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Accurate Mapping and Planning for Autonomous Racing
(2020)2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)This paper presents the perception, mapping, and planning pipeline implemented on an autonomous race car. It was developed by the 2019 AMZ driverless team for the Formula Student Germany (FSG) 2019 driverless competition, where it won 1st place overall. The presented solution combines early fusion of camera and LiDAR data, a layered mapping approach, and a planning approach that uses Bayesian filtering to achieve high-speed driving on ...Conference Paper -
MultiPoint: Cross-spectral registration of thermal and optical aerial imagery
(2020)Proceedings of Machine Learning Research ~ Proceedings of the 2020 Conference on Robot LearningWhile optical cameras are ubiquitous in robotics, some robots can sense the world in several sections of the electromagnetic spectrum simultaneously, which can extend their capabilities in fundamental ways. For instance, many fixed-wing UAVs carry both optical and thermal imaging cameras, potentially allowing them to detect temperature difference-induced atmospheric updrafts, map their locations, and adjust their flight path accordingly ...Conference Paper -
IAN: Multi-behavior navigation planning for robots in real, crowded environments
(2020)2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)State-of-the-art approaches for robot navigation among humans are typically restricted to planar movement actions. This work addresses the question of whether it can be beneficial to use interaction actions, such as saying, touching, and gesturing, for the sake of allowing robots to navigate in unstructured, crowded environments. To do so, we first identify challenging scenarios to traditional motion planning methods. Based on the hypothesis ...Conference Paper -
A Connectivity-Prediction Algorithm and its Application in Active Cooperative Localization for Multi-Robot Systems
(2020)2020 IEEE International Conference on Robotics and Automation (ICRA)This paper presents a method for predicting the probability of future connectivity between mobile robots with range-limited communication. In particular, we focus on its application to active motion planning for cooperative localization (CL). The probability of connection is modeled by the distribution of quadratic forms in random normal variables and is computed by the infinite power series expansion theorem. A finite-term approximation ...Conference Paper -
Informative Path Planning for Active Field Mapping under Localization Uncertainty
(2020)2020 IEEE International Conference on Robotics and Automation (ICRA)Information gathering algorithms play a key role in unlocking the potential of robots for efficient data collection in a wide range of applications. However, most existing strategies neglect the fundamental problem of the robot pose uncertainty, which is an implicit requirement for creating robust, high-quality maps. To address this issue, we introduce an informative planning framework for active mapping that explicitly accounts for the ...Conference Paper