TechTalks from event: Technical session talks from ICRA 2012

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Hybrid Legged Robots

  • Passive Dynamic Walking of Viscoelastic-Legged Rimless Wheel Authors: Asano, Fumihiko; Kawamoto, Junji
    imit cycle walking including passive-dynamic walkers is mathematically modeled as a nonlinear hybrid dynamical system with state jumps in general. The generated motion is natural and energy efficient, but it is still pointed out that there are many differences between limit cycle walking and human walking. Non-existence of the period of double-limb support in the former comes from the assumption of instantaneous inelastic collision and is one of the biggest differences from the latter. In human walking, the period of double-limb support accounts for more than 10% of one cycle, and this must have significant effects on the gait stability and efficiency. Also in robot walking, utilizing the effects of double-limb support is essential to achieve more flexible, adaptive and human-like behavior. This paper then develops a novel mathematical model of a passive rimless wheel that emerges double-limb support by using the leg viscoelasticity, and numerically investigates the fundamental properties.
  • Control of Dynamic Locomotion for the Hybrid Wheel-Legged Mobile Robot by using Unstable-Zeros Cancellation Authors: Suzumura, Akihiro; Fujimoto, Yasutaka
    In this paper, a new method of center of mass trajectory planning using the zero-phase low pass filter is proposed. This method is based on a table-cart model which simply describes the relationship between center of mass and zero moment point. Generally, zero moment point should be controlled to realize dynamic motion. This method can easily generate the center of mass trajectory which realizes the desired zero moment point. In our study, this method is applied to wheel-legged locomotion. We will show the result that zero moment point can be sufficiently controlled even if quadruped wheel-legged mobile robot is apploximated to a table-cart model. The effectiveness of the idea is validated by simulation and experiment.
  • Comparison of Cost Functions for Electrically Driven Running Robots Authors: Remy, C. David; Buffinton, Keith; Siegwart, Roland
    In this work we apply optimal control to create running gaits for the model of an electrically driven one legged hopper, and compare the results obtained for five different objective functions. By using high compliant series elastic actuators, the motions of joint and motor are decoupled, which allows the exploitation of natural dynamics. Depending on the cost function, this exploitation varies. Energy is injected at different points of time, the amplitude of actuator action changes significantly, and the optimal gear ratios differ by a factor of two. Variations are, however, comparable over a wide range of hopping heights and running velocities. Purely force-based cost functions prove to be ill-suited for such non-conservative systems, and it is shown that thermal electrical losses, in contrast to common belief, do not dominate energy expenditure. The numerical results are corroborated by detailed analytical considerations which give general insights into optimal excitation with electric actuators.
  • A Reduced-Order Dynamical Model for Running with Curved Legs Authors: Jun, Jae Yun; Clark, Jonathan
    Some of the unique properties associated with running with curved legs or feet (as opposed to point-contact feet) are examined in this work, including the rolling contact motion, the change of the leg's effective stiffness and rest length, the shift of the effective flexion point along the leg, and the compliant-vaulting motions over its tiptoe during stance. To examine these factors, a novel torque-driven reduced-order dynamical model with a clock-based control scheme and with a simple motor model is developed (named as torque-driven and damped half-circle-leg model (TD-HCL)). The controller parameters are optimized for running efficiency and forward speed using a direct search method, and the results are compared to those of other existing dynamical models such as the torque-driven and damped spring-loaded-inverted-pendulum (TD-SLIP) model, the torque-driven and damped two-segment-leg (TD-TSL) model, and the TD-SLIP with a rolling foot (TD-SLIP-RF) model. The results show that running with rolling is more efficient and more stable than running with legs that involve pin joint contact model. This work begins to explain why autonomous robots using curved legs run efficiently and robustly. New curved legs are designed and manufactured in order to validate these results.
  • FastRunner: A Fast, Efficient and Robust Bipedal Robot. Concept and Planar Simulation Authors: Cotton, Sebastien; OLARU, IONUT MIHAI CONSTANTIN; bellman, matthew; van der ven, tim; Godowski, Johnny C; Pratt, Jerry
    Bipedal robots are currently either slow, energetically inefficient and/or require a lot of control to maintain their stability. This paper introduces the FastRunner, a bipedal robot based on a new leg architecture. Simulation results of a Planar FastRunner demonstrate that legged robots can run fast, be energy efficient and inherently stable. The simulated FastRunner has a cost of transport of 1.4 and requires only a local feedback of the hip position to reach 35.4 kph from stop in simulation.
  • Zero-Moment Point Based Balance Control of Leg-Wheel Hybrid Structures with Inequality Constraints of Dynamic Behavior Authors: An, Sang-ik; Oh, Yonghwan; Kwon, Dong-Soo
    This paper discusses an unified method of the tracking and balancing controls for leg-wheel hybrid structures in an effort to improve the mobility over hard, flat surfaces. Preliminarily, we analyzed the contact constraint to formulate a dynamically decoupled model in the task space. Then, inequality constraints were determined to restrict the dynamic behavior of the system within the given bounds for the dynamic stability and the actuator saturation. The inequality constraints were applied to the reference control input that was designed for the mechanism to traverse the desired trajectories without the constraints. To find the constrained control input, a quadratic objective function was proposed to minimize the modification error of the control inputs. We tested the effectiveness of the proposed algorithm by comparing simulation results with our previous research.

