EXOT: Exit-aware Object Tracker for Safe Robotic Manipulation of Moving Object

Current robotic hand manipulation narrowly operates with objects in predictable positions in limited environments. Thus, when the location of the target object deviates severely from the expected location, a robot sometimes responds in an unexpected way, especially when it operates with a human. For safe robot operation, we propose the EXit-aware Object Tracker (EXOT) on a robot hand camera that recognizes an object's absence during manipulation. The robot decides whether to proceed by examining the tracker's bounding box output containing the target object. We adopt an out-of-distribution classifier for more accurate object recognition since trackers can mistrack a background as a target object. To the best of our knowledge, our method is the first approach of applying an out-of-distribution classification technique to a tracker output. We evaluate our method on the first-person video benchmark dataset, TREK-150, and on the custom dataset, RMOT-223, that we collect from the UR5e robot. Then we test our tracker on the UR5e robot in real-time with a conveyor-belt sushi task, to examine the tracker's ability to track target dishes and to determine the exit status. Our tracker shows 38% higher exit-aware performance than a baseline method. The dataset and the code will be released at https://github.com/hskAlena/EXOT.Comment: 2023 IEEE International Conference on Robotics and Automation (ICRA

Design of Single-modal Take-over Request in SAE Level 2 & 3 Automated Vehicle

Recently, cutting-edge technology has led to the development of automated vehicles, but the limitations of the related technology may lead to hazardous situations. This resulted in the remarkable significance of the interaction between automated vehicles and drivers. In particular, the transition between the driver and the automated vehicle in accordance with Level 3 of SAE J3016 is inevitable, and guidelines or standards regarding the takeover should be provided. Therefore, we aim to prepare the safety guidelines for the takeover and to conduct a comparative test. First, guidelines for visual, auditory, and haptic displays in existing vehicles were examined. Second, preliminary research was conducted on the modality of automated vehicles. Third, we carried out a modality investigation regarding the partially automated vehicle. Based on this, we proposed visual, auditory, and haptic signals for each modality. This will serve as a significant starting point for future research based on multimodal methods

Visualization and Quantification of MicroRNA in a Single Cell Using Atomic Force Microscopy

MicroRNAs (miRNAs) play critical roles in controlling various cellular processes, and the expression levels of individual miRNAs can be considerably altered in pathological conditions such as cancer. Accurate quantification of miRNA at the single-cell level will lead to a better understanding of miRNA function. Here, we present a direct and sensitive method for miRNA detection using atomic force microscopy (AFM). A hybrid binding domain (HBD)-tethered tip enabled mature miRNAs, but not premature miRNAs, to be located individually on an adhesion force map. By scanning several sections of a micrometer-sized DNA spot, we were able to quantify the copy number of miR-134 in a single neuron and demonstrate that the expression was increased upon cell activation. Moreover, we visualized individual miR-134s on fixed neurons after membrane removal and observed 2–4 miR-134s in the area of 1.0 × 1.0 μm² of soma. The number increased to 8–14 in stimulated neurons, and this change matches the ensemble-averaged increase in copy number. These findings indicate that miRNAs can be reliably quantified at the single cell level with AFM and that their distribution can be mapped at nanometric lateral resolution without modification or amplification. Furthermore, the analysis of miRNAs, mRNAs, and proteins in the same sample or region by scanning sequentially with different AFM tips would let us accurately understand the post-transcriptional regulation of biological processes