TY - JOUR
T1 - Overview of Terrain Traversability Evaluation for Autonomous Robots
AU - Shu, Yongjie
AU - Dong, Linwei
AU - Liu, Jianfeng
AU - Liu, Cheng
AU - Wei, Wei
N1 - Publisher Copyright:
© 2024 Wiley Periodicals LLC.
PY - 2024
Y1 - 2024
N2 - Traversability evaluation is the foundation and core of unmanned platforms for scene understanding and autonomous navigation, whose successful completion relies on the analysis of the platform's characteristics and the semantic and geometric features of the surrounding environment. This topic has been reviewed by many literatures, which are characterized by a single perspective and lack comprehensive evaluation frameworks. Thus, the concept and developmental trajectory of traversability evaluation are initially outlined in this paper, distinguishing it from other issues, while constructing an evaluation framework based on two categories: direct assessment and downstream task assessment. Subsequently, traversability evaluation methods are classified based on multiple dimensions, including sensor types, robot types, usage scenarios, and learning approaches. On the basis of the constructed evaluation framework, comparisons are made among existing algorithms in terms of performance and runtime. Subsequently, a summary is provided on commonly used features and their mainstream computation methods in terrain evaluation. Additionally, open-source data sets in this field and projects for scene construction and algorithm validation are compiled and organized. Finally, an analysis is conducted on the development direction and trends, emphasizing the urgent need to establish standardized evaluation systems and comparison baselines. Furthermore, it is imperative that various environmental and platform information be comprehensively integrated into algorithms, while also ensuring that simulation, demonstration, and exploration are incorporated into a unified framework to enhance the robot's learning capability.
AB - Traversability evaluation is the foundation and core of unmanned platforms for scene understanding and autonomous navigation, whose successful completion relies on the analysis of the platform's characteristics and the semantic and geometric features of the surrounding environment. This topic has been reviewed by many literatures, which are characterized by a single perspective and lack comprehensive evaluation frameworks. Thus, the concept and developmental trajectory of traversability evaluation are initially outlined in this paper, distinguishing it from other issues, while constructing an evaluation framework based on two categories: direct assessment and downstream task assessment. Subsequently, traversability evaluation methods are classified based on multiple dimensions, including sensor types, robot types, usage scenarios, and learning approaches. On the basis of the constructed evaluation framework, comparisons are made among existing algorithms in terms of performance and runtime. Subsequently, a summary is provided on commonly used features and their mainstream computation methods in terrain evaluation. Additionally, open-source data sets in this field and projects for scene construction and algorithm validation are compiled and organized. Finally, an analysis is conducted on the development direction and trends, emphasizing the urgent need to establish standardized evaluation systems and comparison baselines. Furthermore, it is imperative that various environmental and platform information be comprehensively integrated into algorithms, while also ensuring that simulation, demonstration, and exploration are incorporated into a unified framework to enhance the robot's learning capability.
KW - autonomous robots
KW - data-driven
KW - learning-based
KW - terrain characterization
KW - traversability evaluation
UR - http://www.scopus.com/inward/record.url?scp=85210151757&partnerID=8YFLogxK
U2 - 10.1002/rob.22461
DO - 10.1002/rob.22461
M3 - Article
AN - SCOPUS:85210151757
SN - 1556-4959
JO - Journal of Field Robotics
JF - Journal of Field Robotics
ER -