Abstract: A method and device are disclosed for improved object detection in an area surrounding a robot. In the method, first and second sensing data are obtained, which can be assigned to a first or second sensing means of the robot, respectively, and which contain at least one portion of the area surrounding the robot. An objection detection of an object in the area surrounding the robot is carried out using a fusion of at least the first and the second sensing data. An item of redundancy information is generated, which is assigned to the object detection and at least indicates whether the detected object has been detected using only the first or only the second sensing data or whether the detected object or at least one or more sections of same has been detected redundantly using both the first and the second sensing data.

Abstract: A method for managing tracklets in a particle filter estimation framework includes executing a tracklet prediction dependent on a list of previous tracklets, thereby determining persistent tracklets and new tracklets; sampling new measurements for initializing the new tracklets, thereby determining an amount of estimated new tracklets; and determining an amount of the persistent tracklets dependent on the list of previous tracklets. The method further includes determining an amount of the new tracklets and an amount of updated persistent tracklets to be sampled dependent on the amount of estimated new tracklets, the amount of the persistent tracklets, and a memory bound; sampling the updated persistent tracklets from a list of the persistent tracklets dependent on the determined amount of the updated persistent tracklets; and sampling the new tracklets from unassociated measurements dependent on the determined amount of the new tracklets.

Abstract: A method for managing tracklets in a particle filter estimation framework includes executing a tracklet prediction dependent on a list of previous tracklets, thereby determining persistent tracklets and new tracklets; sampling new measurements for initializing the new tracklets, thereby determining an amount of estimated new tracklets; and determining an amount of the persistent tracklets dependent on the list of previous tracklets. The method further includes determining an amount of the new tracklets and an amount of updated persistent tracklets to be sampled dependent on the amount of estimated new tracklets, the amount of the persistent tracklets, and a memory bound; sampling the updated persistent tracklets from a list of the persistent tracklets dependent on the determined amount of the updated persistent tracklets; and sampling the new tracklets from unassociated measurements dependent on the determined amount of the new tracklets.