Paper Info
Title
Step: Stochastic Traversability Evaluation And Planning For Risk-Aware Off-Road Navigation
Abstract
Although ground robotic autonomy has gained widespread usage in structured and controlled environments, autonomy in unknown and off-road terrain remains a difficult problem. Extreme, off-road, and unstructured environments such as undeveloped wilderness, caves, and rubble pose unique and challenging problems for autonomous navigation. To tackle these problems we propose an approach for assessing traversability and planning a safe, feasible, and fast trajectory in real-time. Our approach, which we name STEP (Stochastic Traversability Evaluation and Planning), relies on: 1) rapid uncertaintyaware mapping and traversability evaluation, 2) tail risk assessment using the Conditional Value-at-Risk (CVaR), and 3) efficient risk and constraint-aware kinodynamic motion planning using sequential quadratic programming-based (SQP) model predictive control (MPC). We analyze our method in simulation and validate its efficacy on wheeled and legged robotic platforms exploring extreme terrains including an abandoned subway and an underground lava tube. (See video: https: //youtu.be/N97cv4eH5c8)
Year
DOI
Venue
2021
10.15607/RSS.2021.XVII.021
ROBOTICS: SCIENCE AND SYSTEM XVII
DocType
ISSN
Citations 
Conference
2330-7668
2
PageRank 
References 
Authors
0.38
0
6
Name
Order
Citations
PageRank
David D. Fan120.72
Kyohei Otsu243.80
Yuki Kubo3178.75
Anushri Dixit420.38
Burdick, J.W.52988516.87
Ali-akbar Agha-mohammadi621.06