Tag Archives: robots

Integrating Time, Memory, and Heading Capability, Part IV

1 Reply

Posted 07/26/18,

In my last post on this subject, I described my efforts to troubleshoot an intermittent ‘bad data’ problem I experienced with the Inversense MPU6050/DMP breakout board from DFRobots.   The calculated yaw value would occasionally ‘lose synch with reality’ and start varying wildly.   I finally tracked this down to occasional bad reads from the DMP FIFO; the read would extract bytes from two different packets, producing an invalid yaw value.   The fix for this problem is to monitor the FIFO ‘bytes remaining’ count and reset the FIFO whenever the ‘bytes remaining’ count is not an integral multiple of the packet size.

After demonstrating that I could run the MPU6050 for days (literally) without any bad data occurrences, I thought I was home free in my effort to provide relative heading information for precise turns, but I ran into yet another problem when I tried to integrate the MPU6050 back onto the robot.   This time the problem was a hangup problem; after some tens of minutes, the program would stop responding at all – as if it had gone into an infinite loop somewhere (which is exactly what was happening, but I’m getting ahead of myself…).

This problem turned out to be a ‘simple’ I2C wire-length issue; I was able to demonstrate that the problem would occur any time the I2C ICL/SDA wire length went beyond about 42 cm, and would not occur with wire lengths below about 30 cm.   The problem did not appear to be sensitive to I2C bus speed (at least not for the default 100KHz or for a reduced clock speed of 50KHz) or pullup resistor value – just to wire length.

The rest of this post is a copy of my troubleshooting notes from the effort to track this problem down and solve it.   I have found in the past that when facing a non-trivial problem with multiple possible causal factors, a troubleshooting journal is an absolute must.   In the pre-computer days (you do remember there was a time before ubiquitous computing don’t you?), I used a real MIT engineering notebook for this purpose, and then later on a 3-ring binder into which I added quadrille-ruled sheets covered with my notes and drawings.   Then I moved on to Word documents – nicer because I could include Excel plots, Visio drawings, photos, and other mixed media.   Now that I have graduated to a WordPress blog, I can use it as a repository of my working notes, while also allowing others to see the inner workings of a mad scientist’s mind ;-).

I2C Hangup problem with Inversense MPU6050

Download

Stay tuned,

Frank

 

Integrating Time, Memory, and Heading Capability, Part III

Leave a reply

Posted 12 July 2018

In the last installment of this particular saga, I described another chapter in my ongoing effort to add heading knowledge to Wall-E2’s (my autonomous wall-following robot) super powers.   In that post, I described my attempt to utilize the Inversense IMU 6050 6DOF breakout board from DFRobots.   I posted some results that showed problems with vibration screwing up the results, and then getting error-free results using an ‘air pillow’ (a piece of air-filled packing material).   At the time, this led me to believe that the cause of the bad data was motor vibration.   However, when I tried adding some foam vibration dampening material, it didn’t seem to help – I was still getting intermittent stretches of bad data, with or without the motors running.   Clearly I  still didn’t understand what was happening.

Once again I ran away from the whole thing, to regroup and let my mind work on the problem for a while; back to basketball, bridge, and general goofing off.

After some more web research and just thinking about what I knew and didn’t know, I started to suspect that what I was seeing was an artifact of the way the sensor(s) communicated with the main controller via the I2C serial interface.   When yaw measurements went bad, they went  really bad, rapidly cycling from positive to negative values, and this didn’t make a lot of sense.   Maybe the main controller wasn’t keeping up with the sensor data stream, and   the software was trying to form heading values using bits from two different measurements; this would explain why the heading sign changed from measurement to measurement.   Also, I wasn’t utilizing the INT pin on the IMU6050 module, just pulling data out of the FIFO as rapidly as possible; could that be part of the problem too?

So, I decided to start all over again with the IMU6050 sensor on an ASP plugboard, with a spare Arduino Mega 2560 controller identical to the one being used to run Wall-E2, as shown in the following photo.   I also hooked up the INT pin, and used Jeff Rowberg’s I2CDev materials and MPU6050 example programs as the starting point.

