Robotic chefs are a promising technology that can improve the availability of quality food by reducing the time required for cooking, therefore decreasing food's overall cost. This paper clarifies and structures design and benchmarking rules in this new area of research, and provides a comprehensive review of technologies suitable for the construction of cooking robots. The diner is an ultimate judge of the cooking outcome, therefore we put focus on explaining human food preferences and perception of taste and ways to use them for control. Mechanical design of robotic chefs at a practically low cost remains the challenge, but some recently published gripper designs as well as whole robotic systems show the use of cheap materials or off‐the‐shelf components. Moreover, technologies like taste sensing, machine learning, and computer vision are making their way into robotic cooking enabling smart sensing and therefore improving controllability and autonomy. Furthermore, objective assessment of taste and food palatability is a challenge even for trained humans, therefore the paper provides a list of procedures for benchmarking the robot's tasting and cooking abilities. The paper is written from the point of view of a researcher or engineer building a practical robotic system, therefore there is a strong priority for solutions and technologies that are proven, robust and self‐contained enough to be a part of a larger system.

中文翻译：

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走向实用的机器人厨师：相关工作回顾和未来挑战

机器人厨师是一项很有前途的技术，它可以通过减少烹饪所需的时间来提高优质食品的可用性，从而降低食品的总体成本。本文阐明并构建了这一新研究领域的设计和基准测试规则，并对适合构建烹饪机器人的技术进行了全面的回顾。用餐者是烹饪结果的最终评判者，因此我们重点解释人类的食物偏好和味道感知以及利用它们进行控制的方法。以实际上较低的成本进行机器人厨师的机械设计仍然是一个挑战，但最近发布的一些夹具设计以及整个机器人系统显示了廉价材料或现成组件的使用。此外，味觉传感、机器学习和计算机视觉等技术正在进入机器人烹饪领域，实现智能传感，从而提高可控性和自主性。此外，即使对于训练有素的人类来说，客观评估味道和食物适口性也是一个挑战，因此本文提供了一系列用于对机器人的品尝和烹饪能力进行基准测试的程序。该论文是从构建实用机器人系统的研究人员或工程师的角度撰写的，因此优先考虑经过验证、稳健且独立的解决方案和技术，足以成为更大系统的一部分。