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We reconsider the problem of reactive navigation in sphere worlds, i.e., the construction of a vector field over a compact, convex Euclidean subset punctured by Euclidean disks, whose flow brings a Euclidean disk robot from all but a zero measure set of initial conditions to a designated point destination, with the guarantee of no collisions along the way. We use power diagrams, generalized Voronoi...
Conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. This may in some cases also include the cover art, table of contents, copyright statements, title-page or half title-pages, blank pages, venue maps or other general information relating to the conference that was part of the original...
Motion planning is a fundamental tool in robotics, used to generate collision-free, smooth, trajectories, while satisfying task-dependent constraints. In this paper, we present a novel approach to motion planning using Gaussian processes. In contrast to most existing trajectory optimization algorithms, which rely on a discrete state parameterization in practice, we represent the continuous-time trajectory...
Cloud Robotics techniques based on Learning from Demonstrations suggest promising alternatives to manual programming of robots and autonomous vehicles. One challenge is that demonstrated trajectories may vary dramatically: it can be very difficult, if not impossible, for a system to learn control policies unless the trajectories are clustered into meaningful consistent subsets. Metric clustering methods,...
Recent progress in motion planning has made it possible to determine homotopy inequivalent trajectories between an initial and terminal configuration in a robot configuration space. Current approaches have however either assumed the knowledge of differential one-forms related to a skeletonization of the collision space, or have relied on a simplicial representation of the free space. Both of these...
We address the question of how resource-aware concepts can be utilized in motion planning algorithms. Resource-awareness facilitate better resource allocation on global system level, e.g. when a humanoid robot needs to distribute and schedule a wide variety of concurrent algorithms. We present a motion planning approach that employs self-monitoring concepts in order to identify the difficulty of the...
This paper presents a fast approximate multi-agent decision theoretic planning method extended from the well-known Markov Decision Process (MDP). Our objective is to plan motions for a team of homogeneous micro air vehicles (MAVs) toward a set of goals, such that each MAV at any state at any moment follows an action policy toward a unique goal, while considering action uncertainty. We pursue an efficient...
This paper presents a new approach for fast collision detection in high dimensional configuration spaces for Rapidly-exploring Random Trees (RRT) motion planning. The proposed method is based upon Gaussian Mixture Models (GMM) that are learned using an incremental Expectation Maximization clustering algorithm trained online using exemplars provided by a slow, conventional kinematic-based collision...
This paper presents a new approach to C-space exploration and path planning for robotic manipulators using the structure named bur of free C-space. This structure builds upon the so-called bubble, which is a local volume of free C-space, easily computed using the distance information in the workspace. We show how the same distance information can be used to compute the bur that can reach substantially...
This paper presents a novel method for using volumetric information in the C-space for generating collision-free paths for robotic manipulators in the presence of obstacles. The method is based on the RRT paradigm, i.e., incrementally building trees in C-space in order to connect the initial configuration to the final one. Bubbles of free C-space are used within a carefully modified extend procedure...
We present several modifications to the previously proposed MSPP algorithm that can speed-up its execution considerably. The MSPP algorithm leverages a multi-scale representation of the environment in n dimensions encoded in tree structure constructed by recursive dyadic partitioning of the search space. We first present a new method to compute the graph neighbors in order to reduce the complexity...
We present hierarchical rejection sampling (HRS) to improve the efficiency of asymptotically optimal sampling-based planners for high-dimensional problems with differential constraints. Pruning nodes and rejecting samples that cannot improve the currently best solution have been shown to improve performance for certain problems. We show that in high-dimensional domains this improvement can be so large...
This paper presents a highly sensitive dual mode tactile and proximity sensor for robotic applications that uses Carbon Microcoils (CMCs). The sensor consists of multiple electrode layers printed on a Flexible Printed Circuit Board (FPCB) and a dielectric substrate into which the CMCs are dispersed. The dielectric layer is simply put on the top of the FPCB. Thus, the sensor provides ease of fabrication...
Nanoforce sensors using passive magnetic springs associated to a macroscopic seismic mass are known to be a possible alternative to force sensors based on elastic microstructures like Atomic Force Microscopes if the nanoforces that have to be measured are characterized by a bandwidth limited to a few Hertz. The estimation of the unknown force applied to the seismic mass is based on the deconvolution...
This paper presents a new approach to the characterization of tactile array sensors that aims to reduce the computational time needed for convergence to obtain a useful estimator for normal and shear forces. This is achieved by breaking up the sensor characterization into two parts: a linear regression portion using multivariate least squares regression, and a nonlinear regression portion using a...
Tactile manipulation is the ability to control objects in real-time using the sense of touch. Here we examine tactile manipulation from the perspective of active touch with a biomimetic tactile sensor, which combines tactile perception with control of sensor location. Experiments are performed with the tactile fingertip mounted as end effector to a robot arm, to manipulate (roll) a cylinder in contact...
The observation of robotic assembly tasks is required as feedback for decisions and adaption of the task execution on the current situation. A sequential Monte Carlo observation algorithm is proposed, which uses a fast and accurate collision detection algorithm as a reference model for the contacts between complex shaped parts. The main contribution of the paper is the extension of the classic random...
We have proposed a multimodal sensing with optical device and its application to robotic grasp control. The proposed device provides both tactile and proximity information with high spatial resolution on the same scale of coordinates, that is necessary while grasping small and complicated-shaped objects using a robotic hand. In our proposed device, tactile information is obtained as infrared image...
Robotic manipulation tasks often require the control of forces and torques exerted on external objects. This paper presents a machine learning approach for estimating forces when no force sensors are present on the robot platform. In the training phase, the robot executes the desired manipulation tasks under controlled conditions with systematically varied parameter sets. All internal sensor data,...
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