# Small-Scale Zero-Shot Collision Localization for Robots Using RL-CNN
## 1 Introduction
In contrast to the previous scenario, in order to perceive and grasp the objects in a reasonable pose, the contact localization of the end effector to the object is more important. Recent work has attempted to utilize tactile sensors for high-accuracy contact localization [16; 17]. These tactile sensors are often mounted on specific end effectors, such as dexterous hands, U-shaped graspers, etc. Using a dense array arrangement on an extremely small surface area, the contact positioning accuracy of such a method can even reach the sub-millimeter level [16]. Nevertheless, in the scenario where the required contact frequency is high, the contact load is large, or there is an impact load, the sensor is likely to suffer from the memory effect upon making contact, resulting in a decrease in the robustness [18]. In the scenario of the automatic charging of EVs, with the development of automatic driving and automated valet parking (AVP), a large part of the automatic charging of electric vehicles in the future will be carried out in unmanned scenarios. In such an unmanned scenario, there is often no need to pay much attention to whether the robotic arm will threaten the safety of the surrounding people during its operation, and thus, ensuring the safety of the vehicle-robot interaction is more important. In general, in this scenario, for different types of robotic devices, the difficulty in end-effector contact analysis is different. The current charging robots for EVs can be divided into two types: the non-integrated charger type and the integrated charger type. In the non-integrated charger type, the charger and the robot are independent of each other. Before each charging, the robot needs to grab the charger from the charging pile. In the integrated charger type, the charger and the robot are connected, and the grabbing process of the charger can be omitted. Compared to the integrated charger type, using a robot to automatically grab the charger can result in a pose error of the charger. This error not only complicates the charging process but also makes contact analysis more difficult. Thus, the robots currently researched for automatic charging of electric vehicles are mainly charger-integrated [1; 2; 3]. Therefore, this work focuses on the contact problem of the charger-integrated robot. In our previous work, we explored the feasibility of using a supervised learning method to realize collision classification and collision localization for a charger-integrated, cable-driven manipulator when the charger and the charging port are in contact [19]. To alleviate the the mode difficulty during data collection, we designed an mm scale area on the charging port and set pre-specified collision points in this region. Both the training set and the test set are these pre-specified collision points. The difference between the two sets is that the joint configurations, corresponding to the collision points at the same position in the specified region, are different. Using the above method, in order to localize a random collision point in such a region, the pre-specified collision points need to contain the random collision point. This will greatly increase the time needed for data collection in practical applications. In this work, to alleviate this situation, we explore an approach in which the entire region is divided into several sub-regions, and the pre-specified collision points in the sub-regions are used to predict the positions of collision points that have never been seen before. Here, we refer to these collision points that have never been seen before as zero-shot collision points. In the process of data collection, we found that when the central axis of the elastic compensator and the central axis of the end link of the manipulator do not coincide, the vibration caused by the collision between the charger and the upper part of the charging port will have a certain degree of similarity to the vibration caused by the collision between the charger and the lower part of the charging port.