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


  • Time-Optimal Multi-Stage Motion Planning with Guaranteed Collision Avoidance Via an Open-Loop Game Formulation Authors: Takei, Ryo; Huang, Haomiao; Ding, Jerry; Tomlin, Claire
    We present an efficient algorithm which computes, for a kinematic point mass moving in the plane, a time-optimal path that visits a sequence of target sets while conservatively avoiding collision with moving obstacles, also modelled as kine- matic point masses, but whose trajectories are unknown. The problem is formulated as a pursuit-evasion differential game, and the underlying construction is based on optimal control. The algorithm, which is a variant of the fast marching method for shortest path problems, can handle general dynamical constraints on the players and arbitrary domain geometry (e.g. obstacles, non-polygonal boundaries). Applications to a two- stage game, capture-the-flag, is presented.
  • Execution and Analysis of High-Level Tasks with Dynamic Obstacle Anticipation Authors: Johnson, Benjamin; Havlak, Frank; Campbell, Mark; Kress-Gazit, Hadas
    This paper uniquely embeds high-level robot controllers with sensor data obtained from abstracting probabilistic anticipation of the behavior of dynamic obstacles. An example problem of an autonomous vehicle operating in an urban environment, in the presence of other vehicles and pedestrians, is used as motivation. The correct-by-construction controller is automatically synthesized from a set of high-level tasks, specified as temporal logic formulas. The anticipated behavior of other vehicles is abstracted to a set of propositions describing the safety of road segments at intersections, and used as the output of high-level sensors for the controller. Such an input to the controller is inherently probabilistic, and this paper investigates the types of probabilistic guarantees that can be made about the system using both formal and statistical analysis.
  • A Depth Space Approach to Human-Robot Collision Avoidance Authors: Flacco, Fabrizio; Kroeger, Torsten; De Luca, Alessandro; Khatib, Oussama
    In this paper a real-time collision avoidance approach is presented for safe human-robot coexistence. The main contribution is a fast method to evaluate distances between the robot and possibly moving obstacles (including humans), based on the concept of depth space. With these distances, repulsive vectors are generated that are used to control the robot while executing a generic motion task. The repulsive vectors can also take advantage of an estimation of the obstacle velocity. In order to preserve the execution of a Cartesian task with a redundant manipulator, a simple collision avoidance algorithm has been implemented where different reaction behaviors are set up for the end-effector and for other control points along the robot structure. The complete collision avoidance framework, from perception of the environment to joint-level robot control, is presented for a 7-dof KUKA Light-Weight-Robot IV using the Microsoft Kinect sensor. Experimental results are reported for dynamic environments with obstacles and a human.
  • LQG-Obstacles: Feedback Control with Collision Avoidance for Mobile Robots with Motion and Sensing Uncertainty Authors: van den Berg, Jur; Wilkie, David; Guy, Stephen J.; Niethammer, Marc; Manocha, Dinesh
    This paper presents LQG-Obstacles, a new concept that combines linear-quadratic feedback control of mobile robots with guaranteed avoidance of collisions with obstacles. Our approach generalizes the concept of Velocity Obstacles to any robotic system with a linear Gaussian dynamics model. We integrate a Kalman filter for state estimation and an LQR feedback controller into a closed-loop dynamics model of which a higher-level control objective is the ``control input''. We then define the LQG-Obstacle as the set of control objectives that result in a collision with high probability. Selecting a control objective outside the LQG-Obstacle then produces collision-free motion. We demonstrate the potential of LQG-Obstacles by safely and smoothly navigating a simulated quadrotor helicopter with complex non-linear dynamics and motion and sensing uncertainty through three-dimensional environments with obstacles and narrow passages.
  • K-IOS: Intersection of Spheres for Efficient Proximity Query Authors: Zhang, Xinyu; Kim, Young J.
    We present a new bounding volume structure, k-IOS that is an intersection of k spheres, for accelerating proximity query including collision detection and Euclidean distance computation between arbitrary polygon-soup models that undergo rigid motion. Our new bounding volume is easy to implement and highly efficient both for its construction and runtime query. In our experiments, we have observed up to 4.0 times performance improvement of proximity query compared to an existing well-known algorithm based on swept sphere volume (SSV) [1]. Moreover, k-IOS is strictly convex that can guarantee a continuous gradient of distance function with respect to object’s configuration parameter.
  • Reciprocal Collision Avoidance for Multiple Car-Like Robots Authors: Alonso-Mora, Javier; Breitenmoser, Andreas; Beardsley, Paul; Siegwart, Roland
    In this paper a method for distributed reciprocal collision avoidance among multiple non-holonomic robots with bike kinematics is presented. The proposed algorithm, bicycle reciprocal collision avoidance (B-ORCA), builds on the concept of optimal reciprocal collision avoidance (ORCA) for holonomic robots but furthermore guarantees collision-free motions under the kinematic constraints of car-like vehicles. The underlying principle of the B-ORCA algorithm applies more generally to other kinematic models, as it combines velocity obstacles with generic tracking control. The theoretical results on collision avoidance are validated by several simulation experiments between multiple car-like robots.

