Introduction: Navigate Robot With Shoe Sensors, W/o GPS, W/o Map

About: oblu is an indoor navigation sensor

The robot moves in a pre-programmed path and transmits (over bluetooth) its actual movement information to a phone for real-time tracking. Arduino is pre-programmed with path and oblu is used for sensing robot's motion. oblu transmits movement information to Arduino at regular interval. Based on that, Arduino controls wheels' movements to let robot follow the predefined path.


The project is about making the robot move in a pre-defined path with precision, without making use of GPS or WiFi or Bluetooth for positioning, not even map or building layout plan. And draw its actual path (to the scale), in real-time. The bluetooth can be used as a substitute of wire, for transmitting real-time location information.


Our team's prime agenda is to develop shoe-mounted pedestrian navigation sensors. However, we were approached by an academic research group with the requirement of navigating robot indoor and simultaneous monitoring its realtime position. They wanted to use such system for mapping radiation in an enclosed chamber or detected gas leakage in an industrial setup. Such places are hazardous to human beings. looking for a robust solution for indoor navigation of our Arduino based robot.

Our obvious choice for any motion sensor module (IMU) was "oblu" (Ref above image). But the tricky part here was that oblu's existing firmware was suitable for foot-mounted indoor Pedestrian Dead Reckoning (PDR ) or Pedestrian Navigation, in simple words. oblu's PDR performance in indoor as a foot-mounted IMU is quite impressive. Availability of Android app (Xoblu) for oblu's real-time tracking as shoe-sensor, adds to the advantage. However, the challenge was to make use of its existing algorithm which is based on human walking model, for navigating robot and monitoring it.

Step 3: A BRIEF INTRO TO "oblu"

"oblu" is a miniaturized, low cost and opensource development platform targeted towards wearable motion sensing applications. It is Li-ion rechargeable battery operable and allows onboard USB battery charging. It has an onboard Bluetooth (BLE 4.1) module for wireless communication. "oblu" hosts a 32-bits floating point microcontroller (Atmel's AT32UC3C) which allows solving complex navigation equations onboard. Therefore one perform all the motion processing on oblu itself and transmits just the final outcome. This makes integration of oblu with the associate system extremely simple. "oblu" also hosts multi-IMU (MIMU) array which allows sensor fusion and enhances motion sensing performance. MIMU approach adds to the uniqueness of "oblu".

oblu's internal computations are based on human walking. oblu gives out displacement between two successive steps and change in heading. How - when the foot comes in touch with the ground, speed of the sole is zero, i.e. the sole is at standstill. This way oblu detects 'steps' and corrects some internal errors. And this frequent correction of errors, results in great tracking performance. So here lies the catch. What if our robot also walks in the same fashion - move, stop, move, stop..
Infact, oblu could be used for any object whose movement has regular zero and nonzero moments. Thus we moved ahead with oblu and in no time we could assemble our robot and the tracking system.


We spend nearly 70% of our time indoors. Therefore, there are many applications which require indoor navigation of humans and machines. The most commonly used positioning solution is satellite based GPS/GNSS which is good for outdoor navigation. It fails in indoor environment or in urban environment which are not accessible to the clear sky. Such applications are geo-survey of slums or the areas under heavy tree canopy, indoor navigation of robots, positioning of rescue agents' for fire fighting, mining accidents, urban warfare etc.

The predecessor of oblu was introduced as a very compact shoe-sensor (or a PDR sensor) for the positioning of fire-fighters, which was later upgraded and modified as a highly configurable development platform for the makers who are looking for easy-accurate-affordable inertial sensing solution for indoor navigation of humans as well as robots. So far, oblu's users have demonstrated its applications in tracking pedestrians, industrial safety and resource management, tactical policing, geo-survey of GPS devoid area, self navigating robot, assistive robotics, gaming, AR/VR, treatment of movement disorders, understanding physics of motion etc. oblu is suitable for applications with space constraints, e.g. wearable motion sensing. It can also be used as a wireless IMU, thanks to the on-board Bluetooth. Presence of on-board floating point processing capability, along with four IMUs array, makes sensor fusion and motion processing possible within the module itself, which in turn results in very accurate motion sensing.


The story of this project is in the video...


The robot moves in a pre-programmed path and transmits (over bluetooth) its actual movement information to a phone for real-time tracking.

