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/Markus Wulfmeier

About Markus Wulfmeier

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So far Markus Wulfmeier has created 4 blog entries.

On Machine Learning and Prior Structure for Mobile Robots – The Summary

Similar to the long-term discussion on how much innate structure is required for artificial general intelligence [1], an important challenge in the short-term lies in the combination of traditional programming and machine learning for more narrow applications e.g. towards more efficient, robust, and safe robots. The question about the limitations or benefits of increased prior [...]

On Machine Learning and Prior Structure for Mobile Robots – The Summary 2018-04-12T13:52:09+00:00

FAB-MAP 3D: Topological Mapping with Spatial and Visual Appearance

  Abstract— This paper describes a probabilistic framework for appearance based navigation and mapping using spatial and visual appearance data. Like much recent work on appearance based navigation we adopt a bag-of-words approach in which positive or negative observations of visual words in a scene are used to discriminate between already visited and new places. [...]

FAB-MAP 3D: Topological Mapping with Spatial and Visual Appearance 2016-10-22T19:49:34+00:00

Hidden View Synthesis using Real-Time Visual SLAM for Simplifying Video Surveillance Analysis

Abstract— Understanding and analysing static or mobile surveillance cameras often requires knowledge of the scene and the camera placement. In this article, we provide a way to simplify the user’s task of understanding the scene by rendering the camera view as if observed from the user’s perspective by estimating his position using a real-time visual [...]

Hidden View Synthesis using Real-Time Visual SLAM for Simplifying Video Surveillance Analysis 2016-10-22T19:51:02+00:00

Teaching a Randomized Planner to plan with Semantic fields

 Abstract—This paper presents a novel way to bias the sampling domain of stochastic planners by learning from example plans. We learn a generative model of a planner as a function of proximity to labeled objects in the workspace. Our motivation is that certain objects in the workspace have a local influence on planning strategies, which [...]

Teaching a Randomized Planner to plan with Semantic fields 2016-10-22T19:51:02+00:00