TechTalks from event: Technical session talks from ICRA 2012

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RGB-D Localization and Mapping

  • Efficient Scene Simulation for Robust Monte Carlo Localization Using an RGB-D Camera Authors: Fallon, Maurice; Johannsson, Hordur; Leonard, John
    This paper presents Kinect Monte Carlo Localization (KMCL), a new method for localization in three dimensional indoor environments using RGB-D cameras, such as the Microsoft Kinect. The approach makes use of a low fidelity a priori 3-D model of the area of operation composed of large planar segments, such as walls and ceilings, which are assumed to remain static. Using this map as input, the KMCL algorithm employs feature-based visual odometry as the particle propagation mechanism and utilizes the 3-D map and the underlying sensor image formation model to efficiently simulate RGB-D camera views at the location of particle poses, using a graphical processing unit (GPU). The generated 3D views of the scene are then used to evaluate the likelihood of the particle poses. This GPU implementation provides a factor of ten speedup over a pure distance-based method, yet provides comparable accuracy. Experimental results are presented for five different configurations, including: (1) a robotic wheelchair, (2) a sensor mounted on a person, (3) an Ascending Technologies quadrotor, (4) a Willow Garage PR2, and (5) an RWI B21 wheeled mobile robot platform. The results demonstrate that the system can perform robust localization with 3D information for motions as fast as 1.5 meters per second. The approach is designed to be applicable not just for robotics but other applications such as wearable computing.
  • Robust Egomotion Estimation Using ICP in Inverse Depth Coordinates Authors: Lui, Wen Lik Dennis; Tang, Titus Jia Jie; Drummond, Tom; Li, Wai Ho
    This paper presents a 6 degrees of freedom egomotion estimation method using Iterative Closest Point (ICP) for low cost and low accuracy range cameras such as the Microsoft Kinect. Instead of Euclidean coordinates, the method uses inverse depth coordinates which better conforms to the error characteristics of raw sensor data. Novel inverse depth formulations of point-to-point and point-to-plane error metrics are derived as part of our implementation. The implemented system runs in real time at an average of 28 frames per second (fps) on a standard computer. Extensive experiments were performed to evaluate different combinations of error metrics and parameters. Results show that our system is accurate and robust across a variety of motion trajectories. The point-to-plane error metric was found to be the best at coping with large inter-frame motion while remaining accurate and maintaining real time performance.
  • Online Egomotion Estimation of RGB-D Sensors Using Spherical Harmonics Authors: Osteen, Philip; Owens, Jason; Kessens, Chad C.
    We present a technique to estimate the egomotion of an RGB-D sensor based on rotations of functions defined on the unit sphere. In contrast to traditional approaches, our technique is not based on image features and does not require correspondences to be generated between frames of data. Instead, consecutive functions are correlated using spherical harmonic analysis. An Extended Gaussian Image (EGI), created from the local normal estimates of a point cloud, defines each function. Correlations are efficiently computed using Fourier transformations, resulting in a 3 Degree of Freedom (3-DoF) rotation estimate. An Iterative Closest Point (ICP) process then refines the initial rotation estimate and adds a translational component, yielding a full 6-DoF egomotion estimate. The focus of this work is to investigate the merits of using spherical harmonic analysis for egomotion estimation by comparison with alternative 6-DoF methods. We compare the performance of the proposed technique with that of stand-alone ICP and image feature based methods. As with other egomotion techniques, estimation errors accumulate and degrade results, necessitating correction mechanisms for robust localization. For this report, however, we use the raw estimates; no filtering or smoothing processes are applied. In-house and external benchmark data sets are analyzed for both runtime and accuracy. Results show that the algorithm is competitive in terms of both accuracy and runtime, and future work will aim to
  • Incremental Registration of RGB-D Images Authors: Dryanovski, Ivan; Jaramillo, Carlos; Xiao, Jizhong
    An RGB-D camera is a sensor which outputs range and color information about objects. Recent technological advances in this area have introduced affordable RGB-D devices in the robotics community. In this paper, we present a real-time technique for 6-DoF camera pose estimation through the incremental registration of RGB-D images. First, a set of edge features are computed from the depth and color images. An initial motion estimation is calculated through aligning the features. This initial guess is refined by applying the Iterative Closest Point algorithm on the dense point cloud data. A rigorous error analysis assesses several sets of RGB-D ground truth data via an error accumulation metric. We show that the proposed two-stage approach significantly reduces error in the pose estimation, compared to a state-of-the-art ICP registration technique.