DFRobots Inversense IMU6050 breakout board (board with blue LED, between FRAM and RTC) on an ASP plugboard, controlled by an Arduino Mega 2560

After getting everything going, I ran some long-term tests to see I could produce ‘bad’ yaw readings independent of the robot platform.   And, of course, I couldn’t get the darned thing to fail, no matter how long I ran it.   Shown below is a 20-minute long plot

20-minute run with no observed problems

Next, I tried inserting some delays into the ‘do other stuff’ part of the main loop, to try and simulate the normal robot processing delays.   This had no effect up until the delay reached 40mSec or so, and then I started to see problems very similar to what I had seen before with both the MPU9250 and 6050 sensor setups.

On robot test displaying yaw value and bytes remaining in MPU6050 FIFO

Then I modified the code again to check for FIFO byte lengths that weren’t an integral multiple of the normal packet length (42 in this case), and to reset the FIFO if the condition was detected. This seemed to eliminate the ‘bad data’ effect, regardless of the amount of delay introduced in the processing portion of loop().

About 6 minutes with the motors running. Program modified to reset the FIFO whenever a non-modulo ‘bytes remaining’ condition was detected

Detail view of the last 100 seconds of the previous plot

Summary:

The Invensense MPU6050/DMP/FIFO combination is sensitive to delays in the main   processing loop, even when using the INT line with an Interrupt Service Routine (ISR).   When the main loop processing delays get beyond about 40mSec, the  ‘mpu.getFIFOBytes(fifoBuffer, packetSize);’ call will occasionally  not remove the correct number of bytes from the FIFO, leaving a non-modulo (packetsize) number of bytes remaining in the FIFO.   When this happens, the next read will get (and process) bytes from two different packets, resulting in wildly varying yaw value outputs.   This condition is (now, after knowing what’s going on) fairly easy to recognize, as the error condition generally causes adjacent yaw values to have different signs, resulting in a classic sawtooth output.

The way to eliminate this artifact is to check for non-modulo (packetsize) FIFO bytes remaining value each time, and reset the FIFO when this happens.   Whatever good data is still in the FIFO will be lost, but the data that you do get will be valid.

I have included below my test program, with the FIFO modulo check and FIFO reset mechanism.   Note that this program also includes my motor control code, which obviously will not work with your setup.

 

Stay tuned,

Frank

 

 

 

 

Integrating Time, Memory, and Heading Capability

2 Replies

Posted 06 May 2018

For the last two months I have been working on adding some secondary, but still important capabilities to Wall-E2, my wall-following autonomous robot.   As I noted back in April, Wall-E2 still can’t tell which way he is heading, which (among other problems) means he can’t make accurate turns.   In addition, Wall-E2 can’t tell how long (or even  if) he has been turned off, making it impossible to tell how long it has been since he last was charged.

In the intervening months, I have been able to obtain and test individual modules to address the above issues; the Sparkfun MPU9250 9DOF IMU breakout board to obtain heading information, and the combination of an Adafruit MB85RC256V FRAM breakout board and an Adafruit DS3221 RTC breakout board to capture the date/time of any power interruptions.

Since all three of the above breakout boards are I2C-capable, it should be feasible to run all three from a single I2C bus on Wall-E2’s main controller – an Arduino Mega 2560.   Unfortunately, the Sparkfun MPU9250 module isn’t 5V tolerant, so integrating all three isn’t as simple as just daisy-chaining them all together.   Back to Google for some more research, where I eventually uncovered Philips Application Note AN97055 by Herman Schutte of The Netherlands dealing with bidirectional level-shifters for just this problem. Turns out that Philips introduced the I2C bus back in 1980, so they may know a thing or two about the issues ;-).   In any case, this 1997 paper described a 2-MOSFET bidirectional level-shifter that completely addresses the issue, and seemed to be pretty straightforward to implement.   It took me a couple of tries, but I got it working, with the result that I can now run all three modules (RTC, FRAM and IMU) from an Arduino Mega 2560, with the level-shifting MOSFET’s placed between the IMU and the rest of the circuit, as shown in the photo below.

