This paper presents the CSA robotic manipulatorbased system developed to remotely conduct sample acquisition, storage, and transfer back to a lander/ascent vehicle. The prototype system was integrated with a rover and demonstrated during an emulated lunar sample return mission scenario.

In 2017 and 2019 the Canadian Space Agency (CSA) and the European Space Agency (ESA) conducted joint mission simulations in preparation for a potential sample return lunar rover mission. These simulations were conducted to study several mission elements such as: concepts of operation, robotic systems, and to measure driving performance metrics such as achievable average speed. The 2017/2019 simulations cumulated 6.8 km of distance traveled by the rover and 67 hours of on-console operation. In 2019, the operators achieved an overall average speed of 3.4 m/min (0.2 km/h) when they explicitly controlled the rover using several driving modes. This was found to be slower when compared to the rover average speed of 4.4 m/min measured in autonomous navigation .

Since the Global Exploration Roadmap has been released in the third generation early this year, the International Space Exploration Coordination Group (ISECG) has formed two technology working groups (TWG) to identify gaps in “Telerobotic Operations with Time Delay” and “Autonomy Operations”, required by the mission profiles discussed in the Global Exploration Roadmap. This paper describes the compressed results from the Working Group “Telerobotic Operations with Time Delay”, including the goal and objectives of the working team. It gives an overview of the different mode of operation, required to control robots remotely. Analysing the mission scenarios described in the roadmap, the required robotic tasks has been extracted and gaps within those have been identified. These gaps are discussed respect to the common capabilities, divided and classified in operational, performance technology and non-technical gaps.

The Canadian Space Agency, in partnership with Western University and MacDonald Dettwiler and Associates, conducted a field deployment in the Utah desert in November 2015 to emulate portions of the first steps of a Mars Sample Return mission: the identification and acquisition of scientifically interesting samples. The site was selected because of its scientific relevance to certain regions on Mars, being predominantly of sedimentary nature and preserving evidence of a previous aqueous environment. Equipment being tested at the site included the CSA’s Mars Exploration Science Rover (MESR) equipped with a mini-corer and a 3D microscope mounted on a robotic arm, a suite of cameras, and a LASER range sensor. The rover was remotely controlled over a satellite link from the Canadian Space Agency headquarters in Saint-Hubert, Canada. During the 14-day mission, the rover traversed 234 meters, acquired four samples (regolith and sedimentary material), took microscopic images at every sample location, and acquired several images and 3D LIDAR scans of the site. In addition, X-Ray fluorescence, Raman spectroscopy and X-Ray diffraction measurements were taken from hand-held instruments throughout the mission. Tubed samples have been returned to the science team for analysis, along with additional hand-collected samples from the same sites to give the science team enough material to validate its sample selection strategy.

This paper outlines the Teleoperation Robotic Testbed (TRT) project, which aims at testing simple concepts of operation (ConOps) for remotely driving a rover on the Moon, under a constrained Earth-Moon communication link. The ConOps under study focuses on teleoperating a rover with very little onboard autonomy, with ground operators actively and continuously involved in the control loop. The remote control station features enhanced situational awareness tools such as predictive displays, overlays on imagery, rover trajectory plot and panoramic imagery. The main source of feedback to the operators were monocular cameras and a basic localization system that were integrated on the TRT rover. During the 2013 field testing season, the TRT was deployed in many planetary analogue sites in order to exercise the ConOps. A total of sixteen teams remotely operated the TRT rover, taking turns on three-hour driving missions and traveled a total of 5.8 km over 48 hours of operation. The results of the campaign suggest that the ConOps studied might support simple lunar driving tasks. However, the rover average speed would be low (around 2 to 4 m/min), resulting from the rover being stationary most of the time, moreover, fatigue would prevent the operators from supporting long uninterrupted operations.

