From 975911b5ed2e4a1a702478380fbf52bed4558268 Mon Sep 17 00:00:00 2001 From: Soraxas Date: Fri, 15 Oct 2021 23:56:33 +1100 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 0da8d55..a8d1de1 100644 --- a/README.md +++ b/README.md @@ -7,9 +7,9 @@ [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/github/license/soraxas/sbp-env.svg)](https://github.com/soraxas/sbp-env/blob/master/LICENSE) -Sampling-based motion planners' testing environment (`sbp-env`) is a full feature framework to quickly test different sampling-based algorithm for motion planning. `sbp-env` focuses on flexibility of tinkering with different aspect of the framework, and had divided the main planning components into two categories (i) **samplers** and (ii) **planners**. +Sampling-based motion planners' testing environment (`sbp-env`) is a full feature framework to quickly test different sampling-based algorithms for motion planning. `sbp-env` focuses on the flexibility of tinkering with different aspects of the framework, and had divided the main planning components into two categories (i) **samplers** and (ii) **planners**. -The focus of *motion planning planning research* had been mainly on (i) improving the sampling efficiency (with methods such as heuristic or learned distribution) and (ii) the algorithmic aspect of the planner using different routine to build a connected graph. Therefore, by separating the two components one can quickly swap out different components to test novel ideas. +The focus of *motion planning research* had been mainly on (i) improving the sampling efficiency (with methods such as heuristic or learned distribution) and (ii) the algorithmic aspect of the planner using different routines to build a connected graph. Therefore, by separating the two components one can quickly swap out different components to test novel ideas. Have a look at the [documentations](https://cs.tinyiu.com/sbp-env) for more detail information. If you are looking for the previous code for the RRdT* paper it is now archived at [soraxas/rrdt](https://github.com/soraxas/rrdt).