STEP: Stochastic Traversability Evaluation and Planning for Safe Off-road Navigation

03/04/2021
by   David D. Fan, et al.
0

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 uncertainty-aware 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 underground lava tube.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 4

page 9

page 10

04/26/2020

Online Mapping and Motion Planning under Uncertainty for Safe Navigation in Unknown Environments

Safe autonomous navigation is an essential and challenging problem for r...
07/25/2021

Learning Risk-aware Costmaps for Traversability in Challenging Environments

One of the main challenges in autonomous robotic exploration and navigat...
06/05/2021

Trajectory Optimization of Chance-Constrained Nonlinear Stochastic Systems for Motion Planning and Control

We present gPC-SCP: Generalized Polynomial Chaos-based Sequential Convex...
11/23/2020

Risk-Sensitive Motion Planning using Entropic Value-at-Risk

We consider the problem of risk-sensitive motion planning in the presenc...
03/10/2021

Non-Holonomic RRT MPC: Path and Trajectory Planning for an Autonomous Cycle Rickshaw

This paper presents a novel hierarchical motion planning approach based ...
02/24/2021

Contingency Model Predictive Control for Linear Time-Varying Systems

We present Contingency Model Predictive Control (CMPC), a motion plannin...
02/25/2021

Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain

This paper presents a learning-based approach to consider the effect of ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.