TechTalks from event: Technical session talks from ICRA 2012

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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 = 576μs (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 "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.

Environment Mapping

  • A Dependable Perception-Decision-Execution Cycle for Autonomous Robots Authors: Gspandl, Stephan; Podesser, Siegfried; Reip, Michael; Steinbauer, Gerald; Wolfram, Máté
    The tasks robots are employed to achieve are becoming increasingly complex, demanding for dependable operation, especially if robots and humans share common space. Unfortunately, for these robots non-determinism is a severe challenge. Malfunctioning hardware, inaccurate sensors, exogenous events and incomplete knowledge lead to inconsistencies in the robot’s belief about the world. Thus, a robot has to cope efficiently with such adversities while sensing its surroundings, deciding what to do next, and executing its decisions. In this paper, we present such a dependable perception-decision-execution cycle. It employs a belief management system that performs history-based diagnosis in the high-level control module. The belief management enables robots to detect these inconsistencies and thus operate successfully in non-deterministic environments. The main contributions of this paper are a robot design extending the high-level control IndiGolog by a belief management allowing to deal with a large variety of faults in a unique way, together with an evaluation on a real robot system.
  • Efficient Change Detection in 3D Environment for Autonomous Surveillance Robots based on Implicit Volume Authors: Wilson Vieira, Antonio; Drews Jr, Paulo; Campos, Mario Montenegro
    The ability to detect changes in the environment is an essential trait for robots commissioned to work in several applications. In surveillance, for instance, a robot needs to detect meaningful changes in the environment which is achieved by comparing current sensory data with previously acquired information from the environment. The large amount of sensory data, which are often complex and very noisy, explains the inherent difficulty of this task. As an attempt to tackle this hard problem, we present an efficient method to automatically segment 3D data, corrupted with noise and outliers, into an implicit volume bounded by a surface. The method makes it possible to efficiently apply Boolean operations to 3D data in order to detect changes and to update existing maps. We show that our approach is powerful, albeit simple, with linear time complexity. The method has been validated through several trials using mobile robots operating in real environments and their performance was compared to another state-of-art algorithm. Experimental results demonstrate the performance of the proposed method, both in accuracy and computational cost.
  • Stochastic Source Seeking in Complex Environments Authors: Atanasov, Nikolay; Le Ny, Jerome; Michael, Nathan; Pappas, George J.
    The objective of source seeking problems is to determine the minimum of an unknown signal field, which represents a physical quantity of interest, such as heat, chemical concentration, or sound. This paper proposes a strategy for source seeking in a noisy signal field using a mobile robot and based on a stochastic gradient descent algorithm. Our scheme does not require a prior map of the environment or a model of the signal field and is simple enough to be implemented on platforms with limited computational power. We discuss the asymptotic convergence guarantees of algorithm and give specific guidelines for its application to mobile robots in unknown indoor environments with obstacles. Both simulations and real-world experiments were carried out to evaluate the performance of our approach. The results suggest that the algorithm has good finite time performance in complex environments.
  • Robust Sound Localization for Various Platform of Robots Using TDOA Map Adaptation Authors: Shen, Guanghu, Guanghu; Hwang, Dohyung; Nguyen, Quang; Choi, Jongsuk
    In realistic environments, mismatches between the calculated angle-TDOA map with its real exact values are the major reason of performance degradation in sound localization. Usually, those mismatches come from some certain configuration errors or deviations caused by the change of environments. To reduce those mismatches, in this paper we proposed an angle-TDOA map adaptation method, which can achieve the robust sound localization in various robot platforms (i.e., various types of microphone array configuration). Especially, the proposed method is possible to easily apply to the sound localization system by using only several sound sources which generated from some known directions. As a result, the proposed method not only showed a good localization performance, and the program running time is also very short.