The object perception capabilities of humans are impressive, and this becomes even more evident when trying to develop solutions with a similar proficiency in autonomous robots. While there have been notable advancements in the technologies for artificial vision and touch, the effective integration of these two sensory modalities in robotic applications still needs to be improved, and several open challenges exist. Taking inspiration from how humans combine visual and haptic perception to perceive object properties and drive the execution of manual tasks, this article summarises the current state of the art of visuo-haptic object perception in robots. Firstly, the biological basis of human multimodal object perception is outlined. Then, the latest advances in sensing technologies and data collection strategies for robots are discussed. Next, an overview of the main computational techniques is presented, highlighting the main challenges of multimodal machine learning and presenting a few representative articles in the areas of robotic object recognition, peripersonal space representation and manipulation. Finally, informed by the latest advancements and open challenges, this article outlines promising new research directions.

翻译：人类的物体感知能力令人印象深刻，在试图为自主机器人开发具有类似熟练度的解决方案时，这一点尤为突出。尽管人工视觉和触觉技术已取得显著进展，但这两种感官模式在机器人应用中的有效集成仍有待提升，且存在若干开放性挑战。受人类如何结合视觉和触觉感知来识别物体属性并驱动手部任务执行的启发，本文总结了机器人中视觉-触觉物体感知的当前最新技术。首先，概述了人类多模态物体感知的生物学基础。接着，讨论了机器人传感技术和数据收集策略的最新进展。然后，介绍了主要计算技术的概览，强调了多模态机器学习的主要挑战，并展示了机器人物体识别、近体空间表征和操作领域中的几篇代表性文章。最后，基于最新进展和开放性挑战，本文概述了有前景的新研究方向。