Visual Tracking

  • Generic Realtime Kernel Based Tracking Authors: Hadj-Abdelkader, Hicham; Mezouar, Youcef; Chateau, Thierry
    This paper deals with the design of a generic visual tracking algorithm suitable for a large class of camera (single viewpoint sensors). It is based on the estimation of the relationship between observations and motion on the sphere. This is efficiently achieved using a kernel-based regression function on a generic linearly-weighted sum of non-linear basis functions. We also present two set of experiments. The first one shows the efficiency of our algorithm through the tracking in video sequences acquired with three types of cameras (conventional, dioptric-fisheye and catadioptric). The real-time performances will be shown by tracking one or several planes. The second set of experiments presents an application of our tracking algorithm to visual servoing with a fisheye camera.
  • Generative Object Detection and Tracking in 3D Range Data Authors: Kaestner, Ralf; Maye, Jerome; Pilat, Yves; Siegwart, Roland
    This paper presents a novel approach to tracking dynamic objects in 3D range data. Its key contribution lies in the generative object detection algorithm which allows the tracker to robustly extract objects of varying sizes and shapes from the observations. In contrast to tracking methods using discriminative detectors, we are thus able to generalize over a wide range of object classes matching our assumptions. Whilst the generative model underlying our framework inherently scales with the complexity and the noise characteristics of the environment, all parameters involved in the detection process obey a clean probabilistic interpretation. Nevertheless, our unsupervised object detection and tracking algorithm achieves real-time performance, even in highly dynamic scenarios covering a significant amount of moving objects. Through an application to populated urban settings, we are able to show that the tracking performance of the presented approach yields results which are comparable to state-of-the-art discriminative methods.
  • Moving Vehicle Detection and Tracking in Unstructured Environments Authors: Wojke, Nicolai; Häselich, Marcel
    The detection and tracking of moving vehicles is a necessity for collision-free navigation. In natural unstructured environments, motion-based detection is challenging due to low signal to noise ratio. This paper describes our approach for a 14 km/h fast autonomous outdoor robot that is equipped with a Velodyne HDL-64E S2 for environment perception. We extend existing work that has proven reliable in urban environments. To overcome the unavailability of road network information for background separation, we introduce a foreground model that incorporates geometric as well as temporal cues. Local shape estimates successfully guide vehicle localization. Extensive evaluation shows that the system works reliable and efficient in various outdoor scenarios without any prior knowledge about the road network. Experiments with our own sensor as well as on publicly available data from the DARPA Urban Challenge revealed more than 96 % correctly identified vehicles.
  • Learning to Place New Objects Authors: Jiang, Yun; Zheng, Changxi; Lim, Marcus; Saxena, Ashutosh
    The ability to place objects in an environment is an important skill for a personal robot. An object should not only be placed stably, but should also be placed in its preferred location/orientation. For instance, it is preferred that a plate be inserted vertically into the slot of a dish-rack as compared to being placed horizontally in it. Unstructured environments such as homes have a large variety of object types as well as of placing areas. Therefore our algorithms should be able to handle placing new object types and new placing areas. These reasons make placing a challenging manipulation task. In this work, we propose using a supervised learning approach for finding good placements given point-clouds of the object and the placing area. Our method combines the features that capture support, stability and preferred configurations, and uses a shared sparsity structure in its the parameters. Even when neither the object nor the placing area is seen previously in the training set, our learning algorithm predicts good placements. In robotic experiments, our method enables the robot to stably place known objects with a 98% success rate and 98% when also considering semantically preferred orientations. In the case of placing a new object into a new placing area, the success rate is 82% and 72%.
  • Lost in Translation (and Rotation): Rapid Extrinsic Calibration for 2D and 3D LIDARs Authors: Maddern, William; Harrison, Alastair; Newman, Paul
    This paper describes a novel method for determining the extrinsic calibration parameters between 2D and 3D LIDAR sensors with respect to a vehicle base frame. To recover the calibration parameters we attempt to optimize the quality of a 3D point cloud produced by the vehicle as it traverses an unknown, unmodified environment. The point cloud quality metric is derived from Rényi Quadratic Entropy and quantifies the compactness of the point distribution using only a single tuning parameter. We also present a fast approximate method to reduce the computational requirements of the entropy evaluation, allowing unsupervised calibration in vast environments with millions of points. The algorithm is analyzed using real world data gathered in many locations, showing robust calibration performance and substantial speed improvements from the approximations.

