Merge pull request #190 from sterlingm/master

New robotics papers

robotics/README.md

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