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45 lines
2.3 KiB
Markdown
45 lines
2.3 KiB
Markdown
Robotics
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====
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[Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow](http://www.roboticsproceedings.org/rss01/p36.pdf)
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[DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks](http://people.ee.duke.edu/~lcarin/Lihan4.21.06a.pdf)
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[The Dynamic Window Approach to Collision Avoidance](http://www.cs.washington.edu/node/4749)
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[Online Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Events](http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5350749)
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[Probablistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces](http://www.kavrakilab.org/sites/default/files/kavraki1996prm-high-dim-conf.pdf)
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[Rapidly-Exploring Random Trees: A New Tool for Path Planning](http://msl.cs.uiuc.edu/~lavalle/papers/Lav98c.pdf)
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[RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments](https://rse-lab.cs.washington.edu/postscripts/3d-mapping-iser-10-final.pdf)
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Reasoning for the new papers:
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The dynamic window approach to collision avoidance is an influential
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paper for mobile robots. The method is based on a robot's dynamics
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rather than higher-level representations of a robot and/or obstacles in
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an environment.
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The PRM and RRT algorithms are two seminal papers in robot motion
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planning. The problem of motion planning scales exponentially with the
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degrees of freedom a robot has and the degrees of freedom the obstacles
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in an environment have. Thus, planning with high degrees of freedom leads to many problems
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such as incompleteness and extremely slow speed. The PRM method was the first to
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propose a sampling-based stratey to deal with motion planning and
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created a practical method for offline planning of robot manipulators.
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The RRT method modified PRM by using a tree structure rather than a
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graph so that non-holonomic and other constraints could be considered
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when planning.
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The Instantaneous Trajectory Generation method is relatively new, but
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very important. It allows for extremely fast trajectory generation for
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robots of high degrees of freedom (motion states generated within 1
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millisecond). It has been used to implement robot sword fighting and
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other activities that require fast reaction-based planning. The author
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started a business based simply on the work and has shown the
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algorithm's success in many robot applications.
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