TechTalks from event: Technical session talks from ICRA 2012

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Sampling-Based Motion Planning

  • A Scalable Method for Parallelizing Sampling-Based Motion Planning Algorithms Authors: Jacobs, Sam Ade; Burgos, Juan; Manavi, Kasra; Denny, Jory; Thomas, Shawna; Amato, Nancy
    This paper describes a scalable method for parallelizing sampling-based motion planning algorithms. It subdivides configuration space (C-space) into (possibly overlapping) regions and independently, in parallel, uses standard (sequential) sampling-based planners to construct roadmaps in each region. Next, in parallel, regional roadmaps in adjacent regions are connected to form a global roadmap. By subdividing the space and restricting the locality of connection attempts, we reduce the work and inter-processor communication associated with nearest neighbor calculation, a critical bottleneck for scalability in existing parallel motion planning methods. We show that our method is general enough to handle a variety of planning schemes, including the widely used Probabilistic Roadmap (PRM) and Rapidly-exploring Random Trees (RRT) algorithms.We compare our approach to two other existing parallel algorithms and demonstrate that our approach achieves better and more scalable performance. Our approach achieves almost linear scalability on a 2400 core LINUX cluster and on a 153,216 core Cray XE6 petascale machine.
  • LQR-RRT*: Optimal Sampling-Based Motion Planning with Automatically Derived Extension Heuristics Authors: Perez, Alejandro; Platt, Robert; Konidaris, George Dimitri; Kaelbling, Leslie; Lozano-Perez, Tomas
    The RRT* algorithm has recently been proposed as an optimal extension to the standard RRT algorithm [1]. However, like RRT, RRT* is difficult to apply in problems with complicated or underactuated dynamics because it requires the design of a two domain-specific extension heuristics: a distance metric and node extension method. We propose automatically deriving these two heuristics for RRT* by locally linearizing the domain dynamics and applying linear quadratic regulation (LQR). The resulting algorithm, LQR-RRT*, finds optimal plans in domains with complex or underactuated dynamics without requiring domain-specific design choices. We demonstrate its application in domains that are successively torquelimited, underactuated, and in belief space.
  • SR-RRT: Selective Retraction-Based RRT Planner Authors: Lee, Junghwan; Kwon, Osung; Zhang, Liangjun; Yoon, Sung-eui
    We present a novel retraction-based planner, selective retraction-based RRT, for efficiently handling a wide variety of environments that have different characteristics. We first present a bridge line-test that can identify regions around narrow passages, and then perform an optimizationbased retraction operation selectively only at those regions. We also propose a non-colliding line-test, a dual operator to the bridge line-test, as a culling method to avoid generating samples near wide-open free spaces and thus to generate more samples around narrow passages. These two tests are performed with a small computational overhead and are integrated with a retraction-based RRT. In order to demonstrate benefits of our method, we have tested our method with different benchmarks that have varying amounts of narrow passages. Our method achieves up to 21 times and 3.5 times performance improvements over a basic RRT and an optimizationbased retraction RRT, respectively. Furthermore, our method consistently improves the performances of other tested methods across all the tested benchmarks that have or do not have narrow passages.
  • Sampling-Based Motion Planning with Dynamic Intermediate State Objectives: Application to Throwing Authors: Zhang, Yajia; Luo, Jingru; Hauser, Kris
    Dynamic manipulations require attaining high velocities at specified configurations, all the while obeying geometric and dynamic constraints. This paper presents a motion planner that constructs a trajectory that passes at an intermediate state through a dynamic objective region, which is comprised of a certain lower dimensional submanifold in the configuration/velocity state space, and then returns to rest. Planning speed and reliability is greatly improved using optimizations based on the fact that ramp-up and ramp-down subproblems are coupled by the choice of intermediate state, and that very few (often less than 1%) intermediate states yield feasible solution trajectories. Simulation experiments demonstrate that our method quickly generates trajectories for a 6-DOF industrial manipulator throwing a small object.
  • Towards Small Asymptotically Near-Optimal Roadmaps Authors: Marble, James; Bekris, Kostas E.