This paper describes a collection of 272 three-dimensional laser scans gathered at two unique planetary analogue rover test facilities in Canada, which offer emulated planetary terrain at manageable scales for algorithmic development. This dataset is subdivided into four individual subsets, each gathered using panning laser rangefinders on different mobile rover platforms. This data should be of interest to field robotics researchers developing rover navigation algorithms suitable for use in three-dimensional, unstructured, natural terrain. All of the data are presented in human-readable text files, and are accompanied by Matlab parsing scripts to facilitate use thereof. This paper provides an overview of the available data.

Exploration of unknown planets using autonomous rovers requires an efficient onboard localization system capable of estimating precisely rover position and orienta tion. This paper presents a method to refine rover odometry using an Iterative Closest Point (ICP) algorithm applied on 3-D LIDAR panoramas collected by a rover. Our approach takes two LIDAR scans from different locations, subsamples and simplifies them. Then it performs a registration which gives a 6 degrees of freedom rigid body transformation representing the estimation of rover odometry error accumulated during the rover motion from the first scanned location to the other. The proposed LIDAR ICP Pose Refiner (LIPR) can perform registrations in the presence of large misalignments and with overlap ratios below 50%. An intensive benchmark test using field data has shown that LIPR can tolerate larger error than three standard approaches. The paper also reports experimental results of rover pose refinement tests performed at the Mars Emulation Terrain (MET) of the Canadian Space Agency (CSA). LIPR has been tested online at more than 174 different locations of MET, keeping odometry error on the order of 1% of distance traveled.

Mobile robots using a 360° field of view LIDAR ranging sensor can generate enormous 3D point clouds. To reduce the quantity of data in memory a compression can lead to unstructured environment models such as irregular meshes. This kind of structure can contain deformed cells and the path planning can be cumbersome. This paper presents a path planning method based on fluid mechanics able to deal with unstructured terrain models. The algorithm uses the finite element method to compute a velocity potential function free from local minima. Then, several streamlines are computed as a road map and the optimal path is selected among the candidate paths. The approach is implemented on the Canadian Space Agency (CSA) Mars Robotics Testbed (MRT) rover and tested at the CSA Mars Emulation Terrain (MET). To confirm the feasibility of the method, the path planner has been tested on 284 LIDAR scans collected in a realistic outdoor challenging terrain.

A two-step approach is presented to generate a 3D navigable terrain model for robots operating in natural and uneven environment. First an unstructured surface is built from a 360 degrees field of view LIDAR scan. Second the reconstructed surface is analyzed and the navigable space is extracted to keep only the safe area as a compressed irregular triangular mesh. The resulting mesh is a compact terrain representation and allows point-robot assumption for further motion planning tasks. The proposed algorithm has been validated using a large database containing 688 LIDAR scans collected on an outdoor rough terrain. The mesh simplification error was evaluated using the approximation of Hausdorff distance. In average, for a compression level of 93.5%, the error was of the order of 0.5 cm. This terrain modeler was deployed on a rover controlled from the International Space Station (ISS) during the Avatar Explore Space Mission carried out by the Canadian Space Agency in 2009.

In this paper we present the experimental results validating the approach for autonomous planetary exploration developed by the Canadian Space Agency (CSA). The goal of this work is to autonomously navigate to remote locations, well beyond the sensing horizon of the rover, with minimal interaction with a human operator. We employ LIDAR range sensors due to their accuracy, long range and robustness in the harsh lighting conditions of space. Irregular triangular meshes (ITM) are used for representing the environment providing an accurate yet compact spatial representation. In this paper after a brief overview of the proposed approach, we discuss the terrain modelling used. A variety of experiments performed in CSA’s Mars emulation terrain that validate our approach are also presented.

This paper presents results from the 2006 and 2007 test campaigns of the Canadian Space Agency's autonomous rover navigation research. In particular, results are provided in the area of terrain modelling, path planning and 3D odometry. Results are also provided for integrated system tests whereby the rover travelled autonomously and semi-autonomously beyond its sensing horizon. It provides a summary of the experimental results that were obtained through two seasons of test campaigns.