TechTalks from event: Technical session talks from ICRA 2012

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Control of UAVs

  • Modeling and Control of a Quadrotor UAV with Tilting Propellers Authors: Ryll, Markus; Buelthoff, Heinrich H.; Robuffo Giordano, Paolo
    Standard quadrotor UAVs possess a limited mobility because of their inherent underactuation, i.e., availability of 4 independent control inputs (the 4 propeller spinning velocities) vs. the 6 dofs parameterizing the quadrotor position/orientation in space. As a consequence, the quadrotor pose cannot track an arbitrary trajectory over time (e.g., it can hover on the spot only when horizontal). In this paper, we propose a novel actuation concept in which the quadrotor propellers are allowed to tilt about their axes w.r.t. the main quadrotor body. This introduces an additional set of 4 control inputs which provides full actuation to the quadrotor position/orientation. After deriving the dynamical model of the proposed quadrotor, we formally discuss its controllability properties and propose a nonlinear trajectory tracking controller based on dynamic feedback linearization techniques. The soundness of our approach is validated by means of simulation results.
  • Bilateral Teleoperation of Underactuated Unmanned Aerial Vehicles: The Virtual Slave Concept Authors: Mersha, Abeje Y.; Stramigioli, Stefano; Carloni, Raffaella
    In this paper, we present haptic teleoperation of underactuated unmanned aerial vehicles by providing a multidimensional generalization of the virtual slave concept. The proposed control architecture is composed of high-level and low-level controllers. The high-level controller commands the vehicle to accomplish specific tasks and renders both the state and the environment of the vehicle to the operator through haptic feedback. The low-level controller interprets the command signals from the operator, regulates the dynamics of the vehicle and feeds back its state to the high-level loop. Passivity of the teleoperation loop is always ensured independently of the choice of implementation of the low-level controller and the configuration of the flying hardware by a passivity-enforcing supervisor, which associates every action of the slave with an energy expense that can only be made available from a multi-state energy tank. The effectiveness of the proposed algorithm is illustrated with simulations and experimental tests.
  • Tunable Impedance: A Semi-Passive Approach to Practical Motion Control of Insect-Inspired MAVs Authors: Mahjoubi, Hosein; Byl, Katie
    Research on insect-inspired flapping-wing micro-aerial vehicles (FWMAV) has grown steadily in the past decade, aiming to address unique challenges in morphological construction, force production, and control strategy. In particular, effective methods for motion control still remain an open problem. This paper analyzes the mechanical impedance properties of the joint and their role in rotation of the wing and force production. The results suggest that in addition to previously observed relationship between set point and drag [1], the average lift force is also related to the stiffness of the joint. Furthermore, as long as changes in impedance properties are small, net lift and drag production are almost independent. These relationships are the basis of ‘tunable impedance’ technique, a new approach to force/motion control in FWMAVs. A simple controller designed based on this method is used to simulate various flight maneuvers. The simulated MAV demonstrates exceptional performance, even in presence of measurement noise. This technique requires a fixed stroke profile for both wings, thus allowing to use a single stroke actuator – in a real MAV – with a bandwidth as low as the frequency of flapping. Impedance actuators also prove to have low bandwidth requirements.
  • Learning Hover with Scarce Samples Authors: Lau, Tak Kit; Liu, Yunhui
    Indoor aerial robots are useful in many applications due to their size, agility and ability to hover. However, tweaking a state-feedback controller to fly stably takes either intensive human supervision, or extensive modeling and identification, hence has never been trivial. In this paper, we give a successful flight controller design that can learn from a single demonstration performed by human and hover indoor aerial robots autonomously on maiden flight.
  • A Bio-inspired Active Tail Control Actuator for Nano Air Vehicles Authors: Penskiy, Ivan; Samuel, Paul; Humbert, James Sean; Bergbreiter, Sarah
    The goal of this research is to develop a lightweight, high bandwidth control actuator that can be integrated on a flapping wing nano air vehicle (NAV). Traditional control actuators for air vehicles including DC servomotors and shape memory alloy are either too heavy or too slow to control a fast moving NAV. This paper develops a new bio-inspired active tail mechanism to stabilize an inverted pendulum with the same mass and inertia as the NAV. An analysis of the dynamic model shows a critical angle at which the control actuator can no longer stabilize the pendulum varies significantly with link lengths and mass ratios. Based on this dynamic model, an LQR controller is developed and implemented as a state space controller on a microcontroller based test setup. Using a gyroscope to measure the pendulum’s angular velocity and estimate the angle, the active tail mechanism was able to stabilize the pendulum for over five minutes before falling due to drift in the gyroscope sensor.
  • Indoor Navigation with a Swarm of Flying Robots Authors: Stirling, Timothy; Roberts, James F.; Zufferey, Jean-Christophe; Floreano, Dario
    Swarms of flying robots are promising in many applications due to rapid terrain coverage. However, there are numerous challenges in realising autonomous operation in unknown indoor environments. A new autonomous flight methodology is presented using relative positioning sensors in reference to nearby static robots. The entirely decentralised approach relies solely on local sensing without requiring absolute positioning, environment maps, powerful computation or long-range communication. The swarm deploys as a robotic network facilitating navigation and goal directed flight. Initial validation tests with quadrotors demonstrated autonomous flight within a confined indoor environment, indicating that they could traverse a large network of static robots across expansive environments.

