DCOP-MST is an extension of the DCOP framework for representing and solving dynamic multi-agent applications that include teams of mobile sensing agents. Local search algorithms, enhanced with exploration methods were recently found to produce high quality solutions for DCOP-MST in software simulations. Applying DCOP-MST to robots with directed sensors (e.g., cameras) requires addressing limitations, which were not part of the original design of the DCOP-MST model, e.g., limited angle of the field of vision, collisions between robots etc. In this paper we contribute to the ongoing effort of applying DCOPs to real world applications by addressing the challenges one faces when applying the DCOP-MST model to a team of mobile sensing robots with directed sensors. We integrate the required adjustments into a new model, DCOP-MSTR, which is the modified version of DCOP-MST for such a real world robot application with directed sensors. The proposed revised model was implemented and evaluated both in software simulations and on a team of robots carrying cameras. Our evaluation of existing algorithms revealed the need to combine actions that change the location of a robot with actions that change its sensing direction in order to achieve effective exploration when solving DCOP-MSTR.