TechTalks from event: Technical session talks from ICRA 2012

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Compliance Devices and Control

  • A Position and Stiffness Control Strategy for Variable Stiffness Actuators Authors: Sardellitti, Irene; Medrano-Cerda, Gustavo; Tsagarakis, Nikolaos; Jafari, Amir; Caldwell, Darwin G.
    Variable stiffness actuators (VSAs) have been introduced to improve, at the design level, the safety and the energy efficiency of the new generation of robots that have to interact closely with humans. A wide variety of design solutions have recently been proposed, and a common factor in most of the VSAs is the introduction of a flexible transmission with varying stiffness. This, on the control perspective, usually implies a nonlinear actuation plant with varying dynamics following time-varying parameters, which requires more complex control strategies with respect to those developed for flexible joints with a constant stiffness. For this reason, this paper proposes an approach for controlling the link position and stiffness of a VSA. The link positioning relies on a LQR-based gain scheduling approach useful for continuously adjusting the control effort based on the current stiffness of the flexible transmission. The stiffness perceived at the output link is adjusted to match the varying task requirements through the combination of the positioning gains and the mechanical stiffness. The stability of the overall strategy is briefly discussed. The effectiveness of the controller in terms of tracking performance and stiffness adjustment is verified through experiments on the Actuator with Adjustable Stiffness (AwAS).
  • How Design Can Affect the Energy Required to Regulate the Stiffness in Variable Stiffness Actuators Authors: Jafari, Amir; Tsagarakis, Nikolaos; Sardellitti, Irene; Caldwell, Darwin G.
    Variable stiffness actuators have been developed based on different design solutions which can be arranged into two groups: antagonistic and series design. In both the cases two actuation units are combined with passive elastic elements to adjust both the stiffness and the equilibrium position of the actuated joint. To regulate the stiffness, mechanical work is required to be done which depending on the design principle of the actuator results in certain energy consumption. In this paper different variable stiffness design approaches with different types of springs (linear, quadratic, exponential and cubic) are analyzed and compared with respect to the energy required to regulate the stiffness. The results give some insights about the design parameters which mostly affect the energy consumption for the stiffness adjustment. In this work, it is shown that among different design and spring arrangements, the variable stiffness in series design which uses linear springs with constant pretension, requires the minimum energy consumption to adjust the stiffness.
  • Mechanics and Manipulation of Planar Elastic Kinematic Chains Authors: McCarthy, Zoe; Bretl, Timothy
    In this paper, we study quasi-static manipulation of a planar kinematic chain with a fixed base in which each joint is a linearly-elastic torsional spring. The shape of this chain when in static equilibrium can be represented as the solution to a discrete-time optimal control problem, with boundary conditions that vary with the position and orientation of the last link. We prove that the set of all solutions to this problem is a smooth manifold that can be parameterized by a single chart. For manipulation planning, we show several advantages of working in this chart instead of in the space of boundary conditions, particularly in the context of a sampling-based planning algorithm. Examples are provided in simulation.
  • Simultaneous Optimization of Robot Trajectory and Nonlinear Springs to Minimize Actuator Torque Authors: Schmit, Nicolas; Okada, Masafumi
    In this paper, we consider a robot with nonlinear springs located at each joints and acting in parallel with the actuators. We propose a method to simultaneously design the trajectory of the robot and the force/torque profiles of the springs for an optimal compensation of the gravity and inertial forces. First, we express the trajectory and force/torque profiles of the springs as a Hermite interpolation of a finite number of nodes, then we derive a closed-form solution of the optimal spring design as a function of the trajectory. As a consequence, the initial optimization problem is reduced to a trajectory optimization problem, solved with a numeric algorithm. We show an example of optimal design for a 3-Degree Of Freedom (DOF) serial manipulator. Finally, we show that the nonlinear springs calculated for this manipulator can be technically realized by a non-circular cable spool mechanism.
  • Global Identification of Drive Gains Parameters of Robots Using a Known Payload Authors: Gautier, Maxime; Briot, Sébastien
    Off-line robot dynamic identification methods are based on the use of the Inverse Dynamic Identification Model (IDIM), which calculates the joint forces/torques that are linear in relation to the dynamic parameters, and on the use of linear least squares technique to calculate the parameters (IDIM-LS technique). The joint forces/torques are calculated as the product of the known control signal (the current reference) by the joint drive gains. Then it is essential to get accurate values of joint drive gains to get accurate identification of inertial parameters. In the previous works, it was proposed to identify each gain separately. This does not allow taking into account the dynamic coupling between the robot axes. In this paper the global joint drive gains parameters of all joints are calculated simultaneously. The method is based on the total least squares solution of an over-determined linear system obtained with the inverse dynamic model calculated with available current reference and position sampled data while the robot is tracking one reference trajectory without load on the robot and one trajectory with a known payload fixed on the robot. The method is experimentally validated on an industrial Stäubli TX-40 robot.
