Imọ is a mobile robotics platform built to learn mapping, localization and path planning. The learner sports seven ultrasonic sensors, an encoder and a 9 DOF IMU.

It is currently capable of mapping. The next goal is indoor exploration while SLAMing.

Todo(in no particular order):

• remove the side and rear ultrasonic sensors
• move the embedded code to the periodic scheduler
• change the commands to a steering angle and a linear velocity magnitude
• add a position server to the kalman filter node? or just get the tf between the points of interest
• combine the laser reads into a full 360 laser scan message
• rewrite the mapping node(to cpp)
• rewrite the EKF node(to cpp)
• characterize the lidar and tune a closed loop controller
• characterize the velocity and tune a closed loop controller
• add motor easing to the mix?
• complete the sonar->lidar transition for mapping
• buy a neat container for transporting the robot
• local obstacle avoidance on the robot(VFH+?)
  • rough pose estimation on the robot
• turn off motion commands if nothing was recieved recently(define recently)
• use scan matching to relocalize(hector or cartographer)or detect and track the position of features in the map(EKF SLAM or FastSLAM)?
• implement an exploration algorithm (Frontier based? taking into account the amount of information that could be obtained from each frontier)
  • This can be contain a rosaction for navigation to the goal postition
  • implement a globalish path planner for frontier navigation
• move code to a raspberry pi?
• build or find a simulation of this robot for some of the higher level algorithm testing(MATLAB vs Gazebo)?