large-scale Dataset for Understanding 3D Tabletop Scenes
Drones, Free Full-Text
PDF) The WCCI 2008 simulated car racing competition
PDF] Distributed Approach for implementation of A3C on TORCS
Human-inspired autonomous driving: A survey - ScienceDirect
Imitation Learning
TORCS Dataset Papers With Code
Integrated omics networks reveal the temporal signaling events of brassinosteroid response in Arabidopsis
SUMMIT Dataset Papers With Code
TORCS screen-shot of DRL based lane keeping
BURST Dataset Papers With Code
Sensor Fusion: Gated Recurrent Fusion to Learn Driving Behavior from Temporal Multimodal Data
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