Physical Human-Robot Interaction

  • Planning Body Gesture of Android for Multi-Person Human-Robot Interaction Authors: Kondo, Yutaka; Takemura, Kentaro; Takamatsu, Jun; Ogasawara, Tsukasa
    Natural body gesture, as well as speech dialog, is crucial for human-robot interaction and human-robot symbiosis. We have already proposed a real-time gesture planning method. In this paper, we afford this method more flexibility by adding motion parameterization function. Especially in multi-person HRI, this function becomes more important because of its adaptation to changes of a speaker’s and/or object’s locations. We implement our method for multi-person HRI system on the android Actroid-SIT, and conduct two experiments for estimating the precision of gestures and the human impressions about the Actroid. Through these experiments, we confirmed our method gives humans a more sophisticated impressions.
  • Variable Admittance Control of a Four-Degree-Of-Freedom Intelligent Assist Device Authors: Lecours, Alexandre; Mayer-St-Onge, Boris; Gosselin, Clement
    Robots are currently used in some applications to enhance human performance and it is expected that human/robot interactions will become more frequent in the future. In order to achieve effective human augmentation, the cooperation must be very intuitive to the human operator. This paper presents a variable admittance control approach to improve system intuitivity. The proposed variable admittance law is based on the inference of human intentions using desired velocity and acceleration. Stability issues are discussed and a controller design example is given. Finally, experimental results obtained with a full-scale prototype of an intelligent assist device are presented in order to demonstrate the performance of the algorithm.
  • Extraction of Latent Kinematic Relationships between Human Users and Assistive Robots Authors: Morimoto, Jun; Hyon, Sang-Ho
    In this study, we propose a control method for movement assistive robots using measured signals from human users. Some of the wearable assistive robots have mechanisms that can be adjusted to human kinematics (e.g., adjustable link length). However, since the human body has a complicated joint structure, it is generally difficult to design an assistive robot which mechanically well fits human users. We focus on the development of a control algorithm to generate corresponding movements of wearable assistive robots to that of human users even when the kinematic structures of the assistive robot and the human user are different. We first extract the latent kinematic relationship between a human user and the assistive robot. The extracted relationship is then used to control the assistive robot by converting human behavior into the corresponding joint angle trajectories of the robot. The proposed approach is evaluated by a simulated robot model and our newly developed exoskeleton robot, XoR.
  • Design & Personalization of a Cooperative Carrying Robot Controller Authors: Parker, Chris; Croft, Elizabeth
    In the near future, as robots become more advanced and affordable, we can envision their use as intelligent assistants in a variety of domains. An exemplar human-robot task identified in many previous works is cooperatively carrying a physically large object. An important task objective is to keep the carried object level. In this work, we propose an admittance-based controller that maintains a level orientation of a cooperatively carried object. The controller raises or lowers its end of the object with a human-like behavior in response to perturbations in the height of the other end of the object (e.g., the end supported by the human user). We also propose a novel tuning procedure, and find that most users are in close agreement about preferring a slightly under-damped controller response, even though they vary in their preferences regarding the speed of the controller's response.
  • Trust-Driven Interactive Visual Navigation for Autonomous Robots Authors: Xu, Anqi; Dudek, Gregory
    We describe a model of "trust" in human-robot systems that is inferred from their interactions, and inspired by similar concepts relating to trust among humans. This computable quantity allows a robot to estimate the extent to which its performance is consistent with a human’s expectations, with respect to task demands. Our trust model drives an adaptive mechanism that dynamically adjusts the robot's autonomous behaviors, in order to improve the efficiency of the collaborative team. We illustrate this trust-driven methodology through an interactive visual robot navigation system. This system is evaluated through controlled user experiments and a field demonstration using an aerial robot.
  • The 20-DOF Miniature Humanoid MH-2: A Wearable Communication System Authors: Tsumaki, Yuichi; Ono, Fumiaki; Tsukuda, Taisuke
    The 20-DOF miniature humanoid ``MH-2'' designed as a wearable telecommunicator, is a personal telerobot system. An operator can communicate with remote people through the robot. The robot acts as an avatar of the operator. To date, four prototypes of the wearable telecommunicator T1, T2, T3 and MH-1, have been developed as research platforms. MH-1 is also a miniature humanoid robot with 11-DOF for mutual telexistence. Although human-like appearance might be important for such communication systems, it is unable to achieve sophisticated gestures due to the lack of both wrist and body motions. In this paper, to tackle this problem, a 3-DOF parallel wire mechanism with novel wire arrangement for the wrist is introduced, while 3-DOF body motions are also adopted. Consequently, a 20-DOF miniature humanoid with dual 7-DOF arms has been designed and developed. Details of the concept and design are discussed, while fundamental experiments with a developed 7-DOF arm are also executed to confirm the mechanical properties.