  • A Compact, Maneuverable, Underwater Robot for Direct Inspection of Nuclear Power Piping Systems Authors: Mazumdar, Anirban; Lozano, Martin; Fittery, Aaron; Asada, Harry
    There is an increasing need for the inspection of nuclear power plants worldwide. To access complex underwater structures and perform non-destructive evaluation, robots must be tetherless, compact, highly maneuverable, and have a smooth body shape with minimal appendages. A new water jet propulsion system using fluidic valves coupled with centrifugal pumps is developed for precision maneuvering. A hybrid control system that combines continuous pump regulation and discrete Pulse Width Modulation (PWM) of fluidic valves is proposed. This control scheme provides high accuracy, high bandwidth, and flexibility in maneuvering control. First, the functional requirements for nuclear power plant inspection are discussed, followed by the basic design concept of an inspection robot. Miniaturized Coanda-effect valves are designed and built based on CFD and mathematical analysis. The hybrid control system incorporating the pump/valve system is designed and tested. Experimental results illustrate that the hybrid control scheme holds substantial promise and is capable of very precise orientation control. Based on these, a full 4-DOF robot is designed, and its key components are described.

Video Session

  • Robotic Finger Mechanism Equipped Omnidirectional Driving Roller with Two Active Rotational Axes Authors: Tadakuma, Kenjiro; Tadakuma, Riichiro; Higashimori, Mitsuru; Kaneko, Makoto
    This paper describes the finger mechanism with omnidirectional driving roller to realize the two active rotational axes on the surface of the grasped object. As the omnidirectional driving roller, we adopt the Omni-Crawler we developed: the crawler mechanism with circular cross section. This cylinderical tracked unit can be used as the roller and the fingers with this roller can manipulate the grasped object in the arbitrary axes. The basic concept of this finger is proposed.
  • Indoor and Outdoor Parametrized Gait Execution with Modular Snake Robots Authors: Melo, Kamilo; Paez, Laura; parra, carlos
    This video shows the mechanical structure, module length possibilities, skin options and some of the locomotion capabilities, including indoor and outdoor demonstrations of parametrized gaits for a modular snake robot, used to research at Pontificia Universidad Javeriana by the Systems, Intelligence, Robotics and Perception Research group (SIRP).
  • Quick Slip-Turn of HRP-4C on Its Toes Authors: Miura, Kanako; Kanehiro, Fumio; Kaneko, Kenji; Kajita, Shuuji; Yokoi, Kazuhito
    In this video, we present the realization of quick turning motion of a humanoid robot on its toes via slipping between its feet and the floor. A rotation model is described on the basis of our hypothesis that turning via slip occurs as a result of minimizing the power caused by floor friction. Using the model, the trajectory of the center of the foot can be generated to realize the desired rotational angle. Toe joints are used to realize quicker turning motion, while avoiding excessive motor load due to frictional torque. Quick slip-turn motion with toe support is successfully demonstrated using a humanoid robot HRP-4C.
  • Flight Stability in Aerial Redundant Manipulators Authors: Korpela, Christopher M.; Danko, Todd; McNeil, Clayton; Pisch, Robert; Oh, Paul Y.
    Ongoing efforts toward mobile manipulation from an aerial vehicle are presented. Recent tests and results from a prototype rotorcraft have shown that our hybrid structure increases stability during flight and manipulation. Since UAVs require significant setup time, suitable testing locations, and have tendencies to crash, we developed an aerial manipulation test and evaluation environment that provides controllable and repeatable experiments. By using force feedback techniques, we have designed multiple, dexterous, redundant manipulators that can grasp objects such as tools and small objects. These manipulators are controlled in concert with an emulated aerial platform to provide hovering stability. The manipulator and aircraft flight control are tightly coupled to facilitate grasping without large perturbations in the end-effector.
