Archives/papers-we-love_papers-we-love
1
0
Fork 0
mirror of https://github.com/papers-we-love/papers-we-love.git synced 2026-03-02 03:40:31 +00:00
Code Issues Projects Releases Wiki Activity

Fix broken links (#578)

Browse Source 
Fix broken links in operating_systems
Fix broken link in networks
Fix broken link in robotics (plus typo)
Fix Unikernel paper links
This commit is contained in:
Sébastien Portebois
2019-10-23 09:27:25 -04:00
committed by Darren
parent 1624d6d39c
commit 38bda8dae5
5 changed files with 7 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
robotics/README.md
View File

@@ -9,7 +9,7 @@ Robotics
[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)
[Probablistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces](https://www.cs.cmu.edu/~./motionplanning/papers/sbp_papers/PRM/prmbasic_01.pdf)
[Rapidly-Exploring Random Trees: A New Tool for Path Planning](http://msl.cs.uiuc.edu/~lavalle/papers/Lav98c.pdf)
@@ -29,7 +29,7 @@ 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
propose a sampling-based strategy to deal with motion planning and
created a practical method 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