    An exciting recent development is the definition of sampling-based motion planners which guarantee asymptotic optimality. Nevertheless, roadmaps with this property may grow too large and lead to longer query resolution times. If optimality requirements are relaxed, existing asymptotically near-optimal solutions produce sparser graphs by removing redundant edges. Even these alternatives, however, include all sampled configurations as nodes in the roadmap. This work proposes a method, which can reject redundant samples but does provide asymptotic coverage and connectivity guarantees, while keeping local path costs low. Not adding every sample can significantly reduce the size of the final roadmap. An additional advantage is that it is possible to define a reasonable stopping criterion for the approach inspired by previous methods. To achieve these objectives, the proposed method maintains a dense graph that is used for evaluating the performance of the roadmap with regards to local path costs. Experimental results show that the method indeed provides small roadmaps, allowing for shorter query resolution times. Furthermore, smoothing the final paths results in an even more advantageous comparison against alternatives with regards to path quality.
  • Proving Path Non-Existence Using Sampling and Alpha Shapes Authors: McCarthy, Zoe; Bretl, Timothy; Hutchinson, Seth
    In this paper, we address the problem determining the connectivity of a robot's free configuration space. Our method iteratively builds a constructive proof that two configurations lie in disjoint components of the free configuration space. Our algorithm first generates samples that correspond to configurations for which the robot is in collision with an obstacle. These samples are then weighted by their generalized penetration distance, and used to construct alpha shapes. The alpha shape defines a collection of simplices that are fully contained within the configuration space obstacle region. These simplices can be used to quickly solve connectivity queries, which in turn can be used to define termination conditions for sampling-based planners. Such planners, while typically either resolution complete or probabilistically complete, are not able to determine when a path does not exist, and therefore would otherwise rely on heuristics to determine when the search for a free path should be abandoned. An implementation of the algorithm is provided for the case of a 3D Euclidean configuration space, and a proof of correctness is provided.

Minimally Invasive Interventions II

  • Configuration Comparison for Surgical Robotic Systems Using a Single Access Port and Continuum Mechanisms Authors: Zheng, Xidian; Xu, Kai
    Research on robot-assisted laparoscopic SPA (Single Port Access) surgery and N.O.T.E.S (Natural Orifice Translumenal Endoscopic Surgery) have thrived in the past a few years. A configuration similarity between these surgical robotic slaves is that two robotic arms are extended from the same access port (either a laparoscope or an endoscope) for surgical interventions. However, upon designing such a surgical robotic slave, the structure of the extended robotic arms has not been explored thoroughly based on evaluation of their distal dexterity. This paper presents a simulation-based comparison among three different structures which could be used to form these extended robotic arms. Results presented in this paper could serve as a design reference for surgical robotic slaves which use a single access port and continuum mechanisms.
  • Control of Untethered Magnetically Actuated Tools Using a Rotating Permanent Magnet in Any Position Authors: Mahoney, Arthur; Cowan, Daniel Lewis; Miller, Katie; Abbott, Jake
    It has been shown that when a magnetic dipole, such as a permanent magnet, is rotated around a fixed axis such that the dipole is perpendicular to the axis of rotation, the magnetic field vector at every point in space also rotates around a fixed axis. In this paper, we reformulate this phenomenon using linear algebraic techniques, which enables us to find the necessary dipole rotation axis to make the magnetic field at any desired point in space rotate about any desired axis. To date, untethered magnetically actuated tools (e.g., capsule endoscopes, rolling spheres, and helical-propeller microswimmers) controlled with a single rotating permanent magnet have been constrained to operate in positions where the rotating field behavior is simple and easy to visualize. We experimentally demonstrate that the results of this paper can be used to control a variety of untethered, rotating magnetic devices in any position even while the rotating permanent magnet follows trajectories independent of the devices themselves. This method constitutes a substantial step toward making a great deal of prior laboratory research regarding rotating magnetic microrobots and capsule endoscopes clinically feasible.
