2.5D Mapping, Pathfinding and Path Following For Navigation Of A Differential Drive Robot In Uneven Terrain

TL;DR

This paper presents a 2.5D navigation system for differential drive robots that integrates elevation mapping, path planning, and local path following with obstacle avoidance, using MPPI control adapted for uneven terrain.

Contribution

It introduces novel cost-functions for MPPI to handle elevation maps and uneven terrain, enhancing navigation capabilities in challenging environments.

Findings

System successfully navigates uneven terrains in simulations.

Effective obstacle avoidance demonstrated in synthetic tests.

MPPI adaptation improves path following on rough surfaces.

Abstract

Safe navigation in uneven terrains is an important problem in robotic research. In this paper we propose a 2.5D navigation system which consists of elevation map building, path planning and local path following with obstacle avoidance. For local path following we use Model Predictive Path Integral (MPPI) control method. We propose novel cost-functions for MPPI in order to adapt it to elevation maps and motion through unevenness. We evaluate our system on multiple synthetic tests and in a simulated environment with different types of obstacles and rough surfaces.