TechTalks from event: Technical session talks from ICRA 2012

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Marine Robotics II

  • Opportunistic Localization of Underwater Robots Using Drifters and Boats Authors: Arrichiello, Filippo; Heidarsson, Hordur K; Sukhatme, Gaurav
    The paper characterizes the localization performance of an Autonomous Underwater Vehicle (AUV) when it moves in environments where floating drifters or surface vessels are present and can be used for relative localization. In particular, we study how localization performance is affected by parameters e.g. AUV mobility, surface objects density, the available measurements (ranging and/or bearing) and their visibility range. We refer to known techniques for estimation performance evaluation and probabilistic mobility models, and we bring them together to provide a solid numerical analysis for the considered problem. We perform an extensive simulations in different scenarios, and, as a proof of concept, we show how an AUV, equipped with an upward looking sonar, can improve its localization estimate by detecting a surface vessel.
  • Tracking of a Tagged Leopard Shark with an AUV: Sensor Calibration and State Estimation Authors: Forney, Christina; Manii, Esfandiar; Farris, Michael; Moline, Mark A.; Lowe, Christopher G.; Clark, Christopher M.
    Presented is a method for estimating the 2D planar position, velocity, and orientation states of a tagged shark. The method is designed for implementation on an Autonomous Underwater Vehicle (AUV) equipped with a stereo-hydrophone and receiver system that detects acoustic signals transmitted by a tag. The particular hydrophone system used here provides a measurement of relative bearing angle to the tag, but does not provide the sign (+ or -) of the bearing angle. A Particle Filter was used for fusing these measurements over time to produce a state estimate of the tag location. The Particle Filter combined with an active control system allowed the system to overcome the ambiguity in the sign of the bearing angle. This state estimator was validated by tracking both a stationary tag and moving tag with known positions. These experiments revealed state estimate errors were on par with those obtained by manually driven boat based tracking systems, the current method used for tracking fish and sharks over long distances. Final experiments involved the catching, releasing, and an autonomous AUV tracking of a 1 meter Leopard Shark (<i>Triakis semifasciata<i>) in SeaPlane Lagoon, Los Angeles, California.
  • An Experimental Momentum-Based Front Detection Method for Autonomous Underwater Vehicles Authors: Gottlieb, Jeremy; Graham, Rishi; Maughan, Thom; Py, Frederic; Ryan, John; Elkaim, Gabriel Hugh; Rajan, Kanna
    Fronts have been recognized as hotspots of intense biological activity. They are therefore important targets for observation to understand coastal ecology and transport in a changing ocean. With high spatial and tem- poral variability, detection and event response for frontal zones is challenging. Robotic platforms like autonomous underwater vehicles (AUVs) have shown their versatility in using automated approaches to detect a range of features; directing them using in-situ and on-shore capabilities for front detection then becomes an important tool for observ- ing such rapid and episodic changes. We introduce a novel momentum-based front detection (MBFD) algorithm de- signed to automatically detect frontal zones. MBFD utilizes a Kalman filter and a momentum accumulator function to identify significant temperature gradients associated with upwelling fronts. MBFD is designed to work at a number of levels including onboard an autonomous underwater vehicle (AUV); on-shore with a sparse, real-time data stream and post-experiment on a hi-resolution data set gathered by a robot. Such a multi-layered approach plays an important role in mixed human-computer decision making for oceanographers making coordinating sampling and asset allocation strategies in large multi-robot field experiments in the coastal ocean.
  • An Evaluation of Sampling Path Strategies for an Autonomous Underwater Vehicle Authors: Ho, Colin; Mora, Andres; Saripalli, Srikanth
    A critical problem in planning sampling paths for autonomous underwater vehicles is balancing obtaining an accurate scalar field estimation against efficiently utilizing the stored energy capacity of the sampling vehicle. Adaptive sampling approaches can only provide solutions when real-time and a priori environmental data is available. Through utilizing a cost-evaluation function to experimentally evaluate various sampling path strategies for a wide range of scalar fields and sampling densities, it is found that a systematic spiral sampling path strategy is optimal for high-variance scalar fields for all sampling densities and low-variance scalar fields when sampling is sparse. The random spiral sampling path strategy is found to be optimal for low-variance scalar fields when sampling is dense.
