TechTalks from event: Technical session talks from ICRA 2012

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  • Bilateral Teleoperation of Cooperative Manipulators Authors: Aldana, Carlos Iván; Nuno, Emmanuel; Basanez, Luis
    This paper presents an adaptive controller for the bilateral teleoperation of a system composed by a single local manipulator and multiple cooperative remote manipulators handling a common object. First, the nonlinear operational space dynamical behavior, of the complete teleoperation system, is derived and then, under the assumptions that the remote manipulators are rigidly grasping a non-deformable object and that the communications may induce constant time-delays, it is proved that velocities and position-orientation error between the local manipulator end-effector and the object asymptotically converge to zero. Simulations results are included to show the effectiveness of the proposed scheme.
  • Direct Force Reflecting Teleoperation with a Flexible Joint Robot Authors: Tobergte, Andreas; Albu-Schäffer, Alin
    This paper presents a high fidelity force feedback teleoperation control for surgical applications. Advanced control methods, such as flexible joint tracking control and passivity observation, are introduced in the direct force reflecting control architecture. A full state feedback controller of the flexible joint slave robot controls the motor position, velocity, the joint torque, and the torque derivative. The pose of the haptic device and the first three derivatives are observed to generate reference states for the robot control using the robot's inverse dynamics model. Interaction forces of the slave and the environment are measured with a force/torque sensor and directly sent back to the master device. Stability is guaranteed with a passivity observer that monitors the energy in the teleoperation system online and disconnects master and slave if the system operates beyond its stable region. The proposed control architecture is implemented with the sigma.7 haptic device and the MIRO robot. It is experimentally shown, that appropriately considering elasticities with full state reference and control of the slave, increases the dynamic range of the system enabling transparent and stable interaction with hard and soft environments.
  • Dynamic Scaling Interface for Assisted Teleoperation Authors: Munoz, Luis Miguel; Casals, Alicia
    Teleoperation, by adequately adapting computer interfaces, can benefit from the knowledge on human factors and psychomotor models in order to improve the effectiveness and efficiency in the execution of a task. While scaling is one of the performances frequently used in teleoperation tasks that require high precision, such as surgery, this article presents a scaling method that considers the system dynamics as well. The proposed dynamic scaling factor depends on the apparent position and velocity of the robot and targets. Such scaling improves the performance of teleoperation interfaces, thereby reducing user’s workload.
  • A Proportional Plus Damping Injection Controller for Teleoperators with Joint Flexibility and Time-Delays Authors: Nuno, Emmanuel; Sarras, Ioannis; Basanez, Luis; Kinnaert, Michel
    The problem of controlling a rigid bilateral teleoperator with time-delays has been effectively addressed since the late 80's. However, the control of flexible joint manipulators in a bilateral teleoperation scenario is still an open problem. In the present paper we report two versions of a proportional plus damping injection controller that are capable of globally stabilizing a nonlinear bilateral teleoperator with joint flexibility and variable time-delays. The first version controls a teleoperator composed by a rigid local manipulator and a flexible joint remote manipulator and the second version deals with local and remote manipulators with joint flexibility. For both schemes, it is proved that the joint and motor velocities and the local and remote position error are bounded. Moreover, if the human operator and remote environment forces are zero then velocities asymptotically converge to zero and position tracking is established. Simulations are presented to show the performance of the proposed controllers.
  • Stability of Position-Based Bilateral Telemanipulation Systems by Damping Injection Authors: Franken, Michel; Misra, Sarthak; Stramigioli, Stefano
    In this paper two different approaches to guaran- tee stability of bilateral telemanipulation systems are discussed. Both approaches inject damping into the system to guarantee passivity of the interaction with the device in the presence of time delays in the communication channel. The first approach derives tuning rules for a fixed viscous damper, whereas the second approach employs modulated dampers based upon the measured energy exchange with the device and enforces passivity in the time domain. Furthermore, a theoretical min- imum damping injection scheme is sketched that shows that the fixed damping approach is inherently conservative with respect to guaranteeing stability. Experimental results show that both the theoretical minimum damping scheme and a time domain passivity algorithm are successful in stabilizing the telemanipulation system for large time delays with lower gains of the damping elements than derived by the fixed damping injection approach. However, as damping is inherently present in the system, the tuning rules derived from the fixed damping injection approach can be used to identify if a time domain passivity algorithm is needed given boundary conditions on the actual time delays.
