The gennav's discuss from erc-bpgc

Create djikstra function

This will call astart with 0 heuristic internally.

Add nearest_obstacle_distance method to scan environment

The nearest_obstacle_distance method returns the distance to the nearest obstacle. Check the base.py file in envs to know about the general implementation of the method. As an example you can also take a look at the method implemented in the PolygonEnv.

Add potential field planner

Test PRM on trotbot

Good issue for those who want to get famililar with ROS also

Add bugflood implementation

Add plan function in PRM Path Planner

Path Post Processing

Implement the following path post processing algorithms

Interpolation based path smoothening
Bezeir Curves
B-splines
Cubic-Splines

add differential pid controller

Add PRM* Path Planner

Add methods for path shortcutting

Implement the algorithms given below in the resource.
Link: http://www.osrobotics.org/osr/planning/post_processing.html

Make samplers a callable class

Add Occupancy Grid Environment

Add occupancy gird environment

Add wavefront planner

https://www.youtube.com/watch?v=Ls8EBoG_SEQ&t=1694s

This lecture is a good starting point to understand apf planning algorithms. A unique requirement in wavefront planner is that you need to represent the planning area in the form of a grid world. Asking the user for the coordinates of the points enclosing the grid environment(for eg. the coordinates of end points in case of a polygonal grid world) would be the preferable way to go about this. The dimension of each cell in the grid depends upon the intended resolution

Updated RRT and PRM to use new node class

Adding odometry simulator

A class for an odometry simulator would be very useful for testing controllers. SInce our courrent controllers output a velocity, the simulator would take the velocity command at each step and numerically integrate (basically add) it to get distance travelled.

Now to simulate real life conditions, instead of giving back the position derived directly by integrating (the true position) the class will add gaussian noise (using np.random.randn) to it and then return it back to controller. The simulator would be added in /utils

Basic structure would be

class Simulator
    def __init__(controller)
        ...
    def run(parameters)
        ...

Adding replan to all the planners

Add utils/common.py

Add a file utils/common.py for storing common datatypes and functions

Streamline RRT and RRT*

Improve docs

Organise docs into logical sections
Add intro text
Add examples
Fix minor formatting issues in docstrings (good first issue)

We are using this style guide

Add PRM path planner

Add omni-PID controller

Add benchmarks in the documentation

Add RT-RRT* Path Planning

RT-RRT*.pdf
This is the Real Time RRT* research paper which contains the algorithm.

Add tests for envs

Refactor RRT to follow planner base class

Implement a method to convert Laser Scan data into an Occupancy grid

Most of the robots are equipped with a laser scanner. A sample implementation of algorithms using a laser scanner data can be found in the scan_env.py in envs. Implement a function that takes an input of such data and updates an occupancy grid.