Safe navigation of a wall-climbing robot by methods of risk prediction and suitable counteractive measures

Safe navigation on vertical concrete structures is still a great challenge for mobile climbing robots. The main problem is to find the optimum of applicability and safety since these systems have to fulfill certain tasks without endangering persons or their environment. This paper addresses aspects of safe navigation in the range of wall-climbing robots using negative pressure adhesion in combination with a drive system. In this context aspects of the developed robot control architecture will be presented and common hazards for this type of robots are examined. Based on this a risk prediction function is trained via methods of evolutionary algorithms using internal data generated inside of the behavior-based robot control network. Although there will always be a residual risk of a robot dropoff it is shown that the risk could be lowered tremendously by the developed analysis methods and counteractive measures.