We present an interpolation-based planning and replanning algorithm for generating direct, low-cost paths through nonuniform cost, grids. Most grid-based path planners use discrete state transitions that artificially ...
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ISBN:
(纸本)9783540481102
We present an interpolation-based planning and replanning algorithm for generating direct, low-cost paths through nonuniform cost, grids. Most grid-based path planners use discrete state transitions that artificially constrain an agent's motion to a small set of possible headings (e.g. 0, pi/4, pi/2, etc). As a result, even 'optimal' grid-based planners produce unnatural, suboptimal paths. Our approach uses linear interpolation during planning to calculate accurate path cost estimates for arbitrary positions within each grid cell and to produce paths with a range of continuous headings. Consequently, it is particularly well suited to planning low-cost trajectories for mobile robots. In this paper, we introduce the algorithm and present a number of example applications and results.
Developing reusable robotic software is particularly difficult because there is no universally agreed upon definition of what a robot is. Over the past half-century, robots took many forms. Some were inspired by their...
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Large area mapping at high resolution underwater continues to be constrained by the mismatch between available navigation as compared to sensor accuracy. In this paper we present advances that exploit consistency and ...
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ISBN:
(纸本)9783540481102
Large area mapping at high resolution underwater continues to be constrained by the mismatch between available navigation as compared to sensor accuracy. In this paper we present advances that exploit consistency and redundancy within local sensor measurements to build high resolution optical and acoustic maps that are a consistent representation of the environment. We present our work in the context of real world data acquired using Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs) working in diverse applications including shallow water coral reef surveys with the Seabed AUV, a forensic survey of the RMS Titanic in the North Atlantic at a depth of 4100 meters using the Hercules ROV and a survey of the TAG hydrothermal vent area in the mid-Atlantic at a depth of 2600m using the Jason II ROV. Specifically we focus on the related problems of Structure from Motion and Visually Based Navigation from underwater optical imagery assuming pose instrumented calibrated cameras. We present general wide baseline solutions for these problems based on the extension of techniques from the SLAM, photogrammetric and the computer vision communities. We also examine how such techniques can be extended for the very different sensing modality and scale associated with multi-beam bathymetric mapping. For both the optical and acoustic mapping cases we also show how the consistency in mapping can be used not only for better mapping but also to refine navigation estimates.
We are concerned here with improving long range stereo by filtering image sequences. Traditionally, measurement errors from stereo camera systems have been approximated as 3-D Caussians, where the mean is derived by t...
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ISBN:
(纸本)9783540481102
We are concerned here with improving long range stereo by filtering image sequences. Traditionally, measurement errors from stereo camera systems have been approximated as 3-D Caussians, where the mean is derived by triangulation and the covariance by linearized error propagation. However, there are two problems that arise when filtering such 3-D measurements. First, stereo triangulation suffers from a range dependent statistical bias;when filtering this leads to over-estimating the true range. Second, filtering 3-D measurements derived via linearized error propagation leads to apparent filter divergence;the estimator is biased to under-estimate range. To address the first issue, we examine the statistical behavior of stereo triangulation and show how to remove the bias by series expansion. The solution to the second problem is to filter with image coordinates as measurements instead of triangulated 3-D coordinates. Compared to the traditional approach, we show that bias is reduced by more than an order of magnitude, and that the variance of the estimator approaches the Cramer-Rao lower bound.
This paper introduces the haptic communication robots we developed and proposes a method for detecting human positions and postures based on haptic interaction between humanoid robots and humans. We have developed two...
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ISBN:
(纸本)9783540481102
This paper introduces the haptic communication robots we developed and proposes a method for detecting human positions and postures based on haptic interaction between humanoid robots and humans. We have developed two types of humanoid robots that have tactile sensors embedded in a soft skin that covers the robot's entire body as tools for studying haptic communication. Tactile sensation could be used to detect a communication partner's position and posture even if the vision sensor did not observe the person. In the proposed method, the robot obtains a map that statistically describes relationships between its tactile information and human positions/postures from the records of haptic interaction taken by tactile sensors and a motion capturing system during communication. The robot can then estimate its communication partner's position/posture based on the tactile sensor outputs and the map. To verify the method's performance, we implemented it in the haptic communication robot. Results of experiments show that the robot can estimate a communication partner's position/posture statistically.
Cells and Robots is an outcome of the multidisciplinary research extending over Biology, robotics and Hybrid Systems Theory. It is inspired by modeling reactive behavior of the immune system cell population, where eac...
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ISBN:
(数字)9783540719823
ISBN:
(纸本)9783540719816
Cells and Robots is an outcome of the multidisciplinary research extending over Biology, robotics and Hybrid Systems Theory. It is inspired by modeling reactive behavior of the immune system cell population, where each cell is considered as an independent agent. In our modeling approach, there is no difference if the cells are naturally or artificially created agents, such as robots. This appears even more evident when we introduce a case study concerning a large-size robotic population scenario. Under this scenario, we also formulate the optimal control of maximizing the probability of robotic presence in a given region and discuss the application of the Minimum Principle for partial differential equations to this problem. Simultaneous consideration of cell and robotic populations is of mutual benefit for Biology and robotics, as well as for the general understanding of multi-agent system dynamics. The text of this monograph is based on the PhD thesis of the first author. The work was a runner-up for the fifth edition of the Georges Giralt Award for the best European PhD thesis in robotics, annually awarded by the European robotics Research Network (EURON).
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