TechTalks from event: Technical session talks from ICRA 2012

Conference registration code to access these videos can be accessed by visiting this link: PaperPlaza. Step-by-step to access these videos are here: step-by-step process .
Why some of the videos are missing? If you had provided your consent form for your video to be published and still it is missing, please contact

Octopus-Inspired Robotics

  • A General Mechanical Model for Tendon-Driven Continuum Manipulators Authors: Renda, Federico; Laschi, Cecilia
    Recently, continuum manipulators have drawn a lot of interest and effort from the robotic community, nevertheless control and modeling of such manipulators are still a challenging task especially because they require a continuum approach. In this paper, a general mechanical model with a geometrically exact approach for tendon-driven continuum manipulators is presented. This model can be applied to a wide range of manipulators thanks to the generality of the parameters which can be set. The approach proposed could as well be a powerful tool for developing the control strategy. The model is also capable of properly simulating the couple tendon drive, because it takes into account the torsion of the robot arm rather than neglecting it, as it is common practice in other existing models.
  • A Two Dimensional Inverse Kinetics Model of a Cable Driven Manipulator Inspired by the Octopus Arm Authors: Giorelli, Michele; Renda, Federico; Calisti, Marcello; Arienti, Andrea; Ferri, Gabriele; Laschi, Cecilia
    Control of soft robots remains nowadays a big challenge, as it does in the larger category of continuum robots. In this paper a direct and inverse kinetics models are described for a non-constant curvature structure. A major effort has been put recently in modelling and controlling constant curvature structures, such as cylindrical shaped manipulators. Manipulators with non-constant curvature, on the other hand, have been treated with a piecewise constant curvature approximation. In this work a non-constant curvature manipulator with a conical shape is built, taking inspiration from the anatomy of the octopus arm. The choice of a conical shape manipulator made of soft material is justified by its enhanced capability in grasping objects of different sizes. A different approach from the piecewise constant curvature approximation is employed for direct and inverse kinematics model. A continuum geometrically exact approach for direct kinetics model and a Jacobian method for inverse case are proposed. They are validated experimentally with a prototype soft robot arm moving in water. Results show a desired tip position in the task-space can be achieved automatically with a satisfactory degree of accuracy.
  • Characterizing the Stiffness of a Multi-Segment Flexible Arm During Motion Authors: Held, David; Yekutieli, Yoram; Flash, Tamar
    A number of robotic studies have recently turned to biological inspiration in designing control schemes for flexible robots. Examples of such robots include continuous manipulators inspired by the octopus arm. However, the control strategies used by an octopus in moving its arms are still not fully understood. Starting from a dynamic model of an octopus arm and a given set of muscle activations, we develop a simulation technique to characterize the stiffness throughout a motion and at multiple points along the arm. By applying this technique to reaching and bending motions, we gain a number of insights that can help a control engineer design a biologically inspired impedance control scheme for a flexible robot arm. The framework developed is a general one that can be applied to any motion for any dynamic model. We also propose a theoretical analysis to efficiently estimate the stiffness analytically given a set of muscle activations. This analysis can be used to quickly evaluate the stiffness for new static configurations and dynamic movements.
