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Henrik Christensen

7 accepted papers

2024

OSM vs HD Maps: Map Representations for Trajectory Prediction

IROS 2024poster

High Definition (HD) Maps have long been favored for their precise depictions of static road elements. However, their accessibility constraints and vulnerability to rapid environmental changes impede the widespread deployment of highly map-reliant autonomous driving tasks, such as motion forecasting…

Cited by 5SourceScholar
2021

Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications

ICRA 2021poster

Calibration of sensors is fundamental to robust performance for intelligent vehicles. In natural environments, disturbances can easily challenge calibration. One possibility is to use natural objects of known shape to recalibrate sensors. An approach based on recognition of traffic signs, such as st…

Cited by 10SourceScholar
2020

Multi-task Batch Reinforcement Learning with Metric Learning

NeurIPS 2020poster

We tackle the Multi-task Batch Reinforcement Learning problem. Given multiple datasets collected from different tasks, we train a multi-task policy to perform well in unseen tasks sampled from the same distribution. The task identities of the unseen tasks are not provided. To perform well, the polic…

Cited by 60SourcePDFScholar
2016

Hierarchical rejection sampling for informed kinodynamic planning in high-dimensional spaces

ICRA 2016poster

We present hierarchical rejection sampling (HRS) to improve the efficiency of asymptotically optimal sampling-based planners for high-dimensional problems with differential constraints. Pruning nodes and rejecting samples that cannot improve the currently best solution have been shown to improve per…

Cited by 27SourceScholar
2015

Exploiting symmetries and extrusions for grasping household objects

ICRA 2015poster

In this paper we present an approach for creating complete shape representations from a single depth image for robot grasping. We introduce algorithms for completing partial point clouds based on the analysis of symmetry and extrusion patterns in observed shapes. Identified patterns are used to gene…

Cited by 54SourceScholar
2015

Learning non-holonomic object models for mobile manipulation

ICRA 2015poster

For a mobile manipulator to interact with large everyday objects, such as office tables, it is often important to have dynamic models of these objects. However, as it is infeasible to provide the robot with models for every possible object it may encounter, it is desirable that the robot can identif…

Cited by 16SourceScholar