David Fernández Chaves

University of Malaga and University of Groningen

This paper proposes LTC-Mapping, a method for building object-oriented semantic maps that remain consistent in the long-term operation of mobile robots. Among the different challenges that compromise this aim, LTC-Mappingfocuses on two of the more relevant ones: preventing duplicate instances of objects (instance duplication) and handling dynamic s...

Simulations and synthetic datasets have historically empower the research in different service robotics-related problems, being revamped nowadays with the utilization of rich virtual environments. However, with their use, special attention must be paid so the resulting algorithms are not biased by the synthetic data and can generalize to real world...

This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects,...

Semantic maps augment traditional representations of robot workspaces, typically based on their geometry and/or topology, with meta-information about the properties, relations and functionalities of their composing elements. A piece of such information could be: fridges are appliances typically found in kitchens and employed to keep food in good co...

In robotics, semantic mapping refers to the construction of a rich representation of the environment that includes high level information needed by the robot to accomplish its tasks. Building a semantic map requires algorithms to process sensor data at different levels: geometric, topological and object detections/categories, which must be integrat...