Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction

The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with humans, it is crucial that they have a deep understanding of the environment in which they operate. In particular, the ability to predict traversability and detect tactile information is crucial for enhancing the safety and efficiency of human-robot interactions.
To address this challenge, this paper proposes a method called "Feel the Point Clouds" that use point clouds to predict traversability and detect tactile terrain information for a tracked rescue robot. This information can be used to adjust the robot's behavior and movements in real-time, allowing it to interact with the environment in a more intuitive and safe manner.
The experimental results of the proposed method are evaluated in various scenarios and demonstrate its effectiveness in improving human-robot interaction and visualization for a more accurate and intuitive understanding of the environment.