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Service robots have to robustly follow and interact with humans. In this paper, we propose a very fast multi-people tracking algorithm designed to be applied on mobile service robots. Our approach exploits RGB-D data and can run in real-time at very high frame rate on a standard laptop without...
Introducing a priori knowledge about the latent structure of the environment in simultaneous localization and mapping (SLAM), can improve the quality and consistency results of its solutions. In this paper we describe and analyze a general framework for the detection, evaluation, incorporation...
This paper presents a rectangular cuboid approximation framework (RMAP) for 3D mapping. The goal of RMAP is to provide computational and memory efficient environment representations for 3D robotic mapping using axis aligned rectangular cuboids (RC). This paper focuses on two aspects of the RMAP...
When a battery-powered robot needs to operate for a long period of time, optimizing its energy consumption becomes critical. Driving motors are a major source of power consumption for mobile robots. In this paper, we study the problem of finding optimal paths and velocity profiles for car-like...
We present an example-based planning framework to generate semantic grasps, stable grasps that are functionally suitable for specific object manipulation tasks. We propose to use partial object geometry, tactile contacts, and hand kinematic data as proxies to encode task-related constraints,...
This article presents a probabilistic algorithm for representing and learning complex manipulation activities performed by humans in everyday life. The work builds on the multi-level Hierarchical Hidden Markov Model (HHMM) framework which allows decomposition of longer-term complex manipulation...
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