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给人留下了深刻印象,这一点在试图以自主机器人的类似熟练程度制定解决方案时就更加明显了。虽然在人工视觉和触摸技术方面取得了显著的进步,但在机器人应用中的这两种感知模式的有效整合方面仍有待改进,还存在一些公开的挑战。从人类如何结合视觉和机智感知来感知物体特性和推动执行手工任务的角度,这一条总结了机器人对视觉和机能物体感知的当前水平。首先,概述了人类多式物体感知的生物基础。然后,讨论了机器人感知技术和数据收集战略的最新进展。接着,介绍了主要计算技术的概况,重点介绍了多式机器学习的主要挑战,并在机器人物体识别、近况和公开挑战的介绍中提出了几篇具有代表性的文章。最后,根据最新进展和公开挑战,这一条概述了有希望的新研究方向。</s>