  • Field Performance Evaluation of New Methods for In-Situ Calibration of Attitude and Doppler Sensors for Underwater Vehicle Navigation Authors: Troni, Giancarlo; Whitcomb, Louis
    We report a comparative performance evaluation, using at-sea field data, of recently reported methods for the problem of in-situ calibration of the alignment rotation matrix between Doppler sonar velocity sensors and inertial navigation sensors arising in the navigation of underwater vehicles. Most previously reported solutions to this alignment calibration problem require the use of absolute navigation fixes of the underwater vehicle, thus requiring additional navigation sensors and/or beacons to be located externally and apart from the underwater vehicle. We briefly review four recently reported alignment calibration methods employing only internal vehicle navigation sensors for velocity, acceleration, attitude, and depth. We report the results of comparative analysis of the performance of these recently reported methods and a previously reported method with navigation data from deep-water survey missions of the Sentry autonomous underwater vehicle conducted in March, 2011 in the Kermadec Arc in the Southern Pacific Ocean. The results reveal consistent differences in performance of the various methods when analyzed on navigation data from several different vehicle dives.
  • A Bio-Inspired Compliant Robotic Fish: Design and Experiments Authors: EL DAOU, Hadi; Salumae, Taavi; Toming, Gert; Kruusmaa, Maarja
    This paper studies the modelling, design and fabrication of a bio-inspired fish-like robot propelled by a compliant body. The key to the design is the use of a single motor to actuate the compliant body and to generate thrust. The robot has the same geometrical properties of a subcarangiform swimmer with the same length. The design is based on rigid head and fin linked together with a compliant body. The flexible part is modelled as a non-uniform cantilever beam actuated by a concentrated moment. The dynamics of the compliant body are studied and a relationship between the applied moment and the resulting motion is derived. A prototype that implements the proposed approach is built. Experiments on the prototype are done to identify the model parameters and to validate the theoretical modelling.

Force & Tactile Sensors

  • Finger Flexion Force Sensor Based on Volar Displacement of Flexor Tendon Authors: Heo, Pilwon; Kim, Jung
    A wearable sensor for measuring finger flexion force based on volar displacement of flexor tendon is presented. The proposed sensor utilizes a principle that the volar displacement of tendon under a pulley depends on both of tendon tension and finger posture when a external compressive force is applied on the pulley. A prototype sensor is built for the verification of the proposed method. Experiments with isometric conditions are performed in 9 different finger postures to observe the response of the sensor with regard to the finger flexion force and finger posture. The results show that the output of the proposed sensor has dependency on both of finger force and posture. This implies that the sensor can be used for measuring finger flexion force when the finger posture and the corresponding sensor response is known. A simulation with simplified model is performed to explain the behavior of the sensor output.
  • A Compact Two DOF Magneto-Elastomeric Force Sensor for a Running Quadruped Authors: Ananthanarayanan, Arvind; Foong, Shaohui; Kim, Sangbae
    This paper presents a novel design approach for a two-DOF foot force sensor for a high speed running quadruped. The adopted approach harnesses the deformation property of an elastomeric material to relate applied force to measurable deformation. A lightweight, robust and compact magnetic-field based sensing system, consisting of an assembly of miniature hall-effect sensors, is employed to infer the positional information of a magnet embedded in the elastomeric material. Instead of solving two non-linear models (magnetic field and elastomeric) sequentially, a direct approach of using artificial neural networks (ANN) is utilized to relate magnetic flux density (MFD) measurements to applied forces. The force sensor, which weighs a only 24.5 gms, provides a measurement range of 0 - 1000 N normal to the ground and up to $pm$ 125N parallel to the ground. The mean force measurement accuracy was found to be within 7% of the applied forces. The sensor designed as part of this work finds direct applications in ground reaction force sensing for a running quadrupedal robot.