  • Integration and Preliminary Evaluation of an Insertable Robotic Effectors Platform for Single Port Access Surgery Authors: Bajo, Andrea; Goldman, Roger E.; Wang, Long; Fowler, Dennis; Simaan, Nabil
    In this paper, we present the integration and preliminary evaluation of a novel Insertable Robotic Effectors Platform (IREP) for Single Port Access Surgery (SPAS). The unique design of the IREP includes planar parallel mechanisms, continuum snake-like arms, wire-actuated wrists, and passive flexible components. While this design has advantages, it presents challenges in terms of modeling, control, and telemanipulation. The complete master-slave resolved-rates telemanipulation framework of the IREP along with its actuation compensation is presented. Experimental evaluation of the capabilities of this new surgical system include bi-manual exchange of rings, pick-and-place tasks, suture passing and knot tying. Results show that the IREP meets the minimal workspace and dexterity requirements specified for laparoscopic surgery, it allows for dual-arm operations such as tool exchange and knot tying in confined spaces. Although it was possible to tie a surgeon's knot with minimal training, suture passing was difficult due to the limited axial rotation of the distal wrists.
  • Constrained Filtering with Contact Detection Data for the Localization and Registration of Continuum Robots in Flexible Environments Authors: Tully, Stephen; Bajo, Andrea; Kantor, George; Choset, Howie; Simaan, Nabil
    This paper presents a novel filtering technique that uses contact detection data and environmental stiffness estimates to register and localize a robot with respect to an a priori 3D surface model. The algorithm leverages geometric constraints within a Kalman filter framework and relies on two distinct update procedures: 1) an equality constrained step for when the robot is forcefully contacting the environment, and 2) an inequality constrained step for when the robot lies in the freespace of the environment. This filtering procedure registers the robot by incrementally eliminating probabilistically infeasible state space regions until a high likelihood solution emerges. In addition to registration and localization, the algorithm can estimate the deformation of the surface model and can detect false positives with respect to contact estimation. This method is experimentally evaluated with an experiment involving a continuum robot interacting with a bench-top flexible structure. The presented algorithm produces an experimental error in registration (with respect to the end-effector position) of 1.1 mm, which is less than 0.8 percent of the robot length.
  • Real-Time Control Architecture of a Novel Single-Port Laparoscopy Bimanual Robot (SPRINT) Authors: Niccolini, Marta; Petroni, Gianluigi; Menciassi, Arianna; Dario, Paolo
    This paper presents a novel master-slave teleoperated robotic platform designed for Single Port Laparoscopy. The SPRINT (Single-Port lapaRoscopy bimaNual roboT) is composed of two high-dexterity 6 Degrees of Freedom (DOFs) robotic arms, a stereoscopic camera and a dedicated console for the robot control by the surgeon. Along with a short summary of the hardware features of the system, this paper describes the real-time control architecture of the SPRINT. Particular attention was given to the kinematic coupling between the master and the slave manipulators, as well as to the inverse kinematics algorithm. Tests performed to validate the performance of the robot in terms of accuracy are satisfactory, thus positioning the SPRINT as a candidate for the next generation of robots for Single Port Laparoscopy.
  • Remote Centre-Of-Motion Control Algorithms of 6-RRCRR Parallel Robot Assisted Surgery System (PRAMiSS) Authors: Moradi Dalvand, Mohsen; Shirinzadeh, Bijan
    In this paper a 6-RRCRR parallel robot assisted minimally invasive surgery/microsurgery system (PRAMiSS) is introduced. Remote centre-of-motion (RCM) control algorithms of PRAMiSS suitable for minimally invasive surgery and microsurgery are also presented. The programmable RCM approach is implemented in order to achieve manipulation under the constraint of moving through the fixed penetration point. Having minimised the displacements of the mobile platform of the parallel micropositioning robot, the algorithms also apply orientation constraint to the instrument and prevent the tool tip to orient due to the robot movements during the manipulation. Experimental results are provided to verify accuracy and effectiveness of the proposed RCM control algorithms for minimally invasive surgery.