  • Study on the Omnidirectional Driving Gear Mechanism Authors: Tadakuma, Kenjiro; Tadakuma, Riichiro; Ioka, Kyohei; Kudo, Takeshi; Takagi, Minoru; Tsumaki, Yuichi; Higashimori, Mitsuru; Kaneko, Makoto
    As ordinary dual-axis driving mechanisms in X-Y directions, for example, commercially available X-Y stages with ball screws are familiar. However, such driving mechanisms have two stages, namely both upper and lower linear actuators, the latter of which must generate sufficient thrust to carry large weights, including that of the upper actuator mechanism, which has hampered efforts to achieve suitably fast and smooth driving motion due to the inertial force effect. It is also difficult to achieve a small and slimline driving mechanism with such overlapping two-stage structure. In these ordinary two-stage driving mechanisms, the motion of the X-Y stage can be disturbed by the cords of the upper actuator. In this research, we have considered the abovementioned problems, and propose a new omnidirectional driving gear mechanism that enhances its driving area from the normal X-Y plane to convex and concave curved surfaces respectively, and even various combinations of both. The smoothness of basic omnidirectional motion and effectiveness of the driving method of this proposed omnidirectional driving gear mechanism have been confirmed with several experiments involving our setups.
  • Over-Tube Apparatus for Increasing the Capabilities of an Articulated Robotic Probe Authors: Degani, Amir; Tully, Stephen; Zubiate, Brett; Choset, Howie
    This video elaborates on a new active and controllable over-tube addition to the highly articulated robotic probe; the HARP. This over-tube allows the current HARP mechanism to double its overall length and allows it to perform more complex tasks. We explain the design concept of the current HARP and the novel over-tube mechanism and show two proof-of-concept experiments demonstrating the use of the active over-tube.
  • Video Summary of D.R.O.P. the Durable Reconnaissance and Observation Platform Authors: McKenzie, Clifford; Parness, Aaron
    This video introduces a small, new reconnaissance robot that can climb concrete surfaces up to 85 degrees at a rate of 25cm/s, make rapid horizontal to vertical transitions, carry an audio/visual payload, and survive impacts from 3m. The robot can travel over 45 cm/s on flat ground, and turn in place. The Durable Reconnaissance and Observation Platform, D.R.O.P., is manufactured using a combination of selective laser sintering (SLS) and shape deposition manufacturing (SDM) techniques. The enabling feature of DROP is the use of microspines in a rotary configuration, increasing climbing and walking speed over previous microspine-based robots by more than 5x.
  • Worms, Waves and Robots Authors: Boxerbaum, Alexander; Horchler, Andrew; Shaw, Kendrick; Chiel, Hillel; Quinn, Roger, D.
    The Biologically Inspired Robotics group at Case Western Reserve University has developed several innovative designs for a new kind of robot that uses peristalsis, the method of locomotion used by earthworms. Unlike previous wormlike robots, our concept uses a continuously deformable outer mesh that interpolates the body position between discrete actuators. Here, we summarize our progress with this soft hyper-redundant robot.
  • Capture, Recognition and Imitation of Anthropomorphic Motion Authors: hak, sovannara; Mansard, Nicolas; Ramos, Oscar E.; Saab, Layale; Stasse, Olivier
    We present our works in generation, recognition and editing of anthropomorphic motion using the stack of tasks framework. It is based on the task function formalism classically used for motion generation. The task spaces are suitable to perform motion analysis and task recognition because the tasks are described in those spaces. The reference behaviors are originated from human trajectories. Specific tasks are then integrated to retarget and to edit the reference motion in order to respect the dynamic constraints, the limits of the robot and the general aspect.
  • Automated Biomanipulation of Single Cells Authors: Steager, Edward; Sakar, Mahmut Selman; Magee, Ceridwen; Kennedy III, Monroe; Cowley, Anthony; Kumar, Vijay
    Transport of individual cells or chemical payloads on a subcellular scale is an enabling tool for the study of cellular communication, cell migration, and other localized phenomena. We present a magnetically actuated robotic system for the fully automated manipulation of cells and microbeads. Our strategy uses autofluorescent robotic transporters and fluorescently labeled microbeads to aid tracking and control in optically obstructed environments. We demonstrate automated delivery of microbeads infused with chemicals to specified positions on neurons.
  • Correct High-Level Robot Control from Structured English Authors: Jing, Gangyuan; Finucane, Cameron; Raman, Vasumathi; Kress-Gazit, Hadas
    The Linear Temporal Logic MissiOn Planning (LTLMoP) toolkit is a software package designed to generate a controller that guarantees a robot satisfies a task specification written by the user in structured English. The controller can be implemented on either a simulated or physical robot. This video illustrates the use of LTLMoP to generate a correct-by-construction robot controller. Here, an Aldebaran Nao humanoid robot carries out tasks as a worker in a simplified grocery store scenario.