  • Basic Experiments of Three-Axis Tactile Sensor Using Optical Flow Authors: Ohka, Masahiro; Matsunaga, Takuya; Nojima, Yu; Noda, Daiji; Hattori, Tadashi
    Three-axis tactile sensing has advantages for grasping an object of unknown mass and hardness. We developed a new three-axis tactile sensor that possesses a simple structure to endure large applied force from a powerful grasp. Vertical force distribution is measured based on grayscale values obtained by image data processing, as with previous three-axis tactile sensors. Tangential force distribution is determined by the linear movement of image data calculated by optical flow. The sensing characteristics of this sensor are dominated by the configuration and material of fine conical feelers formed on a silicon rubber sheet. By UV-LIGA, we obtain a fine mold of a silicon rubber sheet. In evaluation experiments, we applied both vertical and tangential force to the sensor and confirmed this tactile sensor’s ability to acquire normal and tangential forces. In its design, we utilize a USB microscope that has a CMOS camera and a light source. In a series of experiments, we performed vertical and tangential force tests to obtain its basic characteristics. The linear relationship between the grayscale value and the vertical force is obtained from the vertical force test. If the average optical flow is under 0.2 mm, the tangential force is proportional to the average optical flow. The inclination of the relationship between the tangential force and the average optical flow increases with additional vertical force. Finally, we derive a series of equations for three-axis force calculatio
  • A Computationally Fast Algorithm for Local Contact Shape and Pose Classification Using a Tactile Array Sensor Authors: Liu, Hongbin; Song, Xiaojing; Nanayakkara, Thrishantha; Seneviratne, lakmal; Althoefer, Kaspar
    This paper proposes a new computationally fast algorithm for classifying the primitive shape and pose of the local contact area in real-time using a tactile array sensor attached on a robotic fingertip. The proposed approach abstracts the lower structural property of the tactile image by analyzing the covariance between pressure values and their locations on the sensor and identifies three orthogonal principal axes of the pressure distribution. Classifying contact shapes based on the principal axes allows the results to be invariant to the rotation of the contact shape. A naïve Bayes classifier is implemented to classify the shape and pose of the local contact shapes. Using an off-shelf low resolution tactile array sensor which comprises of 5×9 pressure elements, an overall accuracy of 97.5% has been achieved in classifying six primitive contact shapes. The proposed method is very computational efficient (total classifying time for a local contact shape = 576&#956;s (1736 Hz)). The test results demonstrate that the proposed method is practical to be implemented on robotic hands equipped with tactile array sensors for conducting manipulation tasks where real-time classification is essential.
  • Analysis of the Trade-Off between Resolution and Bandwidth for a Nanoforce Sensor Based on Diamagnetic Levitation Authors: Piat, Emmanuel; Abadie, Joel; OSTER, Stéphane
    Nanoforce sensors based on passive diamagnetic levitation with a macroscopic seismic mass are a possible alternative to classical Atomic Force Microscopes when the force bandwidth to be measured is limited to a few Hertz. When an external unknown force is applied to the levitating seismic mass, this one acts as a transducer that converts this unknown input into a displacement that is the measured output signal. Because the inertia effect due to the mass of such macroscopic transducers can not be neglected for timevarying force measurement, it is necessary to deconvolve the displacement to correctly estimate the unknown input force. A deconvolution approach based on a Kalman filter and controlled by a scalar parameter has been recently proposed. The adjustement of this parameter leads to a trade-off that is analysed in this paper in term of resolution and bandwidth of the estimated force. Associated tools to help the end-user to set this parameter are also described.
  • An Investigation of the Use of Linear Polarizers to Measure Force and Torque in Optical 6-DOF Force/Torque Sensors for Dexterous Manipulators Authors: Sargeant, Ramon; Seneviratne, lakmal; Althoefer, Kaspar
    This paper presents a prototype of a force/torque sensor that uses fiber optic guided light and linear polarizer materials to obtain intensity modulated light to detect applied force and torque to the sensing structure. The sensor is also capable of measuring the contact direction between the sensor and the object. The sensor’s design and operating principles are explained and experimental data is given to verify the proposed operating principle. The experimental data shows that linear polarizers can be used to measure the torque applied to a force/torque sensor.

Motion Path Planning I

  • Navigation Functions for Everywhere Partially Sufficiently Curved Worlds Authors: Filippidis, Ioannis; Kyriakopoulos, Kostas
    We extend Navigation Functions (NF) to worlds of more general geometry and topology. This is achieved without the need for diffeomorphisms, by direct definition in the geometrically complicated configuration space. Every obstacle boundary point should be partially sufficiently curved. This requires that at least one principal normal curvature be sufficient. A normal curvature is termed sufficient when the tangent sphere with diameter the associated curvature radius is a subset of the obstacle. Examples include ellipses with bounded eccentricity, tori, cylinders, one-sheet hyperboloids and others. Our proof establishes the existence of appropriate tuning for this purpose. Direct application to geometrically complicated cases is illustrated through nontrivial simulations.