  • Robotic Underwater Propulsion Inspired by the Octopus Multi-Arm Swimming Authors: Sfakiotakis, Michael; Kazakidi, Asimina; Pateromichelakis, Nikolaos; Ekaterinaris, John A.; Tsakiris, Dimitris
    The multi-arm morphology of octopus-inspired robotic systems may allow their aquatic propulsion, in addition to providing manipulation functionalities, and enable the development of flexible robotic tools for underwater applications. In the present paper, we consider the multi-arm swimming behavior of the octopus, which is different than their, more usual, jetting behavior, and is often used to achieve higher propulsive speeds, e.g., for chasing prey. A dynamic model of a robot with a pair of articulated arms is employed to study the generation of this mode of propulsion. The model includes fluid drag contributions, which we support by detailed Computational Fluid Dynamic analysis. To capture the basic characteristics of octopus multi-arm swimming, a sculling mode is proposed, involving arm oscillations with an asymmetric speed profile. Parametric simulations were used to identify the arm oscillation characteristics that optimize propulsion for sculling, as well as for undulatory arm motions. Tests with a robotic prototype in a water tank provide preliminary validation of our analysis.
  • Developing Sensorized Arm Skin for an Octopus Inspired Robot Authors: Hou, Jinping; Bonser, Richard
    soft skin artefacts made of knitted nylon reinforced silicon rubber were fabricated mimicking octopus skin. A combination of ecoflex 0030 and 0010 were used as matrix of the composite to obtain the right stiffness for the skin artefacts. Material properties were characterised using static uniaxial tension and scissors cutting tests. Two types of tactile sensors were developed to detect normal contact; one used quantum tunnelling composite materials and the second was fabricated from silicone rubber and a conductive textile. Sensitivities of the sensors were tested by applying different modes of loading and the soft sensors were incorporated into the skin prototype. Passive suckers were developed and tested against squid suckers. An integrated skin prototype with embedded deformable sensors and attached suckers developed for the arm of an octopus inspired robot is also presented.
  • Artificial Adhesion Mechanisms Inspired by Octopus Suckers Authors: Tramacere, Francesca; Beccai, Lucia; Mattioli, Fabio; Sinibaldi, Edoardo; Mazzolai, Barbara
    We present the design and development of novel suction cups inspired by the octopus suckers. Octopuses use suckers for remarkable tasks and they are capable to obtain a good reversible wet adhesion on different substrates. We investigated the suckers morphology that allow octopus to attach them to different wet surfaces to obtain the benchmarks for new suction cups showing similar performances. The investigation was performed by using non-invasive techniques (i.e. ultrasonography and magnetic resonance imaging). We acquired images of contiguous sections of octopus suckers, which were used to make a 3D reconstruction aimed to obtain a CAD model perfectly equivalent to the octopus sucker in terms of sizes and anatomical proportion. The 3D information was used to develop the first passive prototypes of the artificial suction cups made in silicone. Then, in accordance with Kier and Smith’s octopus adhesion model, we put in tension the water volume in the interior chamber of the artificial suction cup to obtain suction. The characterization of the passive sucker was addressed by measuring both the differential pressure between external and internal water volume of suction cup (~ 105) and the pull-off force applied to detach the substrates from the suction cup (~ 8N).

