How Rough Is the Path? Terrain Traversability Estimation for Local and Global Path Planning

地形 运动规划 计算机科学 点云 人工智能 惯性测量装置 卷积神经网络 移动机器人 计算机视觉 机器人 地理 地图学
作者
Gabriel Waibel,Tobias Löw,Mathieu Nass,David Howard,Tirthankar Bandyopadhyay,Paulo Borges
出处
期刊:IEEE Transactions on Intelligent Transportation Systems [Institute of Electrical and Electronics Engineers]
卷期号:23 (9): 16462-16473 被引量:26
标识
DOI:10.1109/tits.2022.3150328
摘要

Perception and interpretation of the terrain is essential for robot navigation, particularly in off-road areas, where terrain characteristics can be highly variable. When planning a path, features such as the terrain gradient and roughness should be considered, and they can jointly represent the traversability cost of the terrain. Despite this range of contributing factors, most cost maps are currently binary in nature, solely indicating traversible versus non-traversible areas. This work presents a joint local and global planning methodology for building continuous cost maps using LIDAR, based on a novel traversability representation of the environment. We investigate two approaches. The first, a statistical approach, computes terrain cost directly from the point cloud. The second, a learning-based approach, predicts an IMU response solely from geometric point cloud data using a 2D-Convolutional-LSTM neural network. This allows us to estimate the cost of a patch without directly driving over it, based on a data set that maps IMU signals to point cloud patches. Based on the terrain analysis, two continuous cost maps are generated to jointly select the optimal path considering distance and traversability cost for local navigation. We present a real-time terrain analysis strategy applicable for local planning, and furthermore demonstrate the straightforward application of the same approach in batch mode for global planning. Off-road autonomous driving experiments in a large and hybrid site illustrate the applicability of the method. We have made the code available online for users to test the method.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
体贴不悔发布了新的文献求助10
刚刚
SYLH应助hauru采纳,获得10
1秒前
2秒前
Lsx完成签到,获得积分10
3秒前
3秒前
4秒前
绿色心情完成签到,获得积分10
5秒前
CodeCraft应助lee采纳,获得10
5秒前
6秒前
7秒前
NexusExplorer应助秋来九月八采纳,获得10
7秒前
M1982发布了新的文献求助10
7秒前
CC完成签到,获得积分10
8秒前
snowpie完成签到 ,获得积分10
8秒前
完美世界应助整齐行云采纳,获得10
8秒前
绿色心情发布了新的文献求助10
9秒前
9秒前
9秒前
充电宝应助OKOK采纳,获得10
9秒前
CipherSage应助大卫戴采纳,获得10
9秒前
充电宝应助124578采纳,获得10
10秒前
归海老四完成签到,获得积分10
10秒前
小二郎应助走路的超人采纳,获得10
10秒前
苔原猫咪甜甜圈完成签到,获得积分10
10秒前
CC发布了新的文献求助10
11秒前
11秒前
11秒前
11秒前
杨YY完成签到,获得积分10
12秒前
12秒前
大个应助知更鸟采纳,获得10
12秒前
天天快乐应助M1982采纳,获得10
13秒前
余顺和发布了新的文献求助10
14秒前
cchen发布了新的文献求助10
14秒前
852应助周周采纳,获得10
16秒前
冷傲冬易发布了新的文献求助10
16秒前
慕青应助2jz采纳,获得10
17秒前
17秒前
17秒前
77发布了新的文献求助10
18秒前
高分求助中
Picture Books with Same-sex Parented Families: Unintentional Censorship 1000
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 310
The Moiseyev Dance Company Tours America: "Wholesome" Comfort during a Cold War 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3980224
求助须知:如何正确求助?哪些是违规求助? 3524191
关于积分的说明 11220260
捐赠科研通 3261653
什么是DOI,文献DOI怎么找? 1800792
邀请新用户注册赠送积分活动 879296
科研通“疑难数据库(出版商)”最低求助积分说明 807232