Simply: grasp!

抓取是机器人技术中的一项重大挑战。如何拾取由不同材料和形状制成的物体，对于真正揭示机器人帮助人类工作和日常生活活动的潜力至关重要。尽管许多人希望具有先进拾取放置能力的家用机器人能够例如卸下洗碗机，但工业将从创新的抓取解决方案中受益匪浅，这些解决方案能够自动挑选和分类仓库、工厂和商店中不同形状和材料的物品。 基于视觉的机器人抓取系统已经有了大量的研究成果。主要的重点一直是识别目标的位置和方向，即要抓住的对象。研究还侧重于根据当前抓取器的具体限制在给定目标上寻找最佳抓取位置。此外，研究还研究了如何最好地识别最佳机械手轨迹，以精确地重新定位抓取器，因为目前商业上可用的抓取器需要精确定位以抓取。 虽然在上述方面已经取得了很大的进展，但机器人抓取在实践中往往仍然不成功。事实上，目前可用的商业抓手往往根本无法抓取不同形状和不同材料制成的目标。此外，基于视觉的系统可能无法在真实世界环境(如房子)中提供目标的精确定位，这使得当前需要的决定如何最好地定位抓取器的过程非常具有挑战性。因此，这项研究计划旨在产生创新的抓取解决方案，这种解决方案需要最小的重新定向来抓取目标，并且能够抓取不同形状和材料的大多数目标，即使在有关它们的信息(例如方向)很少的情况下也是如此。 这项研究有可能有助于在我们的社会中更广泛地采用机器人技术，并帮助经济增长。一种能够抓取大多数物体的抓取解决方案有可能使机器人抓取发生变革性的变化。这一研究计划的结果，如果与最先进的视觉引导灵巧机器人操作器相结合，可以帮助电子商务和其他企业显著提高工厂自动化和我们行业的经济增长。掌握在几乎没有关于目标的信息时也有效的解决方案，有可能使新的行业能够在其设施中使用机器人，即使在照明条件较差和存在遮挡的情况下也是如此。此外，抓取解决方案只需要最小的重新定位，将使负担得起的机械手的广泛使用，由廉价的摄像头引导的几个自由度。这些低成本的机器人系统预计将在我们的社会产生强大的影响，因为在许多工业应用中，成本是进入市场的主要障碍。它们也有很强的潜力，可以在我们的家庭中找到未来的日常用途。

Grasping is a grand challenge in robotics. How to pick up objects made of different materials and shapes is of the utmost importance to truly unveil the potential of robotics for assisting humans in work and daily living activities. While many would like domestic robots with advanced pick-and-place capabilities to, for instance, unload their dishwasher, industry would highly benefit from innovative grasping solutions able to automatically pick and sort items of different shapes and materials in their warehouses, plants and stores. There is a wealth of prolific research on vision-based systems for robotic grasping. A primary focus has been on identifying the position and orientation of the target, i.e. the object to be grasped. Research also focused on finding optimal grasping locations on a given target based on the specific constraints of current grippers. Research additionally investigated how to best identify optimal manipulator trajectories to precisely reorient grippers, as current commercially available grippers require to be precisely oriented to grasp. While much progress has been made on the above-mentioned aspects, robotic grasping is often still unsuccessful in practice. In fact, currently available commercial grippers often simply cannot grasp targets with different shapes and made of different materials. Additionally, vision-based systems may fail to provide a target's precise orientation in real-world environments, such as a house, making the currently needed process of deciding how to best orient the gripper very challenging. This research program therefore aims at generating innovative grasping solutions which require minimal reorientation to grasp targets and are able to grasp most targets of different shapes and materials, even when little information about them (e.g. orientation) is available. This research has the potential to contribute to the wider adoption of robotics in our society and assist with economic growth. A grasping solution enabling most objects to be grasped has the potential to make a transformative change in robotic grasping. Results of this research program, when paired with state-of-the-art vision-guided dexterous robotic manipulators, could help e-commerce and other businesses to dramatically improve plant automatization and economic growth of our industry. Grasping solutions that are also effective when little information about the target is available have the potential to enable new industries to use robots in their facilities, even in poor lighting conditions and in the presence of occlusions. Additionally, grasping solutions requiring only minimal reorientation will enable the extensive use of affordable manipulators with few degrees of freedom guided by inexpensive cameras. These low-cost robotic systems are expected to make a strong impact in our society, as cost is a primary barrier to entry in many industrial applications. They also have a strong potential to find future daily use in our homes.