Indoor pedestrian navigation systems are increasingly needed in various types of applications. However, such systems are still face many challenges. In addition to being accurate, a pedestrian positioning system must be mobile, cheap, and lightweight. Many approaches have been explored. In this paper, we take the advantage of sensors integrated in a smartphone and their capabilities to develop and compare two low-cost, hands-free, and handheld indoor navigation systems. The first one relies on embedded vision (smartphone camera), while the second option is based on low-cost smartphone inertial sensors (magnetometer, accelerometer, and gyroscope) to provide a relative position of the pedestrian. The two associated algorithms are computationally lightweight, since their implementations take into account the restricted resources of the smartphone. In the experiment conducted, we evaluate and compare the accuracy and repeatability of the two positioning methods for different indoor paths. The results obtained demonstrate that the visionbased localization system outperforms the inertial sensor-based positioning system.

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Fig. 1. ELEGOO Smart Robot Car V3.0. by robots. Whereas, in 2020 this percentage have raised to reach 26% as cited in [1].Moreover, robots can be fixed in place or mobile as the International Organization for Standardization (ISO) said in [2]. However, Mobile Robots (MRs) are gaining more and more popularity. In fact, they are very used, specifically when it is a question to improve safety of workmen, performing tough and dangerous tasks. Otherwise, to do these kinds of tasks, MR must be navigated safely within its environment which

In this paper, an online testing approach that checks continuously at remote system the correctness of embedded systems in full operation is proposed. Our new method exploits optical beams produced by an Optical Built-In Logic-Block Observation (OBILBO) register based on the captured data presented on the outputs of all stages of the registers in the BILBO. Then it is possible to send the captured data to remote system equipped with optical sensors in real time way. The final captured response data can also be used for final comparison with stored data of a golden circuit. Preliminary simulation results showed that faults are concurrently detected without affecting normal system operation and without having recourse to any external or internal Automatic Test Pattern Generation (ATPG).

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