Erick Dupuis

Autonomous capture of a tumbling satellite

In this paper, we describe a framework for the autonomous capture and servicing of satellites. The work is based on laboratory experiments that illustrate the autonomy and remote-operation aspects. The satellite-capture problem is representative of most on-orbit robotic manipulation tasks where the environment is known and structured, but it is dynamic since the satellite to be captured is in free flight. Bandwidth limitations and communication dropouts dominate the quality of the communication link. The satellite-servicing scenario is implemented on a robotic test-bed in laboratory settings. The communication aspects were validated in transatlantic tests.

The Avatar Project

CSA (Canadian Space Agency) is currently developing and conducting a series of experiments dubbed Avatar to investigate different command and control schemes allowing operators to interact with robots in space or on other planets. The objective of the Avatar experiments is to develop and test concepts in support of future space exploration missions. Although some of the concepts can be (and have been!) tested on Earth by simulating space-relevant communication links, the benefits of conducting them from the ISS are numerous. First, the usage of an intermittent amateur radio link has raised several issues regarding the robustness of the software: it is impossible to cheat when the communication link really goes down. It has also allowed the team to develop unique operational expertise. One final advantage not to be neglected is the fact that these experiments will have provided flight heritage to the command and control concepts described in this article and to the software that was used to implement them. Such heritage is precious in the traditionally conservative space community.

Task verification facility for the Canadian special purpose dextrous manipulator

As a partner in the International Space Station, Canada is responsible for the verification of all tasks involving the special purpose dextrous manipulator (SPDM). In this paper, the concept of an SPDM task verification facility (STVF) is described. The verification process involves three complementary stages. First, a real-time software simulator is used to verify the complete nominal and malfunction procedures. Next, the feasibility of a task involving contact is verified with the help of a hardware-in-the-loop simulator. Finally, a non real-time simulator is used to perform detailed parametric studies given the known tolerances on the components. The paper describes all three stages but emphasizes on the hardware-in-the-loop simulator, the only new facility within the STVF.

Precision Control of Modular Robot Manipulators: The VDC Approach With Embedded FPGA

A systematic solution to precision control of modular robot manipulators without using joint torque sensing is presented in this paper for the first time. Using the virtual decomposition control (VDC) approach with embedded field programmable gate array (FPGA) logic devices, the proposed solution solves a long-standing problem of lacking control precision fundamentally associated with the modular robot manipulators. As a result, this solution allows modular robot manipulators to possess not only their traditional advantages (such as reconfigurability, flexibility, versatility, and ease of use) but precision control capability as well. A hierarchical master-slave control structure is used, which is supported by a high-speed communication system modified from SpaceWire (IEEE 1355), transferring a limited amount of data between the master and slave nodes at a rate of 1000 Hz. In each module, the FPGA logic implementation uses multiple sampling periods of 163.8 μs, 1.28 μs, and 20 ns. A gravity counterbalance spring provides a design option for the purpose of energy saving. Experimental results demonstrate unprecedented control precision, which is attributed to the use of both the VDC approach and embedded FPGA implementation. The ratio of the maximum position tracking error to the maximum velocity reaches 0.00012 s-more than an order of magnitude better than available technologies in control of robots with harmonic drives. The solution presented in this paper is also applicable to integrated robot manipulators using embedded FPGA controllers.

Over-the-horizon, autonomous navigation for planetary exploration

The success of NASAs Mars exploration rovers has demonstrated the important benefits that mobility adds to planetary exploration. Very soon, mission requirements will impose that planetary exploration rovers drive over-the-horizon in a single command cycle. This require an evolution of the methods and technologies currently used. This paper presents experimental validation of our over-the-horizon autonomous planetary navigation. We present our approach to 3D terrain reconstruction from large sparse range data sets, localization and autonomous navigation in a Mars-like terrain. Our approach is based on on-line acquisition of range scans, map construction from these scans, path planning and navigation using the map. An autonomy engine supervises the whole process ensuring the safe navigation of the planetary rover. The outdoor experimental results demonstrate the effectiveness of the reconstructed terrain model for rover localization, path planning and motion execution scenario as well as the autonomy capability of our approach.

Adaptive Control of Harmonic Drives

Aimed at achieving ultrahigh control performance/or high-end applications of harmonic drives, an adaptive control algorithm using additional sensing, namely, the joint and motor positions and the joint torque, and their practically available time derivatives, is proposed. The proposed adaptive controller compensates the large friction associated with harmonic drives, while incorporating the dynamics offlexspline. The L 2 /L∞ stability and the L 2 gain-induced H ∞ stability are guaranteed in both joint torque and joint position control modes. Conditions for achieving asymptotic stability are also given. The proposed joint controller can be efficiently incorporated into any robot motion control system based on either its torque control interface or the virtual decomposition control approach. Experimental results demonstrated in both the time and frequency domains confirm the superior control performance achieved not only in individual joint motion, but also in coordinated motion of an entire robot manipulator.

Rough Terrain Reconstruction for Rover Motion Planning

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.

The Canadian planetary emulation terrain 3D mapping dataset

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.

Three-dimensional SLAM for mapping planetary work site environments

In this paper, we present a robust framework suitable for conducting three-dimensional simultaneous localization and mapping (3D SLAM) in a planetary work site environment. Operation in a planetary environment imposes sensing restrictions, as well as challenges due to the rugged terrain. Utilizing a laser rangefinder mounted on a rover platform, we have demonstrated an approach that is able to create globally consistent maps of natural, unstructured 3D terrain. The framework presented in this paper utilizes a sparse-feature-based approach and conducts data association using a combination of feature constellations and dense data. Because of feature scarcity, odometry measurements are also incorporated to provide additional information in feature-poor regions. To maintain global consistency, these measurements are resolved using a batch alignment algorithm, which is reinforced with heterogeneous outlier rejection to improve its robustness to outliers in either measurement type (i.e., laser or odometry). Finally, a map is created from the alignment estimates and the dense data. Extensive validation of the framework is provided using data gathered at two different planetary analogue facilities, which consist of 50 and 102 3D scans, respectively. At these sites, root-mean-squared mapping errors of 4.3 and 8.9 cm were achieved. Relative metrics are utilized for localization accuracy and map quality, which facilitate detailed analysis of the performance, including failure modes and possible future improvements.

Path Planning for Planetary Exploration

In this paper we present the work done at the Canadian Space Agency on the problem of planetary exploration. One of the main goals is the over-the-horizon navigation of a mobile robot on a Mars like environment. A key component is the ability to plan a path using maps of different resolutions and also to refine/replan when more data becomes available. Our algorithms on path planning and path segmentation are presented together with results from two years of experiments in realistic conditions.