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Titlebook: Algorithmic Foundations of Robotics XI; Selected Contributio H. Levent Akin,Nancy M. Amato,A. Frank Stappen Book 2015 Springer Internationa

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31#
發(fā)表于 2025-3-26 22:13:41 | 只看該作者
32#
發(fā)表于 2025-3-27 04:50:50 | 只看該作者
Active Control Strategies for Discovering and Localizing Devices with Range-Only Sensors,ices. We develop separate information based objectives to achieve both goals, and examine ways of combining them into a unified approach. Despite the computational complexity of calculating these policies for multiple robots over long time horizons, a series of approximations enable all calculations
33#
發(fā)表于 2025-3-27 07:25:47 | 只看該作者
34#
發(fā)表于 2025-3-27 10:10:51 | 只看該作者
35#
發(fā)表于 2025-3-27 16:04:05 | 只看該作者
Computing Large Convex Regions of Obstacle-Free Space Through Semidefinite Programming,gions of obstacle-free space through a series of convex optimizations. These regions can be used, for example, to efficiently optimize an objective over collision-free positions in space for a robot manipulator. The algorithm alternates between two convex optimizations: (1) a quadratic program that
36#
發(fā)表于 2025-3-27 20:58:17 | 只看該作者
A Region-Based Strategy for Collaborative Roadmap Construction,ilds an approximate representation of the planning space. While these planners have demonstrated success in many scenarios, there are still difficult problems where they lack robustness or efficiency, e.g., certain types of narrow spaces. Conversely, human intuition can often determine an approximat
37#
發(fā)表于 2025-3-28 01:50:28 | 只看該作者
Efficient Sampling-Based Approaches to Optimal Path Planning in Complex Cost Spaces,igh-dimensional problems. However, standard versions of these algorithms cannot guarantee optimality or even high-quality for the produced paths. In recent years, variants of these methods, taking cost criteria into account during the exploration process, have been proposed to compute high-quality p
38#
發(fā)表于 2025-3-28 05:44:48 | 只看該作者
Real-Time Predictive Modeling and Robust Avoidance of Pedestrians with Uncertain, Changing Intentioare particularly challenging to model, as their motion patterns are often uncertain and/or unknown .. This paper presents a novel changepoint detection and clustering algorithm that, when coupled with offline unsupervised learning of a Gaussian process mixture model (DPGP), enables quick detection o
39#
發(fā)表于 2025-3-28 09:32:11 | 只看該作者
40#
發(fā)表于 2025-3-28 13:31:10 | 只看該作者
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