Abstract
Autonomous indoor robotic systems need to perform tasks across multiple floors, such as mapping, search. The floor maps for each floor can be aligned only when the relative position and orientation are known. This can be achieved if the mapping and localization continues as a platform reaches one floor to the next through the staircases. The present work evolves a system which allows a tracked platform navigate through staircases without slippages or tipping, while ensuring that its localization and mapping of the stairway continues. The effort included three main contributions. First, a novel real-time vision-based alignment algorithm that aligns the platform to the staircase is executed before ascending and thereafter, while on-stair, another novel mechanism that continuously keeps the platform aligned with the staircase is executed. For descent, an improved proximity sensor-based algorithm is proposed and analyzed. Some important challenges in mapping and localization are overcome using a sequence of different mapping methods. The staircase mapping algorithm is switched to floor mapping using a novel algorithm for disembark detection using proximity sensor data. The navigation, mapping and localization algorithms work in parallel, allowing the system to perform tasks autonomously across floors. The algorithms developed are independent of slope, width, height, or number of steps, as long as the stairs are straight and regular.
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Syed, I.A., Shine, P., Naidu, K.D., Sharma, B., Singh, S., Deodhare, D. (2018). Autonomous Staircase Navigation System for Multi-floor Tasks. In: Chaudhuri, B., Kankanhalli, M., Raman, B. (eds) Proceedings of 2nd International Conference on Computer Vision & Image Processing . Advances in Intelligent Systems and Computing, vol 704. Springer, Singapore. https://doi.org/10.1007/978-981-10-7898-9_19
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DOI: https://doi.org/10.1007/978-981-10-7898-9_19
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