Robotic behaviors are mainly described by differ- ential equations. Those mathematical models are usually not precise enough because of inaccurately known parameters or model simplifications. Nevertheless, robots are often used in critical contexts as medical or military fields. So, uncertainties in mathematical models have to be taken into account in order to produce reliable and safe analysis results. A framework based on interval analysis is proposed to safely verify and analyze robotic behaviors with bounded uncertainties. It follows an interval constraint programming approach, combined with validated numerical integration methods to deal with differential equations. A case study on robust path planning is presented to emphasize the efficiency of the complete framework.