Tom Lamarche

Velocity Estimation by Using Position and Acceleration Sensors

Knowledge of velocity is crucial to certain industrial applications involving high-bandwidth modeling and control. In conventional approaches, the velocities obtained from encoders or tachometers are quite noisy, and low-pass filters are usually engaged to generate usable velocity signals. The low-pass filter, however, causes significant phase lag that can severely affect both modeling and control accuracy in the mid- and high-frequency ranges. In this paper, two approaches using a combination of an encoder and an imperfect accelerometer are proposed to estimate velocities with high bandwidth. The two approaches, namely the two-channel approach and the observer-based approach, estimate velocities by applying proper frequency weightings to the encoder and accelerometer signals. The encoder mainly contributes to the low-frequency components of velocity estimation, and the accelerometer mainly contributes to the high-frequency components of velocity estimation. An adaptive mechanism for estimating the accelerometer gain is also presented. The effectiveness of the two velocity estimation approaches is verified experimentally with respect to a one-degree-of-freedom robot performing both rigid contact modeling and control. Extension to 3-D applications is discussed.

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.

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.

Modular Robot Manipulators Based on Virtual Decomposition Control

Modular or re-configurable robots have been studied and developed over two decades. Most researches focus on mechatronic interfaces and re-configurable capabilities. However, less attention has been paid to dynamics and control. Consequently, the control performance of a modular robot has never been comparable with an integrated robot, due to the lack of proper handling of the dynamic interactions among the modules. In this paper, the application of the virtual decomposition control to modular robot manipulators is discussed. A high-speed databus with a data rate of 100 Mbps is used for necessary information exchange among the modules. The dynamics based control is fully handled by the local embedded controllers, whereas the host computer handles the kinematics related computation. The stability of the entire robot is rigorously guaranteed. This research aims at giving the modular robots the comparable control performance as the integrated robots, while keeping the fundamental feasibilities such as low cost for mass production, high flexibility, and easy use and expansion.

Autonomous over-the-horizon navigation using LIDAR data

In this paper we present the approach for autonomous planetary exploration developed at the Canadian Space Agency. The goal of this work is to enable autonomous navigation 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 (ITMs) are used for representing the environment, providing an accurate, yet compact, spatial representation. In this paper a novel path-planning technique through the ITM is introduced, which guides the rover through flat terrain and safely away from obstacles. Experiments performed in CSA’s Mars emulation terrain, validating our approach, are also presented.

Terrain Modelling 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 autonomously in unknown terrain. This will require an evolution of the methods and technologies currently used. This paper presents our approach to 3D terrain reconstruction from large sparse range data sets, and the data reduction achieved through decimation. The outdoor experimental results demonstrate the effectiveness of the reconstructed terrain model for different types of terrain. We also present a first attempt to classify the terrain based on the scans properties.

Modular Robot Manipulators with Preloadable Modules

While versatility and flexibility make modular and reconfigurable robots particularly suitable for applications in unstructured environments, the use of embedded electronics and local computers imposes an inherent limitation on control performance and payload capability. The virtual decomposition control (VDC) supported with a high-speed communication system has been suggested to effectively handle the dynamics and control issues aimed at allowing modular and reconfigurable robots to have the same control performance as integrated robots. In this paper, the payload capability issue is addressed by using a preloaded torsional spring to counter-balance static torques caused by gravity. Brief concept on spring design is presented, together with a review on system structure, communication mechanism, and VDC algorithms.

Damping enhancement of haptic devices by using velocities from accelerometers and encoders

High-stiffness environment emulation requires a haptic device to have a large damping coefficient in order to keep the stability during a virtual contact. Aimed at increasing the maximum allowable damping coefficient, two new approaches of using a velocity derived from both acceleration and position measurements are presented in this paper. An adaptive mechanism is provided to accommodate both offset and gain uncertainties of the accelerometer. The feasibility of using the velocity derived from both accelerometer and encoder is demonstrated experimentally when a one-degree of freedom (DOF) haptic device contacts with a virtual wall. The contribution of this paper suggests that any existing haptic device would be able to expand its capacity of emulating high-stiffness virtual environments when velocities estimated from both accelerometers and encoders are used.

Velocity estimation by using imperfect accelerometer and encoder for rigid contact modeling and control

Velocity estimation is crucial to certain robotic applications involving high bandwidth modeling and control. In the conventional approaches, the velocities generated from encoders or tachometers are quite noisy and low-pass filters are usually engaged to generate usable velocity signals. The low-pass filter, however, cause non negligible phase lag that may severely affect both modeling and control accuracy in the middle and high frequency range. In this paper, two approaches of using a fusion of an encoder and an imperfect accelerometer are proposed to estimate accurate velocities. The two approaches, namely the two-channel approach and the observer-based approach, estimate velocities by using proper frequency weightings over the encoder and accelerometer signals. The encoder mainly contributes to the low-frequency part of the velocity estimation and the accelerometer mainly contribute to the high-frequency part of the velocity estimation. An adaptive mechanism for estimating the accelerometer gain is also presented. The effectiveness of the two proposed velocity estimation approaches is verified experimentally with respect to a one degree-of-freedom robot in terms of both rigid contact modeling and control

3D Reconstruction of Environments for Tele-Operation of Planetary Rover

In this paper we consider the problem of constructing a 3D environment model for the tele-operation of a planetary rover. We presented our approach to 3D environment reconstruction from large sparse range data sets. In space robotics applications, an accurate and up-to-date model of the environment is very important for a variety of reasons. In particular, the model can be used for safe tele-operation, path planning and mapping points of interest. We propose an on-line reconstruction of the environment using data provided by an on-board high resolution and accurate 3D range sensor (LIDAR). Our approach is based on on-line acquisition of range scans from different view-points with overlapping regions, merge them together into a single point cloud, and then fit an irregular triangular mesh on the merged data. The experimental results demonstrate the effectiveness of our approach in localization, path planning and execution scenario on the Mars Yard located at the Canadian Space Agency.