2 papers
cs.AI2018
Active Object Perceiver: Recognition-guided Policy Learning for Object Searching on Mobile Robots
Xin Ye, Zhe Lin, Haoxiang Li +2
We study the problem of learning a navigation policy for a robot to actively search for an object of interest in an indoor environment solely from its visual inputs. While scene-dr…
cs.RO2018
The AdobeIndoorNav Dataset: Towards Deep Reinforcement Learning based Real-world Indoor Robot Visual Navigation
Kaichun Mo, Haoxiang Li, Zhe Lin +1
Deep reinforcement learning (DRL) demonstrates its potential in learning a model-free navigation policy for robot visual navigation. However, the data-demanding algorithm relies on…