All three sensors operating a the same time, controlled over a single I2C channel.

In the above photo, the modules are (from left to right): Adafruit MB85RC256K FRAM breakout, Adafruit DS3231 RTC breakout, and Sparkfun MPU9250 9DOF IMU breakout.   The two  2N7000 level-shifter MOSFETs can be seen at the top left-hand corner of the Sparkfun IMU breakout board.

I put together a small test program, combining pieces from the software used to test the power-down date/time capture idea, and the software used to test the ability to use the Sparkfun IMU to accurately manage rotations.   This program doesn’t do much at all, but it does demonstrate that all three modules can be controlled at the same time over a single I2C channel, as shown in the following output.

As shown in the above output, all three modules are initialized, and then the program enters a loop where the current time is displayed from the RTC, and the current IMU heading is displayed from the IMU.   Then every 10 times through the loop, a new value is written to the FRAM until the first 20 or so locations have been written. Then the program starts ‘un-writing’ the values until all the written locations have been cleared, at which point the cycle starts all over again.

So, now that I have conclusively demonstrated the ability to add (relative) heading and FRAM-based non-volatile power-cycle date/time recording to Wall-E2, the next trick will be to actually mount the modules on the robot.   This will entail solving yet another set of problems, as it turns out (naturally) that although I have plenty of room on Wall-E2’s second deck, I have run out of available pins on the inter-deck connector.   This could be addressed by putting the modules somewhere on the first deck, but finding that ‘somewhere’ is going to be a real trick.   Time for either a second inter-deck connector, or to replace the current 8-pin model with a larger one.

10 May 2018 Update:

After verifying the proper operation of all three modules one one of my new high-quality ASP protoboards, I transferred everything to a permanent perfboard rendition more suitable for mounting on Wall-E2’s second deck, as shown below

Stay tuned!

Frank

 

 

Another try at heading information for Wall-E2

2 Replies

Posted 24 April 2018

A little over two years ago I started a project to give Wall-E2 ‘a sense of direction‘ by integrating a Mongoose 9DOF IMU board onto the robot chassis.   I worked on the idea for about six months before I finally determined that the magnetometer idea was not going to work in my indoor environment, as there was just too much magnetic interference due to indoor wiring, air handling motors, and the like.

However, it recently occurred to me that although the absolute magnetic heading problem was   intractable, I might be able to use one of the newer single-board IMU products (like the Sparkfun 9250) to generate  relative heading information, which I could use to solve a different problem.   Wall-E2 occasionally needs to perform sharp turns, on the order of 90 º, either as part of what I call an ‘open room step turn’ (like what happens when Wall-E2 exits a hallway into an open room, and needs to turn 90 º in one direction or the other to continue wall-following), or as part of an evasion maneuver or as part of a recovery from a stuck condition.   In my ‘field’ testing to date I have noticed that Wall-E2’s effective turn rate varies considerably depending on the surface condition; very slow on shag carpeting, OK on tightly-woven rugs, and very fast on hard flooring.   This means that my current strategy of timed turns only works OK on the medium surfaces, but sucks the big weenie on the other two types.   So, if I had even relative heading information, I could use it to make sure Wall-E2’s  90 º turns are actually  90 º, as opposed to  45 º or  180 º.

It turns out there are a  lot of single-board IMU solutions out there new, probably due to the wildly popular quad-copter market; they all need attitude-control (AHRS) module of some kind to make them flyable, and those modules need to be small and lightweight.   The one I started playing with first is the Sparkfun MPU-9250 breakout board, with 3-axis accelerometer, gyro, and magnetometer capability in a really small package for an incredibly cheap price.   And, as a bonus, there is a lot of good Arduino/Teensyduino software out there to help us mere mortals run the thing.   In particular, Kris Winer (of Pesky Products fame) has done a lot of work with sensor fusion software for the Arduino and Teensy line, and actively supports both his products and his software.