  • An Evaluation of the RGB-D SLAM System Authors: Endres, Felix; Hess, Juergen Michael; Engelhard, Nikolas; Sturm, Jürgen; Cremers, Daniel; Burgard, Wolfram
    We present an approach to simultaneous localization and mapping (SLAM) for RGB-D cameras like the Microsoft Kinect. Our system concurrently estimates the trajectory of a hand-held Kinect and generates a dense 3D model of the environment. We present the key features of our approach and evaluate its performance thoroughly on a recently published dataset, including a large set of sequences of different scenes with varying camera speeds and illumination conditions. In particular, we evaluate the accuracy, robustness, and processing time for three different feature descriptors (SIFT, SURF, and ORB). The experiments demonstrate that our system can robustly deal with difficult data in common indoor scenarios while being fast enough for online operation. Our system is fully available as open-source.
  • Depth Camera Based Indoor Mobile Robot Localization and Navigation Authors: Biswas, Joydeep; Veloso, Manuela
    The sheer volume of data generated by depth cameras provides a challenge to process in real time, in particular when used for indoor mobile robot localization and navigation. We introduce the Fast Sampling Plane Filtering (FSPF) algorithm to reduce the volume of the 3D point cloud by sampling points from the depth image, and classifying local grouped sets of points as belonging to planes in 3D (the "plane filtered" points) or points that do not correspond to planes within a specified error margin (the "outlier" points). We then introduce a localization algorithm based on an observation model that down-projects the plane filtered points on to 2D, and assigns correspondences for each point to lines in the 2D map. The full sampled point cloud (consisting of both plane filtered as well as outlier points) is processed for obstacle avoidance for autonomous navigation. All our algorithms process only the depth information, and do not require additional RGB data. The FSPF, localization and obstacle avoidance algorithms run in real time at full camera frame rates(30Hz) with low CPU requirements(16%). We provide experimental results demonstrating the effectiveness of our approach for indoor mobile robot localization and navigation. We further compare the accuracy and robustness in localization using depth cameras with FSPF vs. alternative approaches that simulate laser rangefinder scans from the 3D data.

Micro and Nano Robots II

  • Motion Control of Tetrahymena Pyriformis Cells with Artificial Magnetotaxis: Model Predictive Control (MPC) Approach Authors: Ou, Yan; Kim, Dal Hyung; Kim, Paul; Kim, MinJun; Julius, Agung
    The use of live microbial cells as microscale robots is an attractive premise, primarily because they are easy to produce and to fuel. In this paper, we study the motion control of magnetotactic Tetrahymena pyriformis cells. Magnetotactic T. pyriformis is produced by introducing artificial magnetic dipole into the cells. Subsequently, they can be steered by using an external magnetic field. We observe that the external magnetic field can only be used to affect the swimming direction of the cells, while the swimming velocity depends largely on the cells’ own propulsion. Feedback information for control is obtained from a computer vision system that tracks the cell. The contribution of this paper is twofold. First, we construct a discrete-time model for the cell dynamics that is based on first principle. Subsequently, we identify the model parameters using the Least Squares approach. Second, we formulate a model predictive approach for feedback control of magnetotactic T. pyriformis. Both the model fitness and the performance of the feedback controller are verified using experimental data.
  • Robust H-Infinity Control for Electromagnetic Steering of Microrobots Authors: Marino, Hamal; Bergeles, Christos; Nelson, Bradley J.
    Electromagnetic systems for in vivo microrobot steering have the potential to enable new types of localized and minimally invasive interventions. Accurate control of microrobots in natural fluids requires precise, high-bandwidth localization and accurate knowledge of the steering system’s parameters. However, current in vivo imaging methodologies, such as fluoroscopy, must be used at low update rates to minimize radiation exposure. Low frame rates introduce localization uncertainties. Additionally, the parameters of the electromagnetic steering system are estimated with inaccuracies. These uncertainties can be addressed with robust H-infinity control, which is investigated in this paper. The controller is based on a linear uncertain dynamical model of the steering system and microrobot. Simulations show that the proposed control scheme accounts for modeling uncertainties, and that the controller can be used for servoing in low viscosity fluids using low frame rates. Experiments in a prototype electromagnetic steering system support the simulations.