Stochastic in Robotics and Biological Systems

  • Low-Cost Collaborative Localization for Large-Scale Multi-Robot Systems Authors: Prorok, Amanda; Bahr, Alexander; Martinoli, Alcherio
    Large numbers of collaborating robots are advantageous for solving distributed problems. In order to efficiently solve the task at hand, the robots often need accurate localization. In this work, we address the localization problem by developing a solution that has low computational and sensing requirements, and that is easily deployed on large robot teams composed of cheap robots. We build upon a real-time, particle-filter based localization algorithm that is completely decentralized and scalable, and accommodates realistic robot assumptions including noisy sensors, and asynchronous and lossy communication. In order to further reduce this algorithm’s overall complexity, we propose a low-cost particle clustering method, which is particularly well suited to the collaborative localization problem. Our approach is experimentally validated on a team of ten real robots.
  • Robotic Manifold Tracking of Coherent Structures in Flows Authors: Hsieh, M. Ani; Forgoston, Eric; Mather, T, William; Schwartz, Ira
    Tracking Lagrangian coherent structures in dynamical systems is important for many applications such as oceanography and weather prediction. In this paper, we present a collaborative robotic control strategy designed to track stable and unstable manifolds. The technique does not require global information about the fluid dynamics, and is based on local sensing, prediction, and correction. The collaborative control strategy is implemented on a team of three robots to track coherent structures and manifolds on static flows as well as a noisy time-dependent model of a wind-driven double-gyre often seen in the ocean. We present simulation and experimental results and discuss theoretical guarantees of the collaborative tracking strategy.
  • Ensemble Synthesis of Distributed Control and Communication Strategies Authors: Mather, T, William; Hsieh, M. Ani
    We present an ensemble framework for the design of distributed control and communication strategies for the dynamic allocation of a team of robots to a set of tasks. In this work, we assume individual robot controllers are sequentially composed of individual task controllers. This assumption enables the representation of the robot ensemble dynamics as a class of stochastic hybrid systems that can be modeled as continuous-time Markov jump processes where feedback strategies can be derived to control the team's distribution across the tasks. Since the distributed implementation of these feedback strategy requires the estimation of certain population variables, we show how the ensemble model can be expanded to incorporate the dynamics of the information exchange. This then enables us to optimize the individual robot control policies to ensure overall system robustness given some likelihood of resource failures. We consider the assignment of a team of homogeneous robots to a collection of spatially distributed tasks and validate our approach via high-fidelity simulations.
  • Almost-Uniform Sampling of Rotations for Conformational Searches in Robotics and Structural Biology Authors: Yan, Yan; Chirikjian, Gregory
    We propose a new method for sampling the rotation group that involves decomposing it into identical Voronoi cells centered on rotational symmetry operations of the Platonic solids. Within each cell, Cartesian coordinates in exponential coordinates are used to achieve almost-uniform sampling at any level of resolution, without having to store large numbers of coordinates, and without requiring sophisticated data structures. We analyze the shape of these cells, and explain how this can be used in the context of conformational searches in the fields of Robotics and Structural Biology.
  • Randomly Distributed Delayed Communication and Coherent Swarm Patterns Authors: Lindley, Brandon; Mier-Y-Teran-Romero, Luis; Schwartz, Ira
    Previously we showed how delay communication between globally coupled self-propelled agents causes new spatio-temporal patterns to arise when the delay coupling is fixed among all agents [1]. In this paper, we show how discrete, randomly distributed delays affect the dynamical patterns. In particular, we investigate how the standard deviation of the time delay distribution affects the stability of the different patterns as well as the switching probability between coherent states. [1] E. Forgoston and I. Schwartz, “Delay-induced instabilities in selfpropelling swarms,” Phy. Rev. E, vol. 77, 2008.
  • Real-Time Automated Modeling and Control of Self-Assembling Systems Authors: Mermoud, Gregory; Mastrangeli, Massimo; Upadhyay, Utkarsh; Martinoli, Alcherio
    We present the M<sup>3</sup> framework, a formal and generic computational framework for modeling and controlling stochastic distributed systems of purely reactive robots in an automated and real-time fashion. Based on the trajectories of the robots, the framework builds up an internal microscopic representation of the system, which then serves as a blueprint of models at higher abstraction levels. These models are then calibrated using a Maximum Likelihood Estimation (MLE) approach. We illustrate the structure and performance of the framework by performing the online optimization of a simple bang-bang controller for the stochastic self-assembly of water-floating passive modules. The experimental results demonstrate that the generated models can successfully optimize the assembly of desired structures.