轨迹规划与控制___下载.zip

## Quadrotor simulation ### This project contains: - Informed RRT* to plan a collision free path from start to goal position in an N-dimensional Map. - A minimum snap trajectory generator. The segment times between consecutive waypoints are also optimised. - Nonlinear geometric controller for aggressive trajectory tracking and hover controller - Quadrotor Simulator ### Dependencies - scipy, numpy, matplotlib, rtree-linux ### Usage #### Trajectory generation and control example ```python from TrajGen import trajGenerator, Helix_waypoints from Quadrotor import QuadSim import controller waypoints = Helix_waypoints(5) #Generate trajectory through waypoints traj = trajGenerator(waypoints,max_vel = 10,gamma = 1e6) #initialise simulation with given controller and trajectory Tmax = traj.TS[-1] des_state = traj.get_des_state sim = QuadSim(controller,des_state,Tmax) #run simulation sim.run() ```  #### With Path Planning ```python python3 runsim.py ```  find out more in [PathPlanning/README.md](./PathPlanning/README.md) ### Future Work - Adding disturbance to quadrotor model - Collision checking after trajectory generation ### References - [Polynomial Trajectory Planning for Aggressive Quadrotor Flight in Dense Indoor Environments - Charles Richter, Adam Bry, and Nicholas Roy](https://groups.csail.mit.edu/rrg/papers/Richter_ISRR13.pdf) - [Trajectory Generation and Control for Quadrotors - Daniel Mellinger and Vijay Kumar](https://repository.upenn.edu/cgi/viewcontent.cgi?article=1705&context=edissertations) - [Motion Planning as Search - Russ Tedrake](http://underactuated.csail.mit.edu/planning.html#section2)