— Map learning is a fundamental task in mobile robotics because maps are required for a series of high level applications. In this paper, we address the problem of building maps ...
Patrick Pfaff, Rudolph Triebel, Cyrill Stachniss, ...
Using multilayer perceptrons (MLPs) to approximate the state-action value function in reinforcement learning (RL) algorithms could become a nightmare due to the constant possibilit...
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
Simultaneous localization and mapping (SLAM) is a basic prerequisite in autonomous mobile robotics. Most existing visual SLAM approaches either assume a static environment, or sim...
— This paper presents a new method for navigation and localization of a mobile robot equipped with an omnidirectional camera. We represent the environment using a collection of o...
Amy J. Briggs, Yunpeng Li, Daniel Scharstein, Matt...