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检索条件"丛书名=Springer Tracts in Advanced Robotics"

共 918 条记录，以下是21-30 订阅

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Efficient Planning in Non-Gaussian Belief Spaces and Its Application to Robot Grasping 15th

Efficient Planning in Non-Gaussian Belief Spaces and Its App...

引用

15th International Symposium of robotics Research (ISRR)

作者： Platt, Robert Kaelbling, Leslie Lozano-Perez, Tomas Tedrake, Russ MIT Comp Sci & Artificial Intelligence Lab 32 Vassar St Cambridge MA 02139 USA

ISBN: (纸本)9783319293639;9783319293622

The limited nature of robot sensors make many important robotics problems partially observable. These problems may require the system to perform complex information-gathering operations. One approach to solving these problems is to create plans in belief-space, the space of probability distributions over the under-lying state of the system. The belief-space plan encodes a strategy for performing a task while gaining information as necessary. Most approaches to belief-space planning rely upon representing belief state in a particular way (typically as a Gaussian). Unfortunately, this can lead to large errors between the assumed density representation of belief state and the true belief state. This paper proposes a new sample-based approach to belief-space planning that has fixed computational complexity while allowing arbitrary implementations of Bayes filtering to be used to track belief state. The approach is illustrated in the context of a simple example and compared to a prior approach. Then, we propose an application of the technique to an instance of the grasp synthesis problem where a robot must simultaneously localize and grasp an object given initially uncertain object parameters by planning information-gathering behavior. Experimental results are presented that demonstrate the approach to be capable of actively localizing and grasping boxes that are presented to the robot in uncertain and hard-to-localize configurations.

关键词： Probability distributions

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Soft Mobile Robots with On-Board Chemical Pressure Generation 15th

Soft Mobile Robots with On-Board Chemical Pressure Generatio...

引用

15th International Symposium of robotics Research (ISRR)

作者： Onal, Cagdas D. Chen, Xin Whitesides, George M. Rus, Daniela MIT Comp Sci & Artificial Intelligence Lab 77 Massachusetts Ave Cambridge MA 02139 USA Harvard Univ Dept Chem & Chem Biol Cambridge MA 02138 USA

ISBN: (纸本)9783319293639;9783319293622

We wish to develop robot systems that are increasingly more elastic, as a step towards bridging the gap between man-made machines and their biological counterparts. To this end, we develop soft actuators fabricated from elastomer films with embedded fluidic channels. These actuators offer safety and adaptability and may potentially be utilized in robotics, wearable tactile interfaces, and active orthoses or prostheses. The expansion of fluidic channels under pressure creates a bending moment on the actuators and their displacement response follows theoretical predictions. Fluidic actuators require a pressure source, which limits their mobility and mainstream usage. This paper considers instances of mechanisms made from distributed elastomer actuators to generate motion using a chemical means of pressure generation. A mechanical feedback loop controls the chemical decomposition of hydrogen peroxide into oxygen gas in a closed container to self-regulate the actuation pressure. This on-demand pressure generator, called the pneumatic battery, bypasses the need for electrical energy by the direct conversion of chemical to mechanical energy. The portable pump can be operated in any orientation and is used to supply pressure to an elastomeric rolling mobile robot as a representative for a family of soft robots.

关键词： Soft robotics Fluidic elastomer actuators Chemical pressure generation Distributed actuation Smart materials

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Analytical Least-Squares Solution for 3D Lidar-Camera Calibration 15th

Analytical Least-Squares Solution for 3D Lidar-Camera Calibr...

引用

15th International Symposium of robotics Research (ISRR)

作者： Mirzaei, Faraz M. Kottas, Dimitrios G. Roumeliotis, Stergios I. Univ Minnesota Minneapolis MN 55455 USA

ISBN: (纸本)9783319293639;9783319293622

This paper addresses the problem of estimating the intrinsic parameters of the 3D Velodyne lidar while at the same time computing its extrinsic calibration with respect to a rigidly connected camera. Existing approaches to solve this nonlinear estimation problem are based on iterative minimization of nonlinear cost functions. In such cases, the accuracy of the resulting solution hinges on the availability of a precise initial estimate, which is often not available. In order to address this issue, we divide the problem into two least-squares sub-problems, and analytically solve each one to determine a precise initial estimate for the unknown parameters. We further increase the accuracy of these initial estimates by iteratively minimizing a batch nonlinear least-squares cost function. In addition, we provide the minimal observability conditions, under which, it is possible to accurately estimate the unknown parameters. Experimental results consisting of photorealistic 3D reconstruction of indoor and outdoor scenes are used to assess the validity of our approach.

