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— In this paper, we present an integrated navigation system that allows humanoid robots to autonomously navigate in unknown, cluttered environments. From the data of an on-board consumer-grade depth camera, our system estimates the robot's pose to compensate for drift of odometry and maintains a heightmap representation of the environment. Based on this(More)
AbstrAct Customer investigations in the banking industry are carried out in connection with prosecutions, the administration of estates or other legal actions. The Investigation & Inquiries Department of Credit Suisse has to handle approximately 5,000 client investigations per year. To date, the investigation process has been very complex, time consuming(More)
—In this paper, we present an integrated approach for robot localization, obstacle mapping, and path planning in 3D environments based on data of an onboard consumer-level depth camera. We rely on state-of-the-art techniques for environment modeling and localization, which we extend for depth camera data. We thoroughly evaluated our system with a Nao(More)
— In this paper, we present an approach to obstacle detection for collision-free, efficient humanoid robot navigation based on monocular images and sparse laser range data. To detect arbitrary obstacles in the surroundings of the robot, we analyze 3D data points obtained from a 2D laser range finder installed in the robot's head. Relying only on this laser(More)
— Efficient footstep planning for humanoid navigation through cluttered environments is still a challenging problem. Often, obstacles create local minima in the search space, forcing heuristic planners such as A* to expand large areas. Furthermore, planning longer footstep paths often takes a long time to compute. In this work, we introduce and discuss(More)
Accurate and reliable localization is a prerequisite for autonomously performing high-level tasks with humanoid robots. In this article, we present a probabilistic localization method for humanoid robots navigating in arbitrary complex indoor environments using only onboard sensing, which is a challenging task. Inaccurate motion execution of biped robots(More)
— In this paper, we present an approach to traversability classification solely based on monocular images and odometry estimates. We iteratively estimate the ground plane by detecting and matching features. Since the features are only sparse in the images and do not lead to dense information about traversability, we present a technique to train(More)