  • Learning to Place Objects: Organizing a Room Authors: Basu, Gaurab; Jiang, Yun; Saxena, Ashutosh
    In this video, we consider the task of a personal robot organizing a room by placing objects stably as well as in semantically preferred locations. While this includes many sub-tasks such as grasping the objects, moving to a placing position, localizing itself and placing the object in a proper location and orientation, it is the last problem-how and where to place objects-is our focus in this work and has not been widely studied yet. We formulate the placing task as a learning problem. By computing appearance and shape features from the input (point clouds) that can capture stability and semantics, our algorithm can identify good placements for multiple objects. In this video, we put together the placing algorithm with other sub-tasks to enable a robot organizing a room in several scenarios, such as loading a bookshelf, a fridge, a waste bin and blackboard with various objects.
  • Demonstrations of Gravity-Independent Mobility and Drilling on Natural Rock Using Microspines Authors: Parness, Aaron; Frost, Matthew; King, Jonathan; Thatte, Nitish
    The video presents microspine-based anchors being developed for gripping rocks on the surfaces of comets and asteroids, or for use on cliff faces and lava tubes on Mars. Two types of anchor prototypes are shown on supporting forces in all directions away from the rock; >160 N tangent, >150 N at 45, and >180 N normal to the surface of the rock. A compliant robotic ankle with two active degrees of freedom interfaces these anchors to the Lemur IIB robot for future climbing trials. Finally, a rotary percussive drill is shown coring into rock regardless of gravitational orientation. As a harder-than-zero-g proof of concept, inverted drilling was performed creating 20mm diameter boreholes 83 mm deep in vesicular basalt samples while retaining 12 mm diameter rock cores in 3-6 pieces.
  • Creating and Using RoboEarth Object Models Authors: Di Marco, Daniel; Koch, Andreas; Zweigle, Oliver; Häussermann, Kai; Schießle, Björn; Levi, Paul; Galvez Lopez, Dorian; Riazuelo, Luis; Civera, Javier; Montiel, J.M.M; Tenorth, Moritz; Perzylo, Alexander Clifford; Waibel, Markus
    This work introduces a way to build up and use an extensive sensor-independent object model database. In a first step, a cost-effective and computationally cheap way to create colored point cloud models from common household objects by using a Microsoft Kinect camera is presented. Those object models are stored in a world-wide accessible, distributed database called RoboEarth. Finally, the models are used for recognizing the corresponding objects with any kind of camera. In the presented implementation the demonstration was done with both a Kinect and common RGB cameras.
  • Dexterous Manipulation with Underactuated Fingers: Flip-And-Pinch Task Authors: Odhner, Lael; Ma, Raymond; Dollar, Aaron
    This video demonstrates the use of an underactuated robotic hand modified for the flip-and-pinch task to pick up thin objects from a table surface. Though well-suited for power-grasping, underactuated hands have difficulty with pinch-grasping and precision motions. We introduce a repeatable and robust method by which an underactuated hand flips thin objects off the table into a stable pinch grasp. We explain why this task is quasi-static and robust for a wide range of object dimensions.
  • Beyond Classical Teleoperation: Assistance, Cooperation, Data Reduction, and Spatial Audio Authors: Schauß, Thomas; Passenberg, Carolina; Stefanov, Nikolay; Feth, Daniela; Vittorias, Iason; Peer, Angelika; Hirche, Sandra; Buss, Martin; Rothbucher, Martin; Diepold, Klaus; Kammerl, Julius; Steinbach, Eckehard
    In this video we present a teleoperation system which is capable of solving complex tasks in human-sized wide area environments. The system consists of two mobile teleoperators controlled by two operators, and offers haptic, visual, and auditory feedback. The task examined here, consists of repairing a robot by removing a computer and replacing a defective hard-drive. To cope with the complexity of such a task, we go beyond classical teleoperation by integrating several advanced software algorithms into the system.
  • Geo-Referenced 3D Reconstruction: Fusing Public Geographic Data and Aerial Imagery Authors: Maurer, Michael; Rumpler, Markus; Wendel, Andreas; Hoppe, Christof; Irschara, Arnold; Bischof, Horst
    Abstract—We present an image-based 3D reconstruction pipeline for acquiring geo–referenced semi–dense 3D models. Multiple overlapping images captured from a micro aerial vehicle platform provide a highly redundant source for multiview reconstructions. Publicly available geo–spatial information sources are used to obtain an approximation to a digital surface model (DSM). Models obtained by the semi–dense reconstruction are automatically aligned to the DSM to allow the integration of highly detailed models into the original DSM and to provide geographic context.

