Sensorized Compliant Robot Gripper for Estimating the Cooking Time of Boil-Cooked Vegetables

Towards practical robotic chef: Review of relevant work and future challenges

“…This effect can be achieved in various ways, for example, Hughes et al (2020) proposed a fully pneumatic design, where both actuation and tactile sensing are done using pneumatics. In Figure 1b we see a similar approach, where a gripper with a pneumatic tactile sensor and proprioception is used to measure and assess food readiness (Sochacki, Hughes, et al, 2022). A similar task of assessing mango ripeness was also approached with multiple tactile sensors (Scimeca et al, 2019), with the system shown in Figure 1e.…”

“…Collage of robotic grippers especially useful for food handling and sensing. (a) Sensorized pneumatic gripper handling a potato chip (Hughes et al, 2020), (b) sensorized gripper able to assess cooked‐ness (Sochacki, Hughes, et al, 2022), (c) gripper using conductance measurement to assess ripeness (Almanzor et al, 2022), (d) soft gripper for fruit harvesting (Zhou et al, 2021), (e) tactile feedback to assess mango ripeness (Scimeca et al, 2019), (f) vacuum cup gripper peels lettuce (Hughes et al, 2018), and (g) gripper with chemical sensor at its fingertips (Ciui et al, 2018). …”

“…Boiling can also be modeled using heat transfer equations (Paciulli et al, 2018), as well as traditional ovens (Blikra et al, 2019). A similar model was already used in robotic chefs to predict the required cooking time (Sochacki, Hughes, et al, 2022). We also have some studies that could model the effects of heating type on food healthiness (De Pilli & Alessandrino, 2020; Nandasiri et al, 2023).…”

“…Some progress towards it was made, with models that can generate an image based on a recipe (Zhu et al, 2019). One robotic solution is able to model the effects of boiling on a grasped object (Sochacki, Hughes, et al, 2022) and predict its stiffness after an arbitrary cooking time. Another approach is to have the robot move food around at random or “play” with it to learn its representation (Sawhney et al, 2021).…”

Recognition of Human Chef’s Intentions for Incremental Learning of Cookbook by Robotic Salad Chef

“…tion include peeling lettuce [9], robotic cutting [10], stirfrying [11], tending to food during cooking [12] and in hand assessment of fruit ripeness [13], [14]. New ways of sensing were also implemented, including assessing the state of readiness of a dish [15], using conductance measurement for closed-loop cooking [16], and running various classification tasks with taste and smell sensors eg. classifying wine age [17], detecting mutton adulteration [18], assessing the quality of roasted coffee beans [19], sensing type of milk used for cheese production [20] and judging fish freshness [21].…”