False-ceiling inspection is a critical factor in pest-control management within a built infrastructure. Conventionally, the false-ceiling inspection is done manually, which is time-consuming and unsafe. A lightweight robot is considered a good solution for automated false-ceiling inspection. However, due to the constraints imposed by less load carrying capacity and brittleness of false ceilings, the inspection robots cannot rely upon heavy batteries, sensors, and computation payloads for enhancing task performance. Hence, the strategy for inspection has to ensure efficiency and best performance. This work presents an optimal functional footprint approach for the robot to maximize the efficiency of an inspection task. With a conventional footprint approach in path planning, complete coverage inspection may become inefficient. In this work, the camera installation parameters are considered as the footprint defining parameters for the false ceiling inspection. An evolutionary algorithm-based multi-objective optimization framework is utilized to derive the optimal robot footprint by minimizing the area missed and path-length taken for the inspection task. The effectiveness of the proposed approach is analyzed using numerical simulations. The results are validated on an in-house developed false-ceiling inspection robot-Raptor-by experiment trials on a false-ceiling test-bed.
- Towards an Optimal Footprint Based Area Coverage Strategy for a False-Ceiling Inspection Robot
- Thejus Pathmakumar - Singapore University of Technology and DesignVinu Sivanantham - Singapore University of Technology and DesignSaurav Ghante Anantha Padmanabha - Singapore University of Technology and DesignMohan Rajesh Elara - Singapore University of Technology and DesignThein Than Tun - Oceania Robot Private Ltd, 3 Soon Lee St,01-03 Pioneer Junct, Singapore 627606, Singapore
- Sensors (Basel, Switzerland), Vol.21(15), p.5168
- Mdpi
- 20
- 192 22 00058 / National Robotics Programme under its Robot Domain Specific 1922500051 / National Robotics Programme under its Robotics Enabling Capabilities and Technologies 1922200108 / National Robotics Programme under its Robotics Domain Specific
- 9912445509846
- EPD Pillar
- English
- Journal article