  In the upcoming sixth generation (6G) of wireless communication systems,
reconfigurable intelligent surfaces~(RISs) are regarded as one of the promising
technological enablers, which can provide programmable signal propagation.
Therefore, simultaneous radio localization and mapping(SLAM) with RISs appears
as an emerging research direction within the 6G ecosystem. In this paper, we
propose a novel framework of RIS-enabled radio SLAM for wireless operation
without the intervention of access points (APs). We first design the RIS phase
profiles leveraging prior information for the user equipment~(UE), such that
they uniformly illuminate the angular sector where the UE is probabilistically
located. Second, we modify the marginal Poisson multi-Bernoulli SLAM filter and
estimate the UE state and landmarks, which enables efficient mapping of the
radio propagation environment. Third, we derive the theoretical Cram\'er-Rao
lower bounds on the estimators for the channel parameters and the UE state. We
finally evaluate the performance of the proposed method under scenarios with a
limited number of transmissions, taking into account the channel coherence
time. Our results demonstrate that the RIS enables solving the radio SLAM
problem with zero APs, and that the consideration of the Doppler shift
contributes to improving the UE speed estimates.
