This paper describes the robot vision track that has been proposed to the ImageCLEF 2010 participants. The track addressed the problem of visual place classification, with a special focus on generalization. Participants were asked to classify rooms and areas of an offce environment on the basis of image sequences captured by a stereo camera mounted on a mobile robot, under varying illumination conditions. The algorithms proposed by the participants had to answer the question "where are you?" (I am in the kitchen, in the corridor, etc) when presented with a test sequence, acquired within the same building but at a different oor than the training sequence. The test data contained images of rooms seen during training, or additional rooms that were not imaged in the training sequence. The participants were asked to solve the problem separately for each test image (obligatory task). Additionally, results could also be reported for algorithms exploiting the temporal continuity of the image sequences (optional task). A total of seven groups partic- ipated to the challenge, with 42 runs submitted to the obligatory task, and 13 submitted to the optional task. The best result in the obligatory task was obtained by the Computer Vision and Geometry Laboratory, ETHZ, Switzerland, with an overall score of 677. The best result in the optional task was obtained by the Idiap Research Institute, Martigny, Switzerland, with an overall score of 2052.