Abstract. We present a topographic digital elevation model (DEM) for Princess Elizabeth Land (PEL), East Antarctica. The DEM covers an area of ∼900 000 km2 and was built from radio-echo sounding data collected during four campaigns since 2015. Previously, to generate the Bedmap2 topographic product, PEL's bed was characterized from low-resolution satellite gravity data across an otherwise large (>200 km wide) data-free zone. We use the mass conservation (MC) method to produce an ice thickness grid across faster flowing (>30 m yr−1) regions of the ice sheet and streamline diffusion in slower flowing areas. The resulting ice thickness model is integrated with an ice surface model to build the bed DEM. Together with BedMachine Antarctica and Bedmap2, this new bed DEM completes the first-order measurement of subglacial continental Antarctica – an international mission that began around 70 years ago. The ice thickness data and bed DEMs of PEL (resolved horizontally at 500 m relative to ice surface elevations obtained from the Reference Elevation Model of Antarctica – REMA) are accessible from https://doi.org/10.5281/zenodo.4023343 (Cui et al., 2020a) and https://doi.org/10.5281/zenodo.4023393 (Cui et al., 2020b).

This paper describes the implementation and testing of Alice, the California Institute of Technology's entry in the 2005 DARPA Grand Challenge. Alice utilizes a highly networked control system architecture to provide high performance autonomous driving in unknown environments. Innovations include a vehicle architecture designed for efficient testing in harsh environments, a highly sensory‐driven approach to fuse sensor data into speed maps used by real‐time trajectory optimization algorithms, health and contingency management algorithms to manage failures at the component and system level, and a software logging and display environment that enables rapid assessment of performance during testing. The system successfully completed several runs in the National Qualifying Event, but encountered a combination of sensing and control issues in the Grand Challenge Event that led to a critical failure after traversing approximately 8 miles. © 2006 Wiley Periodicals, Inc.

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The ARTEMIS docking system demonstrates autonomous docking capability applicable to robotic exploration of sub‐ice oceans and sub‐glacial lakes on planetary bodies, as well as here on Earth. In these applications, melted or drilled vertical access shafts restrict vehicle geometry as well as the in‐water infrastructure that may be deployed. The ability of the vehicle to return reliably and precisely to the access point is critical for data return, battery charging, and/or vehicle recovery. This paper presents the mechanical, sensor, and software components that make up the ARTEMIS docking system, as well as results from field deployment of the system to McMurdo Sound, Antarctica in the austral spring of 2015. The mechanical design of the system allows the vehicle to approach the dock from any direction and to pitch up after docking for recovery through a vertical access shaft. It uses only a small volume of in‐water equipment and may be deployed through a narrow vertical access shaft. The software of the system reduces position estimation error with a hierarchical combination of dead reckoning, acoustic aiding, and machine vision. The system provides critical operational robustness, enabling the vehicle to return autonomously and precisely to the access shaft and latch to the dock with no operator input.

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