Soft Tissue Interaction

  • Novel Indentation Depth Measuring System for Stiffness Characterization in Soft Tissue Palpation Authors: Wanninayake, Indika Bandara; Althoefer, Kaspar; Seneviratne, lakmal
    This paper presents a novel approach to measuring the indentation depth of a stiffness sensor in real time during a soft tissue palpation activity. The proposed system is integrated into a stiffness probe and is designed to intra-operatively aid the surgeon to rapidly identify the tissue abnormalities with minimum measurement inaccuracies due to tissue surface profile variations. Stiffness probe and the associated surface profile sensors are pneumatic and the newly designed system can concurrently measure the indentation depth and surface profile variations while sliding over the soft tissues in any direction in a near frictionless manner. With the pneumatic pressure maintained constant, the displacement of the sensing element is a direct function of the stiffness of the tissue under investigation. The sensor has a tunable force range and the indentation force can be adjusted externally to match tissue limitations. The prototype of the new design of stiffness probe was calibrated and tested on silicone blocks simulating soft tissue. The results show that this sensor can measure indentation depth more accurately than air cushion probe alone. The structure, working principle, and a mathematical model for this new design are described.
  • Robotic Compression of Soft Tissue Authors: Nia Kosari, Sina; Ramadurai, Srikrishnan; Chizeck, Howard; Hannaford, Blake
    This paper investigates automation of soft tissue compression for robot-assisted surgery. This is a fundamental task in surgery and includes interaction with a variety of tissues with unknown properties. In addition, due to sterilization and size constraints the use of contact force and position sensors are often avoided in surgical applications. We propose an Adaptive Model Predictive Control approach for execution of given tool trajectories in contact with unknown tissues in the absence of contact measurements. The Unscented Kalman Filter is employed in advance of system operation to identify the dynamics of a cable driven manipulator. These dynamics are then used to estimate contact force and position in free motion and in contact with tissue. An optimal control problem for automating tissue compression is formulated and is solved in real-time using Differential Dynamic Programming with Automatic Differentiation. The proposed methods are evaluated in experiments on an artificial tissue sample with unknown properties.
  • Soft Tissue Force Control Using Active Observers and Viscoelastic Interaction Model Authors: Moreira, Pedro; Liu, Chao; Zemiti, Nabil; Poignet, Philippe
    Controlling the interaction between the robot and living soft tissues has became an important issue as the number of robots inside the operating room increases. Many research works have been done in order to control this interaction. Nowadays, researches are running in force control for helping surgeons in medical procedures such as motion compensation in beating heart surgeries and tele-operation systems with haptic feedback. The viscoelasticity property of the interaction between organ tissue and robotic instrument further complicates the force control design which is much easier in other applications by assuming the interaction model to be elastic (industry, stiff object manipulation, etc.). In order to increase the performance of a model based force control, this work presents a force control scheme using Active Observer (AOB) based on a viscoelastic interaction model. The control scheme has shown to be stable through theoretical analysis and its performance was evaluated and compared with a control scheme based on a classical elastic model through experiments, showing that a more realistic model can increases the performance of the force control.
  • Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation Data Authors: Boonvisut, Pasu; Jackson, Russell; Cavusoglu, M. Cenk
    Robotic motion planning algorithms used for task automation in robotic surgical systems rely on availability of accurate models of target soft tissue's deformation. Relying on generic tissue parameters in constructing the tissue deformation models is problematic; because, biological tissues are known to have very large (inter- and intra-subject) variability. A priori mechanical characterization (e.g., uniaxial bench test) of the target tissues before a surgical procedure is also not usually practical. In this paper, a method for estimating mechanical parameters of soft tissue from sensory data collected during robotic surgical manipulation is presented. The method uses force data collected from a multiaxial force sensor mounted on the robotic manipulator, and tissue deformation data collected from a stereo camera system. The tissue parameters are then estimated using an inverse finite element method. The effects of measurement and modeling uncertainties on the proposed method are analyzed in simulation. The results of experimental evaluation of the method are also presented.
  • Modeling of Needle-Tissue Interaction Forces During Surgical Suturing Authors: Jackson, Russell; Cavusoglu, M. Cenk
    This paper presents a model of needle tissue interaction forces that a rigid suture needle experiences during surgical suturing. The needle-tissue interaction forces are modeled as the sum of lumped parameters. The model has three main components; friction, tissue compression, and cutting forces. The tissue compression force uses the area that the needle sweeps out during a suture to estimate both the force magnitude and force direction. The area that the needle sweeps out is a direct result of driving the needle in a way that does not follow the natural curve of the needle. The friction force is approximated as a static friction force along the shaft of the needle. The cutting force acts only on the needle tip. The resulting force and torque model is experimentally validated using a tissue phantom. These results indicate that the proposed lumped parameter model is capable of accurately modeling the forces experienced during a suture.
  • Modeling of a Steerable Catheter Based on Beam Theory Authors: Khoshnam, Mahta; Azizian, Mahdi; Patel, Rajnikant V.
    Catheter-based cardiac ablation is an interventional treatment for heart arrhythmias. Pull-wire steerable catheters are guided to the heart chambers through the vasculature in order to deliver energy to destroy faulty electrical pathways in the heart. The effectiveness of this treatment is dependent on the accuracy of positioning the catheter tip at the target location and also on maintaining contact with the target while the heart is beating. Therefore, it is desirable to perform hybrid force/position control of the catheter tip. We have studied the problem of modeling the distal part of a steerable catheter using beam theory and have developed and validated a static force-deflection model through extensive experiments. It is shown that the model can estimate the shape of the bending section of a catheter using force information and without requiring any knowledge of the catheter’s internal structure.

