Update README.md

Author: hungpham2511

README.md

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 # TOPP-RA
 [![Build Status](https://travis-ci.org/hungpham2511/toppra.svg?branch=master)](https://travis-ci.org/hungpham2511/toppra) [![Coverage Status](https://coveralls.io/repos/github/hungpham2511/toppra/badge.svg?branch=master)](https://coveralls.io/github/hungpham2511/toppra?branch=master)
 
-TOPP-RA is a library for time-parameterizing robot trajectories subject to kinematic and dynamic constraints. The current implementation supports the following constraints:
 
-1. joint velocity and acceleration bounds;
-2. torque bounds (including redundantly-actuated manipulators);
-3. contact stability for legged robots.
+**Documentation and tutorials** are available at (https://hungpham2511.github.io/toppra/).
 
-If you use this library for your research, please reference the accompanying paper [«A new approach to Time-Optimal Path Parameterization based on Reachability Analysis»](https://arxiv.org/abs/1707.07239), *IEEE Transactions on Robotics*, vol. 34(3), pp. 645–659, 2018.
+TOPP-RA is a library for time-parameterizing robot trajectories subject to kinematic and dynamic constraints. 
+In general, given the inputs:
+
+1. a geometric path `q(s)`, `s` in `[0, s_end]` ;
+2. a list of constraints on joint velocity, joint accelerations, tool Cartesian velocity, et cetera.
+
+TOPP-RA returns the time-parameterization: `s_dot (s)`, from which a trajectory `q(t)` that satisfies the given
+constraints can be computed.
+
+## Citing TOPP-RA
+If you use this library for your research, we encourage you to 
+
+1. reference the accompanying paper [«A new approach to Time-Optimal Path Parameterization based on Reachability Analysis»](https://arxiv.org/abs/1707.07239), *IEEE Transactions on Robotics*, vol. 34(3), pp. 645–659, 2018.
+2. put a star on this repository.
+
+
+## Bug reports and supports
+Please report any issues, questions via [Github issues tracker](https://github.com/hungpham2511/toppra/issues).
 
-For documentations and some tutorials, see [TOPP-RA's documentation](https://hungpham2511.github.io/toppra/).