  • Magnetic Dragging of Vascular Obstructions by Means of Electrostatic and Antibody Binding Authors: Khorami Llewellyn, Maral; Dario, Paolo; Menciassi, Arianna; Sinibaldi, Edoardo
    Exploitation of miniature robots and microrobots for endovascular therapeutics is a promising approach; besides chemical strategies (typically systemic), topical mechanical approaches exist for obstruction removal, which however produce harmful debris for blood circulation. Magnetic particles (MPs) are also studied for blood clot targeting. We investigated magnetic dragging of clots/debris by means of both electrostatic and antibody binding. We successfully produced magnetotactic blood clots in vitro and experimentally showed that they can be effectively dragged within a fluidic channel. We also exploited a magnetic force model in order to quantitatively analyze the experimental results, up to obtaining an estimate of the relative efficiency between electrostatic and antibody binding. Our study takes a first step towards more realistic in vivo investigations, in view of integration into microrobotic approaches to vascular obstructions removal.
  • Coordination of Droplets on Light-Actuated Digital Microfluidic Systems Authors: Ma, Zhiqiang; Akella, Srinivas
    In this paper we explore the problem of coordinating multiple droplets in light-actuated digital microfluidic systems intended for use as lab-on-a-chip systems. In a light actuated digital microfluidic system, droplets of chemicals are actuated on a photosensitive chip by moving projected light patterns. Our goal is to perform automated manipulation of multiple droplets in parallel on a microfluidic platform. To achieve collision-free droplet coordination while optimizing completion times, we apply multiple robot coordination techniques. We present a mixed integer linear programming formulation for coordinating droplets given their paths. This approach permits arbitrary droplet formations, and coordination of both individual droplets and batches of droplets. We then present a linear time stepwise approach for batch coordination of droplet matrix layouts.
  • Mobility and Kinematic Analysis of a Novel Dexterous Micro Gripper Authors: Xiao, Shunli; Li, Yangmin
    The paper presents the design and analysis of a dexterous micro-gripper with two fingers and each finger has 2-DOF translational movement function. The two fingers can move independently in hundreds of microns' range, and can cooperate with each other to realize complex operation for micro objects. The mobility characteristics and the inverse parallel kinematic model of a single finger are analyzed by resorting to screw theory and compliance and stiffness matrix method, which are validated by finite-element analysis (FEA). Both FEA and the theoretical model have well validated the movement of the fingers moving in translational way, the designed micro gripper can realize a lot of complex functions. Properly selecting the amplification ratio and the stroke of the PZT, we can mount the gripper onto a positioning stage to realize a larger motion range, which will make it be widely used in micro parts assembly and bio-operation systems.

Embodied Intelligence - Complient Actuators

  • A Versatile Biomimetic Controller for Contact Tooling and Tactile Exploration Authors: Jarrasse, Nathanael; burdet, etienne; Ganesh, Gowrishankar; Haddadin, Sami; Albu-Schäffer, Alin
    This article presents a versatile controller that enables various contact tooling tasks with minimal prior knowledge of the tooled surface. The controller is derived from results of neuroscience studies that investigated the neural mechanisms utilized by humans to control and learn complex interactions with the environment. We demonstrate here the versatility of this controller in simulations of cutting, drilling and surface exploration tasks, which would normally require different control paradigms. We also present results on the exploration of an unknown surface with a 7-DOF manipulator, where the robot builds a 3D surface map of the surface profile and texture while applying constant force during motion. Our controller provides a unified control framework encompassing behaviors expected from the different specialized control paradigms like position control, force control and impedance control.
  • Passive Impedance Control of a Multi-DOF VSA-CubeBot Manipulator Authors: Mancini, Michele; Grioli, Giorgio; Catalano, Manuel; Garabini, Manolo; Bonomo, Fabio; Bicchi, Antonio
    This work presents an example of the application of passive impedance control of a variable stiffness manipulator, which shows the actual benefits of variable stiffness in rejecting disturbances without resorting to the closure of a high level feedback loop. In the experiment a 4-DOF manipulator arm, built with the VSA-CubeBot platform, is controlled to hold a pen and draw a circle on an uneven surface. The control is designed calculating joint and stiffness trajectories with a Cartesian approach to the problem, thus designing the optimal workspace stiffness at first. Then, the joint stiffness yielding the closest workspace stiffness is searched for. Experimental results are reported, which agree with the theoretical outcomes, showing that the sub-optimal joints stiffness settings allow the arm to follow the circular trajectory on the uneven surface at best.