Localization and Mapping

  • Point Set Registration through Minimization of the L2 Distance between 3D-NDT Models Authors: Stoyanov, Todor; Magnusson, Martin; Lilienthal, Achim, J.
    Point set registration --- the task of finding the best fitting alignment between two sets of point samples, is an important problem in mobile robotics. This article proposes a novel registration algorithm, based on the distance between Three-Dimensional Normal Distributions Transforms. 3D-NDT models --- a sub-class of Gaussian Mixture Models with uniformly weighted, largely disjoint components, can be quickly computed from range point data. The proposed algorithm constructs 3D-NDT representations of the input point sets and then formulates an objective function based on the $L_2$ distance between the considered models. Analytic first and second order derivatives of the objective function are computed and used in a standard Newton method optimization scheme, to obtain the best-fitting transformation. The proposed algorithm is evaluated and shown to be more accurate and faster, compared to a state of the art implementation of the Iterative Closest Point and 3D-NDT Point-to-Distribution algorithms.
  • Consistency Analysis for Sliding-Window Visual Odometry Authors: Dong-Si, Tue-Cuong; Mourikis, Anastasios
    In this paper we focus on the problem of {em visual odometry}, i.e., the task of tracking the pose of a moving platform using visual measurements. In recent years, several VO algorithms have been proposed that employ nonlinear minimization in a sliding window of poses for this task. Through the use of iterative re-linearization, these methods are capable of successfully addressing the nonlinearity of the measurement models, and have become the de-facto standard for high-precision VO. In this work, we conduct an analysis of the properties of marginalization, which is the process through which older states are removed from the sliding window. This analysis shows that the standard way of marginalizing older poses results in an erroneous change in the rank of the measurements' information matrix, and leads to underestimation of the uncertainty of the state estimates. Based on the analytical results, we also propose a simple modification of the way in which the measurement Jacobians are computed. This modification avoids the above problem, and results in an algorithm with superior accuracy, as demonstrated in both simulation tests and real-world experiments.
  • Efficient Visual Odometry Using a Structure-Driven Temporal Map Authors: Martinez-Carranza, Jose; Calway, Andrew
    We describe a method for visual odometry using a single camera based on an EKF framework. Previous work has shown that filtering based approaches can achieve accuracy performance comparable to that of optimisation methods providing that large numbers of features are used. However, computational requirements are signicantly increased and frame rates are low. We address this by employing higher level structure - in the form of planes - to efficiently parameterise features and so reduce the filter state size and computational load. Moreover, we extend a 1-point RANSAC outlier rejection method to the case of features lying on planes. Results of experiments with both simulated and real-world data demonstrate that the method is effective, achieving comparable accuracy whilst running at significantly higher frame rates.
  • Using Depth in Visual Simultaneous Localisation and Mapping Authors: Scherer, Sebastian Andreas; Dube, Daniel; Zell, Andreas
    We present a method of utilizing depth information as provided by RGBD sensors for robust real-time visual simultaneous localisation and mapping (SLAM) by augmenting monocular visual SLAM to take into account depth data. This is implemented based on the freely available software “Parallel Tracking and Mapping” (PTAM) by Georg Klein, which was originally developed for augmented reality applications. Our modifications allow PTAM to be used as a 6D visual SLAM system even without any additional information about odometry or from an inertial measurement unit.
  • A Visual Marker for Precise Pose Estimation Based on Lenticular Lenses Authors: Tanaka, Hideyuki; Sumi, Yasushi; Matsumoto, Yoshio
    Visual marker is a useful assistive tool for service robots. Existing planar visual markers have poor accuracy and stability in pose estimation, especially in frontal direction. In this study, we developed a novel visual marker based on a new principle enabling accurate and stable pose estimation even by observation from frontal direction. The marker has moire patterns which consist of lenticular lens and stripe pattern, which vary their appearance according to visual-line angle of observation. We can extract pose information from the pattern by a single camera. We developed a prototype of the marker and an algorithm for pose estimation, and then demonstrated its superiority to existing markers by some validation tests.
  • Robot Semantic Mapping through Wearable Sensor-Based Human Activity Recognition Authors: Sheng, Weihua; Li, Gang; Zhu, Chun; Du, Jianhao; Cheng, Qi
    Semantic information can help both humans and robots to understand their environments better. In order to obtain semantic information efficiently and link it to a metric map, we present a semantic mapping approach through human activity recognition in an indoor human-robot coexisting environment. An intelligent mobile robot platform can create a 2D metric map, while human activity can be recognized using motion data from wearable motion sensors mounted on a human subject. Combined with pre-learned models of activity-to-furniture type association and robot pose estimates, the robot can determine the distribution of the furniture types on the 2D metric map. Simulations and real world experiments demonstrate that the proposed method is able to create a reliable metric map with accurate semantic information.

