Attitude estimation for dynamic legged locomotion using range and inertial sensors

Legged robots offer exceptional mobility in uncharted terrains. Their dynamic nature yields unrivaled mobility, but serves to destabilize the motion estimation process that underlies legged operations. In particular, the discontinuous foot fall patterns and flight phases result in severe impulses, which, in turn, result in excessive accumulation of drift by inertial sensors. Ground range measurements, amongst several others, are robust to this drift yet are limited in application due to their low-bandwidth and sensitivity to ground conditions. In considering the attitude estimation problem for this dynamic legged locomotion, this paper develops a pose calculation method based on ground range measurements. This is used in conjunction with a hybrid Extended Kalman Filter that takes advantage of the ballistic nature of the flight phases. Results indicate that this combination provides rapid, robust estimates of attitude necessary for extended dynamic legged operations. In single leg experiments, which were conducted using low-cost sensing hardware, this method had an RMS error of <1°, half that of a non-hybrid EKF approach. ©2005 IEEE

System design of a quadrupedal galloping machine

In this paper we present the system design of a machine that we have constructed to study a quadrupedal gallop gait. The gallop gait is the preferred high-speed gait of most cursorial quadrupeds. To gallop, an animal must generate ballistic trajectories with characteristic strong impacts, coordinate leg movements with asymmetric footfall phasing, and effectively use compliant members, all the while maintaining dynamic stability. In this paper we seek to further understand the primary biological features necessary for galloping by building and testing a robotic quadruped similar in size to a large goat or antelope. These features include high-speed actuation, energy storage, on-line learning control, and high-performance attitude sensing. Because body dynamics are primarily influenced by the impulses delivered by the legs, the successful design and control of single leg energetics is a major focus of this work. The leg stores energy during flight by adding tension to a spring acting across an articulated knee. During stance, the spring energy is quickly released using a novel capstan design. As a precursor to quadruped control, two intelligent strategies have been developed for verification on a one-legged system. The Levenberg-Marquardt on-line learning method is applied to a simple heuristic controller and provides good control over height and forward velocity. Direct adaptive fuzzy control, which requires no system modeling but is more computationally expensive, exhibits better response. Using these techniques we have been successful in operating one leg at speeds necessary for a dynamic gallop of a machine of this scale. Another necessary component of quadruped locomotion is high-resolution and high-bandwidth attitude sensing. The large ground impact accelerations, which cause problems for any single traditional sensor, are overcome through the use of an inertial sensing approach using updates from optical sensors and vehicle kinematics

RobotAssist - A platform for human robot interaction research

This paper presents RobotAssist, a robotic platform designed for use in human robot interaction research and for entry into Robocup@Home competition. The core autonomy of the system is implemented as a component based software framework that allows for integration of operating system independent components, is designed to be expandable and integrates several layers of reasoning. The approaches taken to develop the core capabilities of the platform are described, namely: path planning in a social context, Simultaneous Localisation and Mapping (SLAM), human cue sensing and perception, manipulatable object detection and manipulation

Design and evaluation of an integrated planar localization method for desktop robotics

Localization and measurement of displacement are critical aspects to the operation and control of mobile robots. The motion of desktop robots, a class of mobile robots designed for use on a table, can be considered a special case of the general localization problem since the vehicle is primarily operated over a flat surface. Using the assumption that the motion of a desktop robot is essentially planar, this paper presents a novel method that senses the motion of two points to obtain both the position and orientation of the robot in two-dimensional space. The paper details how this method can be implemented using low-cost, off-the-shelf sensor hardware components and demonstrates its application in the Desktop-Bot, a compact desktop robot. Experimental testing validated features of this planar localization such as: estimation with minimal mean error (or drift), no external sensing hardware apparatus (i.e., on-board sensing), fast-update rates (∼50 Hz) and robustness to external occlusion

Towards high-fidelity on-board attitude estimation for legged locomotion via a hybrid range and inertial approach

Legged robots display a characteristically periodic motion. Measuring and tracking this motion has traditionally been performed using general inertial measurement techniques. While widely applied in robotics, this approach is limited in dynamic legged locomotion due to the excessive accumulation of drift from severe impact shocks (nearly 9g in single leg experiments). This paper introduces the attitude estimation problem for legged locomotion and shows preliminary results from a more powerful combined range and inertial sensing approach. Based on a modified Extended Kalman Filter the method uses ground-directed range sensors, the stride period, and other periodic features of legged locomotion in order to address inertial drift. Together this provides rapid, robust estimates of flight phases and attitude necessary for extended dynamic legged operations. © Springer-Verlag Berlin/Heidelberg 2006

GL-Link: A novel telerobotics-based platform supporting distributed mechatronic research via the Internet

Mechatronics and robotics research efforts of large complexity are increasingly interdisciplinary involving collaboration between software, hardware, controls, and scientific teams. Traditionally, the level of integration has either required repeated site-visits or location of the teams at a common site. As the teams become increasingly diverse and disperse, there is a need for distributed operations platform that not only facilitates smooth communications, but also allows for remote experimentation and control of a common robot or device. By separating the principal design functions, a modular communications platform was developed to support the distance learning and experimental requirements of ambitious mechatronic development projects. This separation results in a modular system that is scalable and customizable to the particular conditions governing an experiment. The platform leverages off-the-shelf hardware and software and the presence of Internet connectivity. Where possible, open-source options were used to make the platform extensible to a variety of platforms and applications. The system is modular and consists of: a video observation/conferencing module, a file-transfer module, and a robot teleoperation module. This allowed multiple teams to test the operation of a robot independently and asynchronously without corrupting the work being conducted by another team member. It also allowed for new forms of interaction and reduced the need for travel between the multiple geographically-distributed research teams. Novel features of this work include a modular multi-platform architecture and an integration of basic telerobotics principles to extend PC-based collaboration/conferencing technologies from a basic communications platform to a means for supporting multi-site (robotics) research experiments. This paper describes the design considerations and evaluations associated with the development of the Great Little Interlink (GL-Link) architecture. This platform was motivated by robotics research ongoing between Stanford and Ohio State Universities. The platform was tested over several months as part of the design of a high-speed quadruped robot. Results from this trial highlight the impact of highly sensitive audio and video inputs and show the need for robustness to bandwidth fluctuations

Optical flow aided motion estimation for legged locomotion

Dynamic legged locomotion entails navigating terrain at high speed. The impact shocks from rapid footfalls, pivotal for such mobility, introduce large impulses that saturate motion measurement. A biomimetic approach is presented in which visual information, in the form of optical flow, complements information from inertial sensors. The motion is then determined using a two-phase Hybrid Extended Kalman Filter. Experimentation in determining attitudes on a robotic leg platform shows a reduction in drift over inertial approaches and in delay over visual approaches. In tests with 6g impulses, pose was recovered within 5 deg rms with angular rate errors limited to 10 deg/sec at frequencies up to 250 Hz. © 2006 IEEE