  • Optimality Principles in Stiffness Control: The VSA Kick Authors: Garabini, Manolo; Belo, Felipe; Salaris, Paolo; Passaglia, Andrea; Bicchi, Antonio
    The importance of Variable Stiffness Actuators (VSA) in safety and performance of robots has been extensively discussed in the last decade. It has also been shown recently that a VSA brings performance advantages with respect to common actuators. For instance, the solution of the optimal control problem of maximizing the speed of a VSA for impact maximization at a given position with free final time is achieved by applying a control policy that synchronizes stiffness changes with link speed and acceleration. This problem can be regarded as the formalization of the performance of a soccer player’s free kick. In this paper we revisit the impact maximization problem with imposing a new constraint: we want to maximize the velocity of the actuator link at a given position and fixed terminal time - applicable e.g. to maximize performance of a first-time kick. We first study the problem with fixed stiffness and show that under realistic modeling assumptions, there does exist an optimal linear spring for a given link inertia, final time and motor characteristics. Results are validated with experimental tests. We then study optimal control of VSA and show that varying the spring stiffness during the execution of the kick task substantially improves the final speed.
  • Optimal Control for Exploiting the Natural Dynamics of Variable Stiffness Robots Authors: Haddadin, Sami; Huber, Felix; Albu-Schäffer, Alin
    In contrast to common rigid or actively compliant systems, Variable Stiffness Arms are capable of storing potential energy in their joint and convert it into kinetic energy, respectively speed. This capability is well known from humans and is a good example for the outstanding performance of biological systems. However, only since some years intrinsic compliance is considered as a key feature and not a drawback in robot design. Therefore, only very little work has been carried out for exploiting the natural dynamics of elastic arms for such explosive motion sequences. In this paper, we treat the problem of how to optimally achieve maximum link velocity at a given final time for Variable Stiffness Arms. We show that solutions to this problem lead to excitation motions, which enable the robot to move on the link side at much higher speed on the motor side. In particular, the robot uses the dynamic transfer of elastic joint energy into link side kinetic energy for further acceleration. In our work we consider the practically relevant input and state constraints, and give experimental verification of the developed methods on the new DLR Hand-Arm system.
  • The vsaUT-II: A Novel Rotational Variable Stiffness Actuator Authors: Groothuis, Stefan S.; Rusticelli, Giacomo; Zucchelli, Andrea; Stramigioli, Stefano; Carloni, Raffaella
    In this paper, the vsaUT-II, a novel rotational variable stiffness actuator, is presented. As the other designs in this class of actuation systems, the vsaUT-II is characterized by the property that the output stiffness can be changed independently of the output position. It consists of two internal elastic elements and two internal actuated degrees of freedom. The mechanical design of the vsaUT-II is such that the apparent output stiffness can be varied by changing the transmission ratio between the elastic elements and the output. This kinematic structure guarantees that the output stiffness can be changed without changing the potential energy stored internally in the elastic elements. This property is validated in simulations with the port-based model of the system and in experiments, through a proper control law design, on the prototype.
  • pVEJ: A Modular Passive Viscoelastic Joint for Assistive Wearable Robots Authors: Accoto, Dino; Tagliamonte, Nevio Luigi; Carpino, Giorgio; Sergi, Fabrizio; Di Palo, Michelangelo; Guglielmelli, Eugenio
    In complex dynamical tasks human motor control notably exploits the possibility of regulating joints mechanical impedance, both for stability and for energetic optimization purposes. These biomechanical findings should translate in design requirements for wearable robotics joints, which are required to produce adaptable intrinsic viscoelastic behaviors. This paper describes the design of a purely mechanical, rotary, passive ViscoElastic Joint (pVEJ), functionally equivalent to a torsional spring connected in parallel to a rotary viscous damper. The device has a modular design, which allows to modify the stiffness characteristics by replacing cam profiles. Damping coefficient can be also regulated off-line, manually acting on a valve. Prototype performances are characterized using a custom-developed dynamometric test-bed. Results demonstrate the capability of the system to render both the desired stiffness and damping values, in a range of impedance and peak torque compatible to that of wearable robotics for gait assistance.