  • Bilateral Teleoperation of a Group of UAVs with Communication Delays and Switching Topology Authors: Secchi, Cristian; Franchi, Antonio; Buelthoff, Heinrich H.; Robuffo Giordano, Paolo
    In this paper, we present a passivity-based decentralized approach for bilaterally teleoperating a group of UAVs composing the slave side of the teleoperation system. In particular, we explicitly consider the presence of time delays, both among the master and slave, and within UAVs composing the group. Our focus is on analyzing suitable (passive) strategies that allow a stable teloperation of the group despite presence of delays, while still ensuring high flexibility to the group topology (e.g., possibility to autonomously split or join during the motion). The performance and soundness of the approach is validated by means of human/hardware-in-the-loop simulations (HHIL).

Applied Machine Learning

  • Active Learning from Demonstration for Robust Autonomous Navigation Authors: Silver, David; Bagnell, James; Stentz, Anthony
    Building robust and reliable autonomous navigation systems that generalize across environments and operating scenarios remains a core challenge in robotics. Machine learning has proven a significant aid in this task; in recent years learning from demonstration has become especially popular, leading to improved systems while requiring less expert tuning and interaction. However, these approaches still place a burden on the expert, specifically to choose the best demonstrations to provide. This work proposes two approaches for active learning from demonstration, in which the learning system requests specific demonstrations from the expert. The approaches identify examples for which expert demonstration is predicted to provide useful information on concepts which are either novel or uncertain to the current system. Experimental results demonstrate both improved generalization performance and reduced expert interaction when using these approaches.
  • Tendon-Driven Control of Biomechanical and Robotic Systems: A Path Integral Reinforcement Learning Approach Authors: Rombokas, Eric; Theodorou, Evangelos; Malhotra, Mark; Todorov, Emanuel; Matsuoka, Yoky
    We apply path integral reinforcement learning to a biomechanically accurate dynamics model of the index finger and then to the Anatomically Correct Testbed (ACT) robotic hand. We illustrate the applicability of Policy Improvement with Path Integrals to parameterized and non-parameterized control policies. This method is based on sampling variations in control, executing them in the real world, and minimizing a cost function on the resulting performance. Iteratively improving the control policy based on real-world performance requires no direct modeling of tendon network nonlinearities and contact transitions, allowing improved task performance.
  • Slip Prediction Using Hidden Markov Models: Multidimensional Sensor Data to Symbolic Temporal Pattern Learning Authors: Jamali, Nawid; Sammut, Claude
    We present experiments on the application of machine learning to predicting slip. The sensing information is provided by a force/torque sensor and an artificial finger, which has randomly distributed strain gauges and polyvinylidene fluoride (PVDF) films embedded in silicone resulting in multidimensional time series data on the finger-object contact. An incipient slip is detected by studying temporal patterns in the data. The data is analysed using probabilistic clustering that transforms the data into a sequence of symbols, which is used to train a hidden Markov model (HMM) classifier. Experimental results show that the classifier can predict a slip, at least 100ms before a slip takes place, with an accuracy of 96% on the validation set.
  • Collision-Free State Estimation Authors: Wong, Lawson L.S.; Kaelbling, Leslie; Lozano-Perez, Tomas
    In state estimation, we often want the maximum likelihood estimate of the current state. For the commonly used joint multivariate Gaussian distribution over the state space, this can be efficiently found using a Kalman filter. However, in complex environments the state space is often highly constrained. For example, for objects within a refrigerator, they cannot interpenetrate each other or the refrigerator walls. The multivariate Gaussian is unconstrained over the state space and cannot incorporate these constraints. In particular, the state estimate returned by the unconstrained distribution may itself be infeasible. Instead, we solve a related constrained optimization problem to find a good feasible state estimate. We illustrate this for estimating collision-free configurations for objects resting stably on a 2-D surface, and demonstrate its utility in a real robot perception domain.
