---
title: "Explore Where It Matters: Targeted Exploration for Efficient Rover Adaptation"
source: "arXiv AI/CL/LG（论文）"
source_tier: "t2"
url: "https://arxiv.org/abs/2610.38657v1"
permalink: "https://feed.astralor.com/items/itm_67af1d038eb8a2568fcc905a"
published: "2026-10-28T18:41:55.000Z"
score: 54
channel: "tech"
tags: ["Explore Where","Matters","Targeted Exploration","Efficient Rover Adaptation","Future","Although"]
---

# Explore Where It Matters: Targeted Exploration for Efficient Rover Adaptation

## 速览

Future planetary rovers will traverse steep, deformable terrain where slip, sinkage, and terrain deformation can threaten mobility. Although simulation can capture some wheel-soil effects, unmodeled deformable-terrain p…

## 关键点

- Future planetary rovers will traverse steep, deformable terrain where slip, sinkage, and terrain deformation can threaten mobility.
- Although simulation can capture some wheel-soil effects, unmodeled deformable-terrain phenomena create sim-to-real gaps requiring deployment-time adaptation.
- Yet, rover operations leave little room for extensive trial-and-error.

## 全文

Future planetary rovers will traverse steep, deformable terrain where slip, sinkage, and terrain deformation can threaten mobility. Although simulation can capture some wheel-soil effects, unmodeled deformable-terrain phenomena create sim-to-real gaps requiring deployment-time adaptation. Yet, rover operations leave little room for extensive trial-and-error. We introduce TERRA (Targeted Exploration for Reward-Relevant Adaptation), an online adaptation framework that efficiently seeks deployment data exposing task-relevant model errors and corrects them. TERRA adapts a simulation-trained world model with a reward-weighted prediction loss and trains a loss predictor to estimate where future performance-relevant errors are likely to occur, using this signal to guide exploration during MPC. In simulation, TERRA reaches approximately 90% slope-climbing success within five trials under severe out-of-distribution pretraining conditions, outperforming exploration baselines in reward, completion time, and energy to first success. On the ERNEST rover, TERRA recovers coordinated active-suspension locomotion on a deformable Mars-simulant slope within three to five real-world trials. Project website: https://terra-explore.github.io

---

引用前请核对原文;本文由星际流动整理:https://feed.astralor.com/items/itm_67af1d038eb8a2568fcc905a