While walking around a city, the temporary obstacles present on the sidewalk barely register in most people’s minds. The reality for people with disabilities is quite diff erent, whether it’s a scooter left in the way, crowds that refuse to budge or construction work loud enough to trigger somatic eff ects. While detecting permanent obstacles (e.g. wheelchair-inaccessible areas) is a relatively easy thing, detecting and addressing temporary obstacles is very diffi cult. The objective of this paper is to propose some fi rst elements to build a framework aiming at detecting temporary obstacles for diversely disabled users. We point out several scientifi c and technical obstacles that pave the way to reach our goal and highlight the limits of existing approaches. We insist on three signifi cant obstacles to overcome: incomplete models of the envi- ronment, limited availability of good quality data, and absence of tailored algorithms. Taking inspiration from percolation theory, we propose some leads to solve the fi rst two problems mentioned.