Climbing Robots

  • Step Negotiation with Wheel Traction: A Strategy for a Wheel-Legged Robot Authors: Turker, Korhan; Sharf, Inna
    This paper presents a quasi-static step climbing behavior for a minimal sensing wheel-legged quadruped robot called PAW. In the quasi-static climbing maneuver, the robot benefits from wheel traction and uses its legs to reconfigure itself with respect to the step during the climb. The control methodology with the corresponding controller parameters is determined and the state machine for the maneuver is developed. With this controller, PAW is able to climb steps higher than its body clearance. Furthermore, any step height up to this maximum achievable height can be negotiated autonomously with a single set of controller parameters, without knowledge of the step height or distance to the step.
  • Fast Accessible Rescue Device by Using a Flexible Sliding Actuator Authors: Tsukagoshi, Hideyuki
    This paper discusses a method of locomotion called the “fluid powered ropeway”. It aims to collect information in dangerous buildings as rapidly and safely as possible. The device is mainly composed of a flexible flat tube and a gondola probe driven by fluid power using the buckling phenomenon of the tube. The big advantage is the gondola has the potential to traverse rocky terrains that wheeled and crawler-type vehicles have difficulty in crossing over. This is because the drive force of the gondola is not against the ground but against the tube. In this paper, first, how to operate fluid powered ropeway in a disaster site is illustrated. Next, how to increase the drive force, how to enhance the ability of the gondola to travel over obstacles, and an analysis of the performance are discussed. Finally, the feasibility of the proposed method is verified through an experiment that uses the prototype developed.
  • Design Considerations for Attachment and Detachment in Robot Climbing with Hot Melt Adhesives Authors: Wang, Liyu; Neuschaefer, Fabian; Bernet, Remo; Iida, Fumiya
    Robust climbing in unstructured environments is a long-standing challenge in robotics research. Recently there has been an increasing interest in using adhesive materials for that purpose. For example, a climbing robot using hot melt adhesives (HMAs) has demonstrated advantages in high attachment strength, reasonable operation costs, and applicability to different surfaces. Despite the advantages, there still remain several problems related to the attachment and detachment operations, which prevent this approach from being used in a broader range of applications. Among others, one of the main problems lies in the fact that the adhesive characteristics of this material were not fully understood fin the context of robotic climbing locomotion. As a result, the previous robot often could not achieve expected locomotion performances and ``contaminated'' the environment with HMAs left behind. In order to improve the locomotion performances, this paper focuses on attachment and detachment operations in robot climbing with HMAs. By systematically analyzing the adhesive property and bonding strength of HMAs to different materials, we propose a novel detachment mechanism that substantially improves climbing performances without HMA traces.
  • Parameter Optimization of Directional Dry Adhesives for Robotic Climbing and Gripping Applications Authors: Ruffatto III, Donald; Spenko, Matthew
    This paper experimentally investigates the optimization of directional dry adhesives that can be used for robotic climbing and gripping applications. Directional dry adhesives are modeled on gecko setae. The adhesives are comprised of arrays of micro-scale polymer stalks. The geometry of the polymer stalks has a significant effect upon their adhesion properties. A set of parameters including stalk thickness, stalk angle, face angle and stalk curvature have been identified as factors that influence both normal and shear adhesion levels. A new micro-resolution rapid prototyping process is used to create adhesives with varying geometry and advanced features such as curved stalks. A series of experimental tests characterize the significance of each parameter. Tests indicate that the new curved stalk geometry presented here can provide the greatest overall adhesion and robustness to variations in pull-off angle.
  • System and Design of Clothbot: A Robot for Flexible Clothes Climbing Authors: Liu, Yuanyuan; Wu, Xinyu; QIAN, Huihuan; Zheng, Duan; sun, jianquan; Xu, Yangsheng
    This paper presents a novel climbing robot called Clothbot which has high maneuverability on flexible clothes. It has a novel gripper consisting of two parallel wheels that can grip continuously and stably on various kinds of clothes. Clothbot also has an omni-directional tail of two DOFs so that it can change its center of gravity to control the moving direction on complex and undeterminate clothes. Consequently, Clothbot is able to access most positions of the clothes by moving straight and turning around with only four motors. It is compact, small and light-weighted but has a load capacity six times its own weight. A series of experiments validate its high performance on flexible clothes.