Pose Estimation

  • Invariant Momentum-Tracking Kalman Filter for Attitude Estimation Authors: Persson, Sven Mikael; Sharf, Inna
    This paper presents the development, simulation and experimental testing of a non-linear Kalman filter for attitude estimation. This non-linear filter is able to conserve the invariants of the Kalman filter, i.e., the expectations on state estimates and their covariances, by operating in the Lie algebra of SO(3) and along the trajectory of evolving angular momentum. The main feature of this novel discrete-time filter is that the linearization of the Gaussian uncertainty around these permanent trajectories leads to a locally optimal Kalman gain matrix. Results confirm that this Invariant Momentum-tracking Kalman Filter (IMKF) out-performs state-of-the-art approaches such as the Extended Kalman Filter (EKF), and Invariant Extended Kalman Filter (IEKF). At very-low sampling rates, EKFs suffer from divergence as the uncertainty propagation is corrupted by the underlying system approximations. The IMKF suffers no such problems according to the theoretical developments and results reported here.
  • Complementary Filtering Approach to Orientation Estimation Using Inertial Sensors Only Authors: Kubelka, Vladimir; Reinstein, Michal
    Precise and reliable estimation of orientation plays crucial role for any mobile robot operating in unknown environment. The most common solution to determination of the three orientation angles: pitch, roll, and yaw, relies on the Attitude and Heading Reference System (AHRS) that exploits inertial data fusion (accelerations and angular rates) with magnetic measurements. However, in real world applications strong vibration and disturbances in magnetic field usually cause this approach to provide poor results. Therefore, we have devised a new approach to orientation estimation using inertial sensors only. It is based on modified complementary filtering and was proved by precise laboratory testing using rotational tilt platform as well as by robot field-testing. In the final, the algorithm well outperformed the commercial AHRS solution based on magnetometer aiding.
  • Design of Complementary Filter for High-Fidelity Attitude Estimation Based on Sensor Dynamics Compensation with Decoupled Properties Authors: Masuya, Ken; Sugihara, Tomomichi; Yamamoto, Motoji
    A high-fidelity attitude estimation technique for wide and irregular movements is proposed, in which heterogeneous inertial sensors are combined in complementary way. Although the working frequency ranges of each sensor are not necessarily complementary, inverse sensor models are utilized in order to restore the original movements. In the case of 3D rotation, the sensor dynamics displays a highly nonlinear property. Even if it is approximated by a linear system, the inverse model of a sensor tends to be non-proper and unstable. An idea is to decouple it into the dynamics compensation part approximated by a linear transfer function and the strictly nonlinear coordinate transformation part. Bandpass filters inserted before the coordinate transformation guarantee that the total transfer function becomes proper and stable. Particularly, the differential operator of a high-pass filter cancels the integral operator included in the dynamics compensation of the rate gyroscope, which causes instability. The proposed method is more beneficial than Kalman filter in terms of the implementation since it facilitates a systematic design of the filter.
  • A Low-Cost and Fail-Safe Inertial Navigation System for Airplanes Authors: Leutenegger, Stefan; Siegwart, Roland
    A typical Inertial Navigation System (INS) fuses acceleration and angular rate readings with aiding measurements obtained by GPS and a compass. Here we present a robust state estimation framework based on the Extended Kalman Filter (EKF) applied to low-cost electronics typically installed on-board small unmanned airplanes. It uses airspeed measurements as a backup operation mode replacing GPS updates when temporarily unavailable. We demonstrate the applicability of the proposed approach to real-world scenarios using a challenging dataset recorded on-board a manned glider including long-term circling. A comparison between the normal operation mode and the backup solution reveals minimal difference between the respective orientation estimates, a position error growth sub-linear with time during GPS outage and a seamless transition back to GPS-based operation.
  • Robust Multi-Sensor, Day/Night 6-DOF Pose Estimation for a Dynamic Legged Vehicle in GPS-Denied Environments Authors: Ma, Jeremy; susca, sara; Bajracharya, Max; Matthies, Larry; Malchano, Matthew; Wooden, David
    We present a real-time system that enables a highly capable dynamic quadruped robot to maintain an accurate 6-DOF pose estimate (better than 0.5m over every 50m traveled) over long distances traversed through complex, dynamic outdoor terrain, during day and night, in the presence of camera occlusion and saturation, and occasional large external disturbances, such as slips or falls. The system fuses a stereo-camera sensor, inertial measurement units (IMU), and leg odometry with an Extended Kalman Filter (EKF) to ensure robust, low-latency performance. Extensive experimental results obtained from multiple field tests are presented to illustrate the performance and robustness of the system over hours of continuous runs over hundreds of meters of distance traveled in a wide variety of terrains and conditions.
  • Global Pose Estimation with Limited GPS and Long Range Visual Odometry Authors: Rehder, Joern; Gupta, Kamal; Nuske, Stephen; Singh, Sanjiv
    Here we present an approach to estimate the global pose of a vehicle in the face of two distinct problems; first, when using stereo visual odometry for relative motion estimation, a lack of features at close range causes a bias in the motion estimate. The other challenge is localizing in the global coordinate frame using very infrequent GPS measurements. Solving these problems we demonstrate a method to estimate and correct for the bias in visual odometry and a sensor fusion algorithm capable of exploiting sparse global measurements. Our graph-based state estimation framework is capable of inferring global orientation using a unified representation of local and global measurements and recovers from inaccurate initial estimates of the state, as intermittently available GPS information may delay the observability of the entire state. We also demonstrate a reduction of the complexity of the problem to achieve real-time throughput. In our experiments, we show in an outdoor dataset with distant features where our bias corrected visual odometry solution makes a five-fold improvement in the accuracy of the estimated translation compared to a standard approach. For a traverse of 2km we demonstrate the capabilities of our graph-based state estimation approach to successfully infer global orientation with as few as 6 GPS measurements and with two-fold improvement in mean position error using the corrected visual odometry.