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Open AccessProceedings ArticleDOI

A Simulated Environment for Traversability Estimation Experiments in Field Robotics Applications

TLDR
In this paper, the authors present an environment for simulated experiments in field robotics, and especially in experiments on estimating the traversability of foliage and other objects that appear as obstacles but that can be overcome by the robot without circumventing them.
Abstract
We present an environment for simulated experiments in field robotics, and especially in experiments on estimating the traversability of foliage and other objects that appear as obstacles but that can be overcome by the robot without circumventing them. The simulated environment is developed in the Unity real-time development platform, integrated with the ROS middleware. In the preliminary experiments presented here, we demonstrate that our environment is able to simulate the sensory input needed in order to train supervised traversability estimation models.

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Proceedings ArticleDOI

Breaking the O(√ n)-Bit Barrier: Byzantine Agreement with Polylog Bits Per Party

TL;DR: In this paper, a cryptographic primitive called succinctly reconstructed distributed signatures (SRDS) was defined for constructing O(1) balanced Byzantine agreement protocols with O( √ n) bits per party.
References
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Proceedings ArticleDOI

Design and use paradigms for Gazebo, an open-source multi-robot simulator

TL;DR: Gazebo is designed to fill this niche by creating a 3D dynamic multi-robot environment capable of recreating the complex worlds that would be encountered by the next generation of mobile robots.
Proceedings ArticleDOI

Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping

TL;DR: In this paper, the authors study how randomized simulated environments and domain adaptation methods can be extended to train a grasping system to grasp novel objects from raw monocular RGB images, and they extensively evaluate their approaches with a total of more than 25,000 physical test grasps, including a novel extension of pixel-level domain adaptation that they termed the GraspGAN.
Journal ArticleDOI

A behavior-based system for off-road navigation

TL;DR: A core system for autonomous navigation in outdoor natural terrain consists of a perception module that processes range images to identify untraversable regions of the terrain, a local map management module that maintains a representation of the environment in the vicinity of the vehicle, and a planning module that issues commands to the vehicle controller.
Proceedings ArticleDOI

Navigation planning for legged robots in challenging terrain

TL;DR: This paper presents a framework for planning safe and efficient paths for a legged robot in rough and unstructured terrain, integrated on the quadrupedal robot StarlETH and extensively tested in simulation as well as on the real platform.
Journal ArticleDOI

Learning Ground Traversability From Simulations

TL;DR: In this article, a convolutional neural network is trained for a specific robot model (wheeled, tracked, legged, snake-like) using simulation data on procedurally generated training terrains; the trained classifier can be applied to unseen large heightmaps to yield oriented traversability maps, and then plan traversable paths.
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