  Short Range wireless devices are becoming more and more popular for
ubiquitous sensor and actuator connectivity in industrial communication
scenarios. Apart from communication-only scenarios, there are also
mission-critical use cases where the distance between the two communicating
nodes needs to be determined precisely. Applications such as Automatic Guided
Vehicles (AGV's), Automatic Train Pairing additionally require the devices to
scan the environment and detect any potential humans/obstacles. Ultra-Wide Band
(UWB) has emerged as a promising candidate for Real-Time Ranging and
Localization (RTRL) due to advantages such as large channel capacity, better
co-existence with legacy systems due to low transmit power, better performance
in multipath environments etc. In this paper, we evaluate the performance of a
UWB COTS device - TimeDomain P440 which can operate as a ranging radio and a
monostatic radar simultaneously. To this end, we evaluate the possibility of
using Supervised Learning based estimators for predicting the presence of
obstacles by constructing a multiclass hypothesis. Simulation results show that
the Ensemble tree based methods are able to calculate the likelihood of
obstacle collision with accuracies close to 95%.