  • Fault Detection and Isolation from Uninterpreted Data in Robotic Sensorimotor Cascades Authors: Censi, Andrea; Hakansson, Magnus; Murray, Richard
    One of the challenges in designing the next generation of robots operating in non-engineered environments is that there seems to be an infinite amount of causes that make the sensor data unreliable or actuators ineffective. In this paper, we discuss what faults are possible to detect using zero modeling effort: we start from uninterpreted streams of observations and commands, and without a prior knowledge of a model of the world. We show that in sensorimotor cascades it is possible to define static faults independently of a nominal model. We define an information-theoretic usefulness of a sensor reading and we show that it captures several kind of sensorimotor faults frequently encountered in practice. We particularize these ideas to the case of BDS/BGDS models, proposed in previous work as suitable candidates for describing generic sensorimotor cascades. We show several examples with camera and range-finder data, and we discuss a possible way to integrate these techniques in an existing robot software architecture.
  • Describing and Classifying Spatial and Temporal Contexts with OWL DL in Ubiquitous Robotics Authors: Sgorbissa, Antonio; Scalmato, Antonello; Zaccaria, Renato
    The article describes a system for describing and recognizing spatial and temporal patterns of events. The system is based on an ontology described through the Description Logics formalism and implemented in OWL DL. The approach is different from all other works in the literature since the system does not require an external reasoning engine, but relies only on the base mechanism for ontology classification. Experiments performed in two different scenarios are described, i.e., a Smart Home and a mobile robot for autonomous transportation operating within a partially automated building.


  • Experimental Validation of locomotion efficiency of Worm-like Robots and Contact Compliance Authors: Zarrouk, David; Sharf, Inna; Shoham, Moshe
    Biological vessels are characterized by their substantial compliance and low friction which present a major challenge for crawling robots for minimally invasive medical procedures. Quite a number of studies considered the design and construction of crawling robots, however, very few focused on the interaction between the robots and the flexible environment. In a previous study, we derived the analytical efficiency of worm locomotion as a function of the number of cells, friction coefficients, normal forces and local (contact) tangential compliance. In this paper, we generalize our previous analysis to include dynamic and static coefficients of friction, determine the conditions of locomotion as function of the external resisting forces and experimentally validate our previous and newly obtained theoretical results. Our experimental setup consists of worm robot prototypes, flexible interfaces with known compliance and a Vicon motion capture system to measure the robot positioning. Separate experiments were conducted to measure the tangential compliance of the contact interface which is required for computing the analytical efficiency. The validation experiments are shown to be in clear match with the theoretical predictions. Specifically, the convergence of the tangential deflections to an arithmetic series and the partial and overall loss of locomotion verify the theoretical predictions.
  • Dynamic Turning of 13 Cm Robot Comparing Tail and Differential Drive Authors: Pullin, Andrew; Kohut, Nicholas Joseph; Fearing, Ronald
    Rapid and consistent turning of running legged robots on surfaces with moderate friction is challenging due to leg slip and uncertain dynamics. A tail is proposed as a method to effect turns at higher yaw frequencies than can be obtained by differential velocity drive of alternate sides. Here we introduce a 100 mm scale dynamic robot - OctoRoACH - with differential-drive steering and a low-mass tail to investigate issues of yaw rate control. The robot without tail is under-actuated with only 2 drive motors and mass of 35 grams including all battery and control electronics. For some surface conditions, OctoRoACH can maintain heading or turning rate using only leg velocity control, and a basic rate-gyro-based heading control system can respond to disturbances, with a closed-loop bandwidth of approximately 1 Hz. Using a modified off-the-shelf servo for the tail drive, the robot responds to turning commands at 4 Hz.