关键词： Optical radar

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Pose Graph Compression for Laser-Based SLAM 15th

Pose Graph Compression for Laser-Based SLAM

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15th International Symposium of robotics Research (ISRR)

作者： Stachniss, Cyrill Kretzschmar, Henrik Univ Freiburg Inst Comp Sci Freiburg Germany Univ Bonn Inst Geodesy & Geoinformat Bonn Germany

ISBN: (纸本)9783319293639;9783319293622

The pose graph is a central data structure in graph-based SLAM approaches. It encodes the poses of the robot during data acquisition as well as spatial constraints between them. The size of the pose graph has a direct influence on the runtime and the memory requirements of a SLAM system since it is typically used to make data associations and within the optimization procedure. In this paper, we address the problem of efficient, information-theoretic compression of such pose graphs. The central question is which sensor measurements can be removed from the graph without loosing too much information. Our approach estimates the expected information gain of laser measurements with respect to the resulting occupancy grid map. It allows us to restrict the size of the pose graph depending on the information that the robot acquires about the environment. Alternatively, we can enforce a maximum number of laser scans the robot is allowed to store, which results in an any-space SLAM system. Real world experiments suggest that our approach efficiently reduces the growth of the pose graph while minimizing the loss of information in the resulting grid map.

关键词： Robots

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Probabilistic Collision Detection Between Noisy Point Clouds Using Robust Classification 15th

Probabilistic Collision Detection Between Noisy Point Clouds...

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15th International Symposium of robotics Research (ISRR)

作者： Pan, Jia Chitta, Sachin Manocha, Dinesh UNC Dept Comp Sci Chapel Hill NC 27599 USA Willow Garage Inc Menlo Pk CA 94025 USA

ISBN: (纸本)9783319293639;9783319293622

We present a new collision detection algorithm to perform contact computations between noisy point cloud data. Our approach takes into account the uncertainty that arises due to discretization error and noise, and formulates collision checking as a two-class classification problem. We use techniques from machine learning to compute the collision probability for each point in the input data and accelerate the computation using stochastic traversal of bounding volume hierarchies. We highlight the performance of our algorithm on point clouds captured using PR2 sensors as well as synthetic data sets, and show that our approach can provide a fast and robust solution for handling uncertainty in contact computations.

关键词： Stochastic systems

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The Importance of Structure 15th

The Importance of Structure

引用

15th International Symposium of robotics Research (ISRR)

作者： Ek, Carl Henrik Kragic, Danica Univ Bristol Bristol Avon England Royal Inst Technol Stockholm Sweden

ISBN: (纸本)9783319293639;9783319293622

Many tasks in robotics and computer vision are concerned with inferring a continuous or discrete state variable from observations and measurements from the environment. Due to the high-dimensional nature of the input data the inference is often cast as a two stage process: first a low-dimensional feature representation is extracted on which secondly a learning algorithm is applied. Due to the significant progress that have been achieved within the field of machine learning over the last decade focus have placed at the second stage of the inference process, improving the process by exploiting more advanced learning techniques applied to the same (or more of the same) data. We believe that for many scenarios significant strides in performance could be achieved by focusing on representation rather than aiming to alleviate inconclusive and/or redundant information by exploiting more advanced inference methods. This stems from the notion that;given the "correct" representation the inference problem becomes easier to solve. In this paper we argue that one important mode of information for many application scenarios is not the actual variation in the data but the rather the higher order statistics as the structure of variations. We will exemplify this through a set of applications and show different ways of representing the structure of data.

关键词： Learning algorithms

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Introduction to the Robot Town Project and 3-D Co-operative Geometrical Modeling Using Multiple Robots 15th

Introduction to the Robot Town Project and 3-D Co-operative ...

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15th International Symposium of robotics Research (ISRR)

作者： Kurazume, Ryo Iwashita, Yumi Murakami, Koji Hasegawa, Tsutomu Kyushu Univ Nishi Ku 744Motooka Fukuoka 8190395 Japan Jet Prop Lab M-S 198-235 4800 Oak Grove Dr Pasadena CA 91109 USA Kyushu Sangyo Univ Higashi Ku 2-3-1Matsukadai Fukuoka 8138503 Japan Kumamoto Natl Coll Technol 2659-2Suya Koshi Kumamoto 8611102 Japan

ISBN: (纸本)9783319293639;9783319293622

This paper introduces the author's research project called the "Robot Town Project". Service robots, which co-exist with humans and provide various services in daily life, must have sufficient ability to sense changes in the environment and deal with a variety of situations. However, since the daily environment is complex and unpredictable, it is almost impossible with current methods to sense all the necessary information using only a robot and the attached sensors. One promising approach for robots to co-exist with humans is to use IT technology, such as a distributed sensor network and network robotics. As an empirical example of this approach, the authors have started Robot Town Project. The aim of this research project is to develop a distributed sensor network system covering an area of a block in a town in which there are many houses, buildings, and roads, and manage robot services by monitoring events that occur in the town. This paper introduces currently available technologies including an RFID-tag-based localization system, distributed sensor systems for moving object tracking, and object management systems using RFID tags. For the construction of 3-D geometrical models of large-scale environments, a measurement and modeling system using a group of multiple robots and an on-board laser range finder is also introduced.

