Autonomous Exploration and with Dual RGB-D Sensors

Having a sensor that could autonomously map terrain would be a boon for exploration and a number of societal functions, such as guiding the visually impaired. Ningbo Yu and Shirong Wang, both working at Nankai University in Tianjin, China, developed dual RBG-D sensors, which measures depth, in 2019 that could autonomously map a 3D cloud map and 2D grid map environment. Autonomous navigation and exploration of an environment by a robot or other form of artificial life are dependent on having either a premade grid of surroundings to draw from or enabling the mapping function as it goes, which is much more complicated. If a robot or AUV is equipped with the sensor developed by Yu and Wang, it could then plan a path and appropriately adjust its navigational speed and direction without direct human intervention (assuming the robot is also equipped with some form of artificial intelligence so that decision-making is possible). These sensors are still being developed, and their application is dependent upon successful integration with other technologies, which are broad.. A potential critique of this technology is that it has just been applied to an indoor environment, and as it stands now, it doesn’t yet incorporate any moving objects into its modelling process, which would be an important consideration if this technology were to be practically applied.


Artificial Intelligence, Data, Ecological Modelling, Ecological Monitoring, Monitoring, Regulation