A framework of physically interactive parameter estimation based on active environmental groping for safe disaster response work

Abstract Disaster response robots are expected to perform complicated tasks such as traveling over unstable terrain, climbing slippery steps, and removing heavy debris. To complete safely, the must obtain not only visual-perceptual information (VPI) surface shape but also haptic-perceptual (HPI) friction of objects in environments. VPI can be obtained from laser sensors cameras. In contrast, HPI basically results physical interaction with environments, e.g., reaction force deformation. However, current do have a function estimate HPI. this study, we propose framework physically interactive parameters (PIPs), including hardness, friction, weight, which vital for safe robot-environment interaction. For effective estimation, define ground (GGM) object groping modes (OGM). The endpoint robot arm, has sensor, actively touches, pushes, rubs, lifts environment hybrid position/force control, three kinds PIPs estimated measured displacement arm endpoint. finally judges accident risk based on PIPs, safe, attentional, or dangerous. We prepared environments that had same different weight. experimental indicated proposed could adequately was useful judge safely plan tasks.