Arduino is pre-programmed with path and oblu is used for sensing robot's motion. oblu transmits movement information to Arduino at regular interval. Based on that, Arduino controls wheels' movements to let robot follow the predefined path.

The robot's path is programmed as a set of straight line segments. Each line segment is defined by its length and orientation with respect to the previous one. The robot's motion is kept discreet, i.e. it moves in straight line, but in smaller segments (lets call 'strides' for simplicity). At the end of every stride, oblu transmits stride length and extent of deviation (change in orientation) from straight line, to Arduino. Arduino corrects the alignment of robot at every step on receiving such information, if it finds deviation from the pre-defined straight line.
As per program, the robot is always supposed to move in a straight line. However, it may deviate from straight line and may walk at a certain angle or skewed path because of non-idealities like uneven surface, mass imbalance in robot assembly, architectural or electrical imbalance in dc motors or the random orientation of front free running wheel. Take one step.. correct your heading... move forward. The robot also moves backwards if it travels more than the programmed length of that particular line segment.. The next stride length depends upon the remaining distance to be covered of that particular straight line segment. The robot takes large strides when the distance to be traveled is larger and takes smaller strides close to destination (i.e. end of every straight line segment). oblu transmits data to Arduino and phone (over bluetooth) simultaneously. Xoblu (the Android app) performs some simple computation to construct the path based on the movement information received from the robot, which is used for real-time tracking on phone. (Path construction using Xoblu is illustrated in the second image).

In summary, oblu senses motion and communicates movement information to Arduino and phone at regular intervals. Based on the programmed path and the motion information (sent by oblu), Arduino controls the wheels' movements. The robot's movement is NOT remotely controlled except for start/stop commands.

For firmware of oblu visit

For Aurduino code of the robot visit


The robot could be best controlled if it walks in straight line segments only. Therefore, the path must be first modeled as a set of straight line segments.The pictures contain couple of example paths and their representations in terms of displacement and orientation. This is how the path is programmed in Arduino.

Likewise any path which is a set of straight line segments, can be defined and programmed in Arduino.


The top level system integration diagram. Arduino and oblu are part of the hardware assembly. UART is used for communication between Arduino and oblu. (Please note the connection Rx/Tx connection.) Direction of dataflow is for reference only. The whole hardware assembly communicates with smartphone (Xoblu) using bluetooth.


The detailed electrical connections between Arduino, oblu, motor driver and battery pack.


Below is how the data communication takes place between the oblu sensor mounted on the robot and smartphone, i.e. Xoblu:

Step 1: Xoblu sends START command to oblu Step 2: oblu acknowledges receiving command by sending appropriate ACK to Xoblu Step 3: oblu sends DATA packet containing displacement and orientation infromation for each stride, at every step, to Xoblu. (step = whenever detects zero motion or standstill is detected). Step 4: Xoblu acknowledges receiving last DATA packet by sending appropriate ACK to oblu. (Cycle of steps 3 and 4 is repeated until Xoblu sends STOP. On receiving STOP command, oblu executes Step 5) Step 5: STOP - (i) Stop processing in oblu (ii) Stop all outputs in oblu Please refer oblu's Application Note for details of START, ACK, DATA and STOP

Step 11: HOW DOES "oblu" IMU WORK (optional) :

Presenting some references on oblu's overview and basic principal of operation of a foot-mounted PDR sensors:

--> The available source code of oblu is targeted towards foot-mounted navigation. And it is best optimized for that purpose. Below video covers its basic principal of operation:

--> Here are couple of simple articles on foot mounted PDR sensors:
1. Track my steps

2. Continue tracking my steps

--> You may refer this document for details on pedestrian dead reckoning using foot-sensors.

Step 12: Visit "" (optional)

--> Watch the video for the possible applications of "oblu":

----------------Please do share your feedback, suggestions and leave comments.
Best Wishes!


1 oblu (an opensource IMU development platform)

1 Smart Motor Robot Car Battery Box Chassis Kit DIY Speed Encoder for Arduino

1 Solderless Breadboard Half Size

1 Male/Female Jumper Wires

2 Capacitor 1000 µF

1 Texas Instruments Dual H-Bridge motor drivers L293D

1 Arduino Mega 2560 & Genuino Mega 2560

4 Amazon Web Services AA 2800 Ni-MH Rechargeable

Robotics Contest 2017

Participated in the
Robotics Contest 2017

Internet of Things Contest 2017

Participated in the
Internet of Things Contest 2017