  • A Compliant Bioinspired Swimming Robot with Neuro-Inspired Control and Autonomous Behavior Authors: Stefanini, Cesare; Orofino, Stefano; Manfredi, Luigi; Mintchev, Stefano; Marrazza, Stefano; Assaf, Tareq; Capantini, Lorenza; Sinibaldi, Edoardo; Grillner, Sten; Wallén, Peter; Dario, Paolo
    In this paper the development of a bio-robotic platform is described. The robot design exploits biomechanical and neuroscientific knowledge on the lamprey, an eel-like swimmer well studied and characterized thanks to the reduced complexity of its anatomy. The robot is untethered, has a compliant body, muscle-like high efficiency actuators, proprioceptive sensors to detect stretch and stereoscopic vision. Experiments on the platform are reported, including robust and autonomous goal-directed swimming. Extensive experiments have been possible thanks to very high energy efficiency (around five hour continuous operating) the platform is ready to be used as investigation tool for high level motor tasks.
  • Kinematic Design of an Asymmetric In-phase Flapping Mechanism for MAVs Authors: Park, Joon-Hyuk; Yang, Emily; Agrawal, Sunil
    The thorax of an insect has direct flight muscles that can independently control the flapping amplitude, relative phase, and mean position of its left and right wings. This feature allows insects to modulate lateral dynamics during hovering flight, resulting in high flight maneuverability. This paper introduces the development and characterization of a novel flapping mechanism for MAVs, denoted as AIFM (Asymmetric In-phase Flapping Mechanism), that is capable of achieving controlled, asymmetric in-phase wing flapping as inspired by similar features in insects. The system consists of two 4-bar mechanisms that create basic flapping motions and two RRPR mechanisms that control the asymmetric flapping motion. The kinematics of the mechanism was investigated and optimized in such a way that enables the mechanism to produce reliable, in-phase wing motion during asymmetric flapping flight. The kinematics of the wings was evaluated both computationally and experimentally. It was shown that asymmetric wing flapping can be successfully achieved without affecting the in-phase flapping motion.
  • Maintaining Odor Tracking Behavior Using an Established Tracking Direction in a Dynamic Wind Environment Authors: Taylor, Brian; Wu, Dora; Willis, Mark; Quinn, Roger, D.
    The ability to autonomously track a fluid-borne odor has numerous engineering applications and natural occurrences. Engineering systems can use odor-guided navigation in tasks ranging from search and rescue to locating dangerous chemicals. Animals use odors to locate food and mates. For animals in strong unsteady turbulent flow environments where the wind is intermittent and occasionally vanishes, there is an ecological benefit to maintaining wind-driven tracking behavior. This has been shown in experiments performed using moths and cockroaches, where animals that began tracking odor in wind maintained their wind driven tracking behavior and eventually located the source after the wind was shut off during their tracking behavior. Here, we use RoboMoth, a previously developed 3D odor-tracking robot, to replicate these experiments. Our results can aid biologists in understanding how animals track odors in dynamic environments. In engineering, this study provides a first step in a hardware system towards linking odor tracking in strong wind environments to tracking in zero/low flow environments by studying the transition between the two regimes. This can help further engineers’ efforts to design odor-tracking systems capable of negotiating diverse and dynamic environments. Our study of the transition from using the wind as a primary directional cue to relying on odor and an established tracking direction appears to be novel in an engineering context and unique to our work.
  • Brain-inspired Bayesian Perception for Biomimetic Robot Touch Authors: Lepora, Nathan; Sullivan, John C W; Mitchinson, Ben; Pearson, Martin; Gurney, Kevin; Prescott, Tony J
    Studies of decision making in animals suggest a neural mechanism of evidence accumulation for competing percepts according to Bayesian sequential analysis. This model of perception is embodied here in a biomimetic tactile sensing robot based on the rodent whisker system. We implement simultaneous perception of object shape and location using two psychological test paradigms: first, a free-response paradigm in which the agent decides when to respond, implemented with Bayesian sequential analysis; and second an interrogative paradigm in which the agent responds after a fixed interval, implemented with maximum likelihood estimation. A benefit of free-response Bayesian perception is that it allows tuning of reaction speed against accuracy. In addition, we find that large gains in decision performance are achieved with unforced responses that allow null decisions on ambiguous data. Therefore free-response Bayesian perception offers benefits for artificial systems that make them more animal-like in behavior.