关键词： Geometry

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Demonstration-Guided Motion Planning 15th

Demonstration-Guided Motion Planning

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15th International Symposium of robotics Research (ISRR)

作者： Ye, Gu Alterovitz, Ron Univ N Carolina Dept Comp Sci Chapel Hill NC 27599 USA

ISBN: (纸本)9783319293639;9783319293622

We present demonstration-guided motion planning (DGMP), a new frame-work for planning motions for personal robots to perform household tasks. DGMP combines the strengths of sampling-based motion planning and robot learning from demonstrations to generate plans that (1) avoid novel obstacles in cluttered environments, and (2) learn and maintain critical aspects of the motion required to successfully accomplish a task. Sampling-based motion planning methods are highly effective at computing paths from start to goal configurations that avoid obstacles, but task constraints (e.g. a glass of water must be held upright to avoid a spill) must be explicitly enumerated and programmed. Instead, we use a set of expert demonstrations and automatically extract time-dependent task constraints by learning low variance aspects of the demonstrations, which are correlated with the task constraints. We then introduce multi-component rapidly-exploring roadmaps (MC-RRM), a sampling-based method that incrementally computes a motion plan that avoids obstacles and optimizes a learned cost metric. We demonstrate the effectiveness of DGMP using the Aldebaran Nao robot performing household tasks in a cluttered environment, including moving a spoon full of sugar from a bowl to a cup and cleaning the surface of a table.

关键词： Motion planning

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Planning Complex Inspection Tasks Using Redundant Roadmaps 15th

Planning Complex Inspection Tasks Using Redundant Roadmaps

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15th International Symposium of robotics Research (ISRR)

作者： Englot, Brendan Hover, Franz MIT 77 Massachusetts Ave Cambridge MA 02139 USA

ISBN: (纸本)9783319293639;9783319293622

The aim of this work is fast, automated planning of robotic inspections involving complex 3D structures. A model comprised of discrete geometric primitives is provided as input, and a feasible robot inspection path is produced as output. Our algorithm is intended for tasks in which 2.5D algorithms, which divide an inspection into multiple 2D slices, and segmentation-based approaches, which divide a structure into simpler components, are unsuitable. This degree of 3D complexity has been introduced by the application of autonomous in-water ship hull inspection;protruding structures at the stern (propellers, shafts, and rudders) are positioned in close proximity to one another and to the hull, and clearance is an issue for a mobile robot. A global, sampling-based approach is adopted, in which all the structures are simultaneously considered in planning a path. First, the state space of the robot is discretized by constructing a roadmap of feasible states;construction ceases when each primitive is observed by a specified number of states. Once a roadmap is produced, the set cover problem and traveling salesman problem are approximated in sequence to build a feasible inspection tour. We analyze the performance of this procedure in solving one of the most complex inspection planning tasks to date, covering the stern of a large naval ship, using an a priori triangle mesh model obtained from real sonar data and comprised of 100,000 primitives. Our algorithm generates paths on a par with dual sampling, with reduced computational effort.

关键词： Inspection

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Prediction and Planning Methods of Bipedal Dynamic Locomotion Over Very Rough Terrains 15th

Prediction and Planning Methods of Bipedal Dynamic Locomotio...

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15th International Symposium of robotics Research (ISRR)

作者： Sentis, Luis Fernandez, Benito R. Slovich, Michael Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9783319293639;9783319293622

Although the problem of dynamic locomotion in very rough terrain is critical to the advancement of various areas in robotics and health devices, little progress has been made on generalizing gait behavior with arbitrary paths. Here, we report that perturbation theory, a set of approximation schemes that has roots in celestial mechanics and non-linear dynamical systems, can be adapted to predict the behavior of non closed-form integrable state-space trajectories of a robot's center of mass, given its arbitrary contact state and center of mass (CoM) geometric path. Given an arbitrary geometric path of the CoM and known step locations, we use perturbation theory to determine phase curves of CoM behavior. We determine step transitions as the points of intersection between adjacent phase curves. To discover intersection points, we fit polynomials to the phase curves of neighboring steps and solve their differential roots. The resulting multi-step phase diagram is the locomotion plan suited to drive the behavior of a robot or device maneuvering in the rough terrain. We provide two main contributions to legged locomotion: (1) predicting CoM state-space behavior for arbitrary paths by means of numerical integration, and (2) finding step transitions by locating common intersection points between neighboring phase curves. Because these points are continuous in phase they correspond to the desired contact switching policy. We validate our results on a human-size avatar navigating in a very rough environment and compare its behavior to a human subject maneuvering through the same terrain.

关键词： Dynamics

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