AI Reasoning Methods

  • An Adaptive Nonparametric Particle Filter for State Estimation Authors: Wang, Yali; Chaib-draa, Brahim
    Particle filter is one of the most widely applied stochastic sampling tools for state estimation problems in practice. However, the proposal distribution in the traditional particle filter is the transition probability based on state equation, which would heavily affect estimation performance in that the samples are blindly drawn without considering the current observation information. Additionally, the fixed particle number in the typical particle filter would lead to wasteful computation, especially when the posterior distribution greatly varies over time. In this paper, an advanced adaptive nonparametric particle filter is proposed by incorporating gaussian process based proposal distribution into KLD-Sampling particle filter framework so that the high-qualified particles with adaptively KLD based quantity are drawn from the learned proposal with observation information at each time step to improve the approximation accuracy and efficiency. Our state estimation experiments on univariate nonstationary growth model and two-link robot arm show that the adaptive nonparametric particle filter outperforms the existing approaches with smaller size of particles.
  • Online Semantic Exploration of Indoor Maps Authors: Liu, Ziyuan; Chen, Dong; v. Wichert, Georg
    In this paper we propose a method to extract an abstracted floor plan from typical grid maps using Bayesian reasoning. The result of this procedure is a probabilistic generative model of the environment defined over abstract concepts. It is well suited for higher-level reasoning and communication purposes. We demonstrate the effectiveness of the approach through real-world experiments.
  • Game Solving for Industrial Automation and Control Authors: Cheng, Chih-Hong; Buckl, Christian; Knoll, Alois; Geisinger, Michael
    An ongoing effort within the community of verification and program analysis is to raise the level of abstraction in programming by automatic synthesis. In this paper, we demonstrate how our synthesis engine GAVS+ achieves this goal by automatically creating control code for the FESTO modular production system. The overall approach is model-driven: we reinterpret planning domain definition language (PDDL) (as a design contract) to model two-player games played between control and environment, such that users can describe (i) basic abilities of hardware components, including sensors (as environment moves) and actuators (as control moves), (ii) topologies how components are interconnected, and (iii) desired specification under a restricted class of linear temporal logic. The model is processed by our game-based synthesis engine, and from which intermediate code is generated. By mapping each behavioral-level action to a sequence of low-level PLC control commands, we transform the intermediate code to an executable program. The efficiency of our engine enables to synthesize every scenario presented in this paper within seconds. When the specification evolves, this implies a huge time-gain compared to manual code modification.
  • Learning Relational Affordance Models for Robots in Multi-Object Manipulation Tasks Authors: Moldovan, Bogdan; Moreno, Plinio; van Otterlo, Martijn; Santos-Victor, José; De Raedt, Luc
    Affordances define the action possibilities on an object in the environment and in robotics they play a role in basic cognitive capabilities. Previous works have focused on affordance models for just one object even though in many scenarios they are defined by configurations of multiple objects that interact with each other. We employ recent advances in statistical relational learning to learn affordance models in such cases. Our models generalize over objects and can deal effectively with uncertainty. Two-object interaction models are learned from robotic interaction with the objects in the world and employed in situations with arbitrary numbers of objects. We illustrate these ideas with experimental results of an action recognition task where a robot manipulates objects on a shelf.
  • Abstract Planning for Reactive Robots Authors: Joshi, Saket; Schermerhorn, Paul; Khardon, Roni; Scheutz, Matthias
    Hybrid reactive-deliberative architectures in robotics combine reactive sub-policies for fast action execution with goal sequencing and deliberation. The need for replanning, however, presents a challenge for reactivity and hinders the potential for guarantees about the plan quality. In this paper, we argue that one can integrate abstract planning provided by symbolic dynamic programming in first order logic into a reactive robotic architecture, and that such an integration is in fact natural and has advantages over traditional approaches. In particular, it allows the integrated system to spend off-line time planning for a policy, and then use the policy reactively in open worlds, in situations with unexpected outcomes, and even in new environments, all by simply reacting to a state change executing a new action proposed by the policy. We demonstrate the viability of the approach by integrating the FODD-Planner with the robotic DIARC architecture showing how an appropriate interface can be defined and that this integration can yield robust goal-based action execution on robots in open worlds.
  • Searching Objects in Large-Scale Indoor Environments: A Decision-Theoretic Approach Authors: Kunze, Lars; Beetz, Michael; Saito, Manabu; Azuma, Haseru; Okada, Kei; Inaba, Masayuki
    Many of today's mobile robots are supposed to perform everyday manipulation tasks autonomously. However, in large-scale environments, a task-related object might be out of the robot's reach. Hence, the robot first has to search for the object in its environment before it can perform the task. In this paper, we present a decision-theoretic approach for searching objects in large-scale environments using probabilistic environment models and utilities associated with object locations. We demonstrate the feasibility of our approach by integrating it into a robot system and by conducting experiments where the robot is supposed to search different objects with various strategies in the context of fetch-and-delivery tasks within a multi-level building.