Grasp Planning

  • On the Synthesis of Feasible and Prehensile Robotic Grasps Authors: Rosales Gallegos, Carlos; Suarez, Raul; Gabiccini, Marco; Bicchi, Antonio
    This work proposes a solution to the grasp synthesis problem, which consist of finding the best hand configuration to grasp a given object for a specific manipulation task while satisfying all the necessary constraints. This problem had been divided into sequential sub-problems, including contact region determination, hand inverse kinematics and force distribution, with the particular constraints of each step tackled independently. This may lead to unnecessary effort, such as when one of the problems has no solution given the output of the previous step as input. To overcome this issue, we present a kinestatic formulation of the grasp synthesis problem that introduces compliance both at the joints and the contacts. This provides a proper framework to synthesize a feasible and prehensile grasp by considering simultaneously the necessary grasping constraints, including contact reachability, object restraint, and force controllability. As a consequence, a solution of the proposed model results in a set of hand configurations that allows to execute the grasp using only a position controller. The approach is illustrated with experiments on a simple planar hand using two fingers and an anthropomorphic robotic hand using three fingers.
  • Pose Error Robust Grasping from Contact Wrench Space Metrics Authors: Weisz, Jonathan; Allen, Peter
    Grasp quality metrics which analyze the contact wrench space are commonly used to synthesize and analyze preplanned grasps. Preplanned grasping approaches rely on the robustness of stored solutions. Analyzing the robustness of such solutions for large databases of preplanned grasps is a limiting factor for the applicability of data driven approaches to grasping. In this work, we will focus on the stability of the widely used grasp wrench space epsilon quality metric over a large range of poses in simulation. We examine a large number of grasps from the Columbia Grasp Database for the Barrett hand. We find that in most cases the grasp with the most robust force closure with respect to pose error for a particular object is not the grasp with the highest epsilon quality. We demonstrate that grasps can be reranked grasps by an estimate of the stability of their epsilon quality. We find that the grasps ranked best by this method are successful more often in physical experiments than grasps ranked best by the epsilon quality.
  • Navigation Functions Learning from Experiments: Application to Anthropomorphic Grasping Authors: Filippidis, Ioannis; Kyriakopoulos, Kostas; Artemiadis, Panagiotis
    This paper proposes a method to construct Navigation Functions (NF) from experimental trajectories in an unknown environment. We want to approximate an unknown obstacle function and then use it within an NF. When navigating the same destinations with the experiments, this NF should produce the same trajectories as the experiments. This requirement is equivalent to a partial differential equation (PDE). Solving the PDE yields the unknown obstacle function, expressed with spline basis functions.We apply this new method to anthropomorphic grasping, producing automatic trajectories similar to the observed ones. The grasping experiments were performed for a set of different objects, Principal Component Analysis (PCA) allows reduction of the configuration space dimension, where the learning NF method is then applied.
  • Toward Cloud-Based Grasping with Uncertainty in Shape: Estimating Lower Bounds on Achieving Force Closure with Zero-Slip Push Grasps Authors: Kehoe, Ben; Berenson, Dmitry; Goldberg, Ken
    This paper explores how Cloud Computing can facilitate grasping with shape uncertainty. We consider the most common robot gripper: a pair of thin parallel jaws, and a class of objects that can be modeled as extruded polygons. We model a conservative class of push-grasps that can enhance object alignment. The grasp planning algorithm takes as input an approximate object outline and Gaussian uncertainty around each vertex and center of mass. We define a grasp quality metric based on a lower bound on the probability of achieving force closure. We present a highly-parallelizable algorithm to compute this metric using Monte Carlo sampling. The algorithm uses Coulomb frictional grasp mechanics and a fast geometric test for conservative conditions for force closure. We run the algorithm on a set of sample shapes and compare the grasps with those from a planner that does not model shape uncertainty. We report computation times with single and multi-core computers and sensitivity analysis on algorithm parameters. We also describe physical grasp experiments using the Willow Garage PR2 robot.
  • Combined Grasp and Manipulation Planning As a Trajectory Optimization Problem Authors: Horowitz, Matanya; Burdick, Joel
    Many manipulation planning problems involve several related sub-problems, such as the selection of grasping points on an object, choice of hand posture, and determination of the arm’s configuration and evolving trajectory. Traditionally, these planning sub-problems have been handled separately, potentially leading to sub-optimal, or even infeasible, combinations of the individually determined solutions. This paper formulates the combined problem of grasp contact selection, grasp force optimization, and manipulator arm/hand trajectory planning as a problem in optimal control. That is, the locally optimal trajectory for the manipulator, hand mechanism, and contact locations are determined during the pre-grasping, grasping, and subsequent object transport phase. Additionally, a barrier function approach allows for non-feasible grasps to be optimized, enlarging the region of convergence for the algorithm. A simulation of a simple planar object manipulation task is used to illustrate and validate the approach.

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.