How Robot Dogs See the Unseeable: Improving Visual Interpretability via Peering for Exploratory Robots

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Bimber, Oliver, von Ellenrieder, Karl Dietrich, Haller, Michael, Nathan, Rakesh John Amala Arokia, Lunardi, Gianni, Youssef, Mohamed, Camurri, Marco, Soto, Santos Miguel Orozco, Niven, Jeremy E.
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866909980802678784
author Bimber, Oliver
von Ellenrieder, Karl Dietrich
Haller, Michael
Nathan, Rakesh John Amala Arokia
Lunardi, Gianni
Youssef, Mohamed
Camurri, Marco
Soto, Santos Miguel Orozco
Niven, Jeremy E.
author_facet Bimber, Oliver
von Ellenrieder, Karl Dietrich
Haller, Michael
Nathan, Rakesh John Amala Arokia
Lunardi, Gianni
Youssef, Mohamed
Camurri, Marco
Soto, Santos Miguel Orozco
Niven, Jeremy E.
contents In vegetated environments, such as forests, exploratory robots play a vital role in navigating complex, cluttered environments where human access is limited and traditional equipment struggles. Visual occlusion from obstacles, such as foliage, can severely obstruct a robot's sensors, impairing scene understanding. We show that "peering", a characteristic side-to-side movement used by insects to overcome their visual limitations, can also allow robots to markedly improve visual reasoning under partial occlusion. This is accomplished by applying core signal processing principles, specifically optical synthetic aperture sensing, together with the vision reasoning capabilities of modern large multimodal models. Peering enables real-time, high-resolution, and wavelength-independent perception, which is crucial for vision-based scene understanding across a wide range of applications. The approach is low-cost and immediately deployable on any camera-equipped robot. We investigated different peering motions and occlusion masking strategies, demonstrating that, unlike peering, state-of-the-art multi-view 3D vision techniques fail in these conditions due to their high susceptibility to occlusion. Our experiments were carried out on an industrial-grade quadrupedal robot. However, the ability to peer is not limited to such platforms, but potentially also applicable to bipedal, hexapod, wheeled, or crawling platforms. Robots that can effectively see through partial occlusion will gain superior perception abilities - including enhanced scene understanding, situational awareness, camouflage breaking, and advanced navigation in complex environments.
format Preprint
id arxiv_https___arxiv_org_abs_2511_16262
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle How Robot Dogs See the Unseeable: Improving Visual Interpretability via Peering for Exploratory Robots
Bimber, Oliver
von Ellenrieder, Karl Dietrich
Haller, Michael
Nathan, Rakesh John Amala Arokia
Lunardi, Gianni
Youssef, Mohamed
Camurri, Marco
Soto, Santos Miguel Orozco
Niven, Jeremy E.
Robotics
Computer Vision and Pattern Recognition
In vegetated environments, such as forests, exploratory robots play a vital role in navigating complex, cluttered environments where human access is limited and traditional equipment struggles. Visual occlusion from obstacles, such as foliage, can severely obstruct a robot's sensors, impairing scene understanding. We show that "peering", a characteristic side-to-side movement used by insects to overcome their visual limitations, can also allow robots to markedly improve visual reasoning under partial occlusion. This is accomplished by applying core signal processing principles, specifically optical synthetic aperture sensing, together with the vision reasoning capabilities of modern large multimodal models. Peering enables real-time, high-resolution, and wavelength-independent perception, which is crucial for vision-based scene understanding across a wide range of applications. The approach is low-cost and immediately deployable on any camera-equipped robot. We investigated different peering motions and occlusion masking strategies, demonstrating that, unlike peering, state-of-the-art multi-view 3D vision techniques fail in these conditions due to their high susceptibility to occlusion. Our experiments were carried out on an industrial-grade quadrupedal robot. However, the ability to peer is not limited to such platforms, but potentially also applicable to bipedal, hexapod, wheeled, or crawling platforms. Robots that can effectively see through partial occlusion will gain superior perception abilities - including enhanced scene understanding, situational awareness, camouflage breaking, and advanced navigation in complex environments.
title How Robot Dogs See the Unseeable: Improving Visual Interpretability via Peering for Exploratory Robots
topic Robotics
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2511.16262