  • Trajectory Tracking among Landmarks and Binary Sensor-Beams Authors: Tovar, Benjamin; Murphey, Todd
    We study a trajectory tracking problem for a mobile robot moving in the plane using combinatorial observations from the state. These combinatorial observations come from crossing binary detection beams. A binary detection beam is a sensing abstraction arising from physical sensor beams or virtual beams that are derived from several sensing modalities, such as actual detection beams in the environment, changes in the angular order of landmarks around the robot, or recognizable markings in the plane. We solve the filtering problem from a geometric perspective and present its relation to linear recursive filters in control theory. Subsequently, we develop the acceleration control of the robot to track a given input trajectory, with a finite control set consisting on moving toward landmarks naturally modeling the robot as a switched dynamical system. We present experiments using an e-puck differential-drive robot, in which a useful estimate of the state for tracking is produced regardless of nontrivial uncertainty.
  • A Singularity-Free Path Planner for Closed-Chain Manipulators Authors: Bohigas, Oriol; Henderson, Michael E.; Ros, Lluis; Porta, Josep M
    This paper provides an algorithm for computing singularity-free paths on non-redundant closed-chain manipulators. Given two non-singular configurations of the manipulator, the method attempts to connect them through a configuration space path that maintains a minimum clearance with respect to the singularity locus at all points. The method is resolution-complete, in the sense that it always returns a path if one exists at a given resolution, or returns &quot;failure'' otherwise. The path is computed by defining a new manifold that maintains a one-to-one correspondence with the singularity-free configuration space of the manipulator, and then using a higher-dimensional continuation technique to explore this manifold systematically from one configuration, until the second configuration is found. Examples are included that demonstrate the performance of the method on illustrative situations.
  • Comparison of Constrained Geometric Approximation Strategies for Planar Information States Authors: Song, Yang; O'Kane, Jason
    This paper describes and analyzes a new technique for reasoning about uncertainty called constrained geometric approximation (CGA). We build upon recent work that has developed methods to explicitly represent a robot's knowledge as an element, called an information state, in an appropriately defined information space. The intuition of our new approach is to constrain the I-state to remain in a structured subset of the I-space, and to enforce that constraint using appropriate overapproximation methods. The result is a collection of algorithms that enable mobile robots with extreme limitations in both sensing and computation to maintain simple but provably meaningful representations of the incomplete information available to them. We present a simulated implementation of this technique for a sensor-based navigation task, along with experimental results for this task showing that CGA, compared to a high-fidelity representation of the un-approximated I-state, achieves a similar success rate at a small fraction of the computational cost.
  • Voxel-Based Motion Bounding and Workspace Estimation for Robotic Manipulators Authors: Anderson-Sprecher, Peter; Simmons, Reid
    Identification of regions in space that a robotic manipulator can reach in a given amount of time is important for many applications, such as safety monitoring of industrial manipulators and trajectory and task planning. However, due to the high-dimensional configuration space of many robots, reasoning about possible physical motion is often intractable. In this paper, we propose a novel method for creating a <i>reachability grid</i>, a voxel-based representation that estimates the minimum time needed for a manipulator to reach any physical location within its workspace. We use up to second-degree constraints on joint motion to model motion limits for each joint independently, followed by successive voxel approximations to map these limits on to the robot’s physical workspace. Results using a simulated manipulator indicate that our method can produce accurate reachability grids in real-time, even for robots with many degrees of freedom. Furthermore, errors are almost exclusively biased towards producing more optimistic reachability estimates, which is a desirable characteristic for many applications.
  • Branch and Bound for Informative Path Planning Authors: Binney, Jonathan; Sukhatme, Gaurav
    We present an optimal algorithm for informative path planning (IPP), using a branch and bound method inspired by feature selection algorithms. The algorithm uses the monotonicity of the objective function to give an objective function-dependent speedup versus brute force search. We present results which suggest that when maximizing variance reduction in a Gaussian process model, the speedup is significant.