Implementation of Inertial Navigation System for Autonomous Path Planning of Mobile Robot

Project Title

Implementation of Inertial Navigation System for Autonomous Path Planning of Mobile Robot

Project Area of Specialization RoboticsProject Summary

Our project is basically the implementation of INERTIAL NAVIGATION SYSTEM (INS) on indoor mobile robot. The main objective of our project is that, our robot would follow the per planned path and reached the desired location without any disturbance.

If just in case our robot tilt or deviate due to some external disturbance or force from its original heading while moving toward the  desired goal, so we would have control to detect that disturbance and correct the heading of our robot according to the location of desired goal and then make our robot to continue its movement.

Project Objectives

The objectives of our project are following ;

• First of all we examined our experimental field and its surrounding, then we decided the path that our robot followed. In our case we had indoor experimental field of 8×8 feet.
•  We divided our experimental field into a number of grids having multiple intersection points (nodes) and we expressed this field in 2D i.e X and Y co-ordinates .As we have decided our pre-planned path ,so our next objective is  that our robot would follow this pre-planned path correctly.To achieve this objective we have designed a path planning algorithm with the help of spline algorithm
•  For point by point tracking and monitoring of our robot we have implemented Inertial Navigation System (INS) on our indoor robot which provides us information about our robot’s localization, heading & velocity.
• On the bases of the information we get from INS, we can easily correct our robot’s heading and orientation. For this we had another steering algorithm which compared the robot’s actual localization and our desired robot’s localization. In case of any error, INS would detect the error and on the bases of the information we get from INS, we correct our robot’s heading and orientation and make our robot move towards the desired path.

Project Implementation Method

Basically the main moto of our project would that , our robot would follow the pre-planned path and reach the correct destination , and just in case if our robot deviate from its original path due to some external force ,then we would have control to correct its heading and make robot move toward the desire path.

To achieve our goal,

1. We must know the experimental field and its surroundings so that we can decide the pre-planned path for our robot to move.
2. We must know the movement of our robot point by point w.r.t time, so that in case of any disturbance we must have known.

Path planning;

In cubic splines two consecutive points are considered to be joined by a cubic polynomial Six=aix3+bix2+cix+di that is valid only for xi?x?xi+1. For each spline coefficients are determine for each function. For this certain initial and final conditions are assumed in the trajectory.  

As the robot navigates though the trajectory point by point, the on board controller compares the trajectory of the actual movement against the pre-planned movement and in the case of deviation, such as a collision with an external object that causes a change in orientation, the robot reacts by first measuring the magnitude and direction of collision, then reacts by returning to its original movement.   

Implementation of INS;

To get the tracking of our robot point by point we implemented INERTIAL NAVIGATION SYSTEM (INS) on our mobile robot. INS is actually the combination of both IMU SENSOR and Navigational equation algo implementation to extract useful data.

MEMS BASED IMU SENSOR(MPU6050); 

• IMU sensor like MPU 6050 are used in self-balancing robot, for example in our case it would help to keep our robot its correct heading and orientation. IMU sensors help us to get the position of an object on which it is placed or attached. they are used to detect the orientation of robot in indoor and outdoor environment
•  The MPU 6050 is a 6 DOF or a six-axis IMU sensor, which means that it gives six values as output (three values for accelerometer and three from the gyroscope), in our case we just dealt with 3 DOF, 2 linear movement along x-axis and y-axis and rotation around z-axis (YAW).   

Navigational equation ;

The INS unit integrates the measurements of the IMU sensor to derive a navigation solution using equations of motion and relative orientation. For the case of our mobile robot, the Inertial Navigation System (INS) derives the position, velocity, and yaw movement. And on the basis of the parameters we get from INS , we can correct the heading of our robot using steering algorithm, whcih actually compare the actual parameters we ge from INS with the desired parameters and make the reaction accordingly in case of any error

                                                                                                                                                                                              Benefits of the Project

This project is part of the MEMS Application in Robotics research group based in SSCASE-IT. Our research group focuses on designing and applying MEMS based sensors in the area of robotics to measure and understand inertial parameters which we then use as a testbench to design our own MEMS accelerometer and gyroscope sensors.

As in our FYP, one of the main focused area is on the working of inertial sensors (IMU), which has a wide range of use in autonomous transportation now a days

 IMUs are just as important as cameras and radar when it comes to operating autonomous vehicle. An inertial measurement unit (IMU) is a device that directly measures a vehicle’s three linear acceleration components and three rotational components. An IMU is unique among the sensors typically found in an autonomous vehicle (AV) because an IMU needs no connection to or knowledge of the external world. This environment independence makes the IMU a core technology for safety.

  

                                                            

If an autonomous vehicle wanders in its lane, it will appear to be driven by a bad driver. And wandering out of a lane during a turn could easily result in an accident. The IMU is a key dynamic sensor to steer the vehicle dynamically, maintaining better than 30-cm accuracy for short periods when other sensors go offline. The IMU is also used in algorithms that can cross-compare position/location and then assign a certainty to the overall localization estimate.

Cameras and sensors enable the autonomous system of tomorrow to see and feel nearly like a human being such as RADAR and LIDAR. But the intelligent navigation sensing system which is based on INERTIAL MEASUREMENT UNIT(IMU)/MEMS is a key sensing pillar of autonomous driving and solutions for

• Accurate, dynamic navigation aid during GPS blockage
• Precise positioning
• High fidelity motion capture
• Infrastructure-free navigation

Single-sensor systems make way for approaches which merge multiple sensor streams together to get necessary contextual view enabling the car to make more reliable and solid autonomous decisions.

Technical Details of Final Deliverable

The area of focus in autonomous robots is centered around how the mobile robot reaches its destination. To reach its designated destination, pre-planned paths are utilized to drive a mobile robot across a set of points in a map. The task to navigate autonomously is divided into mapping of the local environment, localization and trajectories with motor control.

The task of localization determines where the mobile robot is positioned with respect to its environment. This area, focuses on the parameters such as heading, orientation, and distance covered. Further details on localization are discussed in the INS section. 

IMPLEMENTATION OF INS:

The Inertial Navigation System (INS) uses an IMU to form a self-contained navigation system which uses measurements provided by the IMU to track the position, altitude, velocity, and orientation of an object relative to a starting point, orientation, and velocity. The parameters of focus are derived using

• IMU SENSORS:The Inertial Measurement Unit sensor or IMU is an integrated sensor package that combines MEMS based accelerometers and gyros to produce a three-dimensional measurement of linear acceleration and angular rates with respect to an inertial reference frame
• NAVIGATION EQUATIONS: The INS unit integrates the measurements of the IMU sensor to derive a navigation solution using equations of motion and relative orientation. For the case of our mobile robot, the Inertial Navigation System (INS) derives the position, velocity, and yaw movement.

To represent the trajectories splines (as piecewise polynomial curves) were used because they offer the representation of a path in terms of linear lines. This allows the robot to drive with more precision across each line and provides a better control on parameters such as jerk and shock. The parameters considered here are time taken during travel, path smoothness and driving velocity.

     

Final Deliverable of the Project Hardware SystemCore Industry OthersOther IndustriesCore Technology RoboticsOther TechnologiesSustainable Development GoalsRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	61450
Robot chassis	Equipment	1	15000	15000
Dc motors	Equipment	2	6000	12000
Li-po battery	Equipment	2	2200	4400
Charger	Equipment	1	750	750
Arduino	Equipment	2	1600	3200
H-bridges	Equipment	2	300	600
Bluetooth module	Equipment	2	600	1200
IMU sensors	Equipment	1	300	300
Gyroscope sensor	Equipment	1	24000	24000