Titlebook: Algorithmic Foundations of Robotics XII; Proceedings of the T Ken Goldberg,Pieter Abbeel,Lauren Miller Book 2020 Springer Nature Switzerlan

MONY

Multiple Start Branch and Prune Filtering Algorithm for Nonconvex Optimization,on. Many approaches have been developed to carry out such nonconvex optimization, but they suffer drawbacks including large computation time, require tuning of multiple unintuitive parameters and are unable to find multiple local/global minima. In this work we introduce multiple start branch and pru

expeditious

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bizarre

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A Certifiably Correct Algorithm for Synchronization over the Special Euclidean Group,of their pairwise relative transforms .. Examples of this class include the foundational problems of pose-graph simultaneous localization and mapping (SLAM) (in robotics) and camera motion estimation (in computer vision), among others. This problem is typically formulated as a nonconvex maximum-like

Narrative

Autonomous Visual Rendering using Physical Motion,ens, brushes, or other tools. This work uses ergodicity as a control objective that translates planar visual input to physical motion without preprocessing (e.g., image processing, motion primitives). We achieve comparable results to existing drawing methods, while reducing the algorithmic complexit

dissolution

Cloud-based Motion Plan Computation for Power-Constrained Robots,loud-based compute service. To meet the requirements of an interactive and dynamic scenario, robot motion planning may need more computing power than is available on robots designed for reduced weight and power consumption (e.g., battery powered mobile robots). In our method, the robot communicates

戰(zhàn)役

Combining System Design and Path Planning,ted to find the best design that optimizes its motion between two given configurations. Solving individual path planning problems for all possible designs and selecting the best result would be a straightforward approach for very simple cases. We propose a more efficient approach that combines discr

表示問(wèn)

Language-Guided Sampling-based Planning using Temporal Relaxation,guage-guided biasing scheme. We leverage the notion of temporal relaxation of time-window temporal logic formulae (TWTL) to reformulate the temporal logic synthesis problem into an optimization problem. Our algorithm exhibits an exploration-exploitation structure, but retains probabilistic completen

HAVOC

Generating Plans that Predict Themselves,ammates’ actions early on can give us a clear idea of what the remainder of their plan is, i.e. what action sequence we should expect. In others, they might leave us less confident, or even lead us to the wrong conclusion. Our goal is for robot actions to fall in the first category: we want to enabl