Autonomous 3D Exploration of Large Structures Using an UAV Equipped with a 2D LIDAR

This paper addressed the challenge of exploring large, unknown, and unstructured industrial environments with an unmanned aerial vehicle (UAV). The resulting system combined well-known components and techniques with a new manoeuvre to use a low-cost 2D laser to measure a 3D structure. Our approach combined frontier-based exploration, the Lazy Theta* path planner, and a flyby sampling manoeuvre to create a 3D map of large scenarios. One of the novelties of our system is that all the algorithms relied on the multi-resolution of the octomap for the world representation. We used a Hardware-in-the-Loop (HitL) simulation environment to collect accurate measurements of the capability of the open-source system to run online and on-board the UAV in real-time. Our approach is compared to different reference heuristics under this simulation environment showing better performance in regards to the amount of explored space. With the proposed approach, the UAV is able to explore 93% of the search space under 30 min, generating a path without repetition that adjusts to the occupied space covering indoor locations, irregular structures, and suspended obstaclesUnión Europea Marie Sklodowska-Curie 64215Unión Europea MULTIDRONE (H2020-ICT-731667)Uniión Europea HYFLIERS (H2020-ICT-779411

Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it. The SLAM community has made astonishing progress over the last 30 years, enabling large-scale real-world applications, and witnessing a steady transition of this technology to industry. We survey the current state of SLAM. We start by presenting what is now the de-facto standard formulation for SLAM. We then review related work, covering a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping, theoretical performance guarantees, active SLAM and exploration, and other new frontiers. This paper simultaneously serves as a position paper and tutorial to those who are users of SLAM. By looking at the published research with a critical eye, we delineate open challenges and new research issues, that still deserve careful scientific investigation. The paper also contains the authors' take on two questions that often animate discussions during robotics conferences: Do robots need SLAM? and Is SLAM solved

Automated Additive Construction (AAC) for Earth and Space Using In-situ Resources

Using Automated Additive Construction (AAC), low-fidelity large-scale compressive structures can be produced out of a wide variety of materials found in the environment. Compressionintensive structures need not utilize materials that have tight specifications for internal force management, meaning that the production of the building materials do not require costly methods for their preparation. Where a certain degree of surface roughness can be tolerated, lower-fidelity numerical control of deposited materials can provide a low-cost means for automating building processes, which can be utilized in remote or extreme environments on Earth or in Space. For space missions where every kilogram of mass must be lifted out of Earth’s gravity well, the promise of using in-situ materials for the construction of outposts, facilities, and installations could prove to be enabling if significant reduction of payload mass can be achieved. In a 2015 workshop sponsored by the Keck nstitute for Space Studies, on the topic of Three Dimensional (3D) Additive Construction For Space Using In-situ Resources, was conducted with additive construction experts from around the globe in attendance. The workshop explored disparate efforts, methods, and technologies and established a proposed framework for the field of Additive Construction Using In-situ Resources. This paper defines the field of Automated Additive Construction Using In-situ Resources, describes the state-of-the-art for various methods, establishes a vision for future efforts, identifies gaps in current technologies, explores investment opportunities, and proposes potential technology demonstration missions for terrestrial, International Space Station (ISS), lunar, deep space zero-gravity, and Mars environments