So, I got a board from Sparkfun and started playing around with it.   The first problem I ran into is that the MPU9250 is a 3.3V board, so I couldn’t run it from an Arduino without either potentially frying the board or having to implement a bidirectional level shifter. So, I grabbed a Teensy 3.2 from my stash and used it instead.   This, in turn, required some judicious sifting through the available software to find the Teensy 3.x compatible versions, but I eventually got that accomplished and started collecting data.

As usual, there were a lot of mis-steps along the way.   The biggest obstacle was figuring out how  to  avoid using the magnetometer data; almost all the software, including the all-important Madgwick quaternion routine for converting raw sensor data into yaw/pitch/roll values assumes the use of magnetometer data to obtain geo-magnetically referenced heading and to minimize/eliminate gyro drift.   In my case, I specifically wanted to decouple heading calculations from magnetometer input, as I already knew the magnetic environment in my house was too variable for reliable measurements.   With some guidance from Kris, I eventually found a 6DOF (3D rate gyro and 3D accelerometer) version of the Madgwick routine.

Once I started getting reliable yaw (heading) measurements from the sensor, I decided to modify my Teensy-based stepper motor rotary table measurement system to rotate the sensor in a uniform way to obtain constant-rate heading scan data.   The basic idea of the rotary table system is to rotate the unit under test X degrees, then stop, take some measurements, and then repeat.   So, I got it all set up, and got the following plot.

This data made no sense at all – for a full 360 º rotation I should have recorded a full 360 º heading change, regardless of the rate of rotation.   Instead, the sensor seemed numb to rotation rates below about 20 rpm (120dps) and even at 60 rpm (360 dps) I wasn’t seeing a full 360 º rotation – what the heck??

After beating on this problem for waaaayyy too long, it finally occurred to me that my test program had a fatal flaw; my measurement system stepped to each desired heading, then stopped, took a heading measurement, and then moved on to the next heading.   The operative word here being  stopped.   While this works great for units under test whose performance varies with rotation, the Sparkfun sensor performance varies with rotation  rate, not the rotation position!   Well, doh – it’s an accelerometer!   So, my carefully assembled test setup wasn’t measuring the sensor’s rotation rate at all – the rotation rate was being reduced to almost zero at each measurement position – oops!

After this “aha!” (or maybe, “doh!”) moment, I realized I needed to modify my rotary test system to make sure that heading data acquisition from the sensor was accomplished ‘on the fly’.   Once I did this, I started getting more reasonable data, like the following plot:

Nice, linear data – great!

At this point I started thinking about how I could integrate this capability into my robot to monitor/manage turn operations, and thought that I could maybe average the first few heading values before the start of a turn to create a stable reference to be used to terminate the turn appropriately.   However, when I tried this trick, with a 10-sample average at the start, I got the following plot

I performed the ‘with’ and ‘without’ initial measurement average experiments several times, and convinced myself that the above phenomenon was real, but I still have no real idea why it occurs.   It has to have something to due with the Madgwick quaternion manipulations, as that is the only place in the entire system where there is any state memory (the 4-element quaternion array itself).   For my purposes, it was sufficient to realize I couldn’t do what I wanted to do, and to “run away!” from this idea.

Next, I modified my stepper motor rotator test system again to simulate the process of setting up a turn direction and angle and terminating the turn when the correct turn angle change had been achieved.   Here’s a short video of the result, where the sensor is turned through +/- 30, 60, 90, and 180 º angles.   The motor is run at a constant rate until the target angle is approached, and then run at 1/5 normal speed to fine-tune turn termination.

So, at this point I confident that I can use the Sparkfun MPU9250 9DOF sensor (used in 6DOF mode) to accurately turn my robot – cool!

With the addition of the Sparkfun accelerometer and the FRAM/RTC combination to his sensor suite, Wall-E2 is set to get significantly smarter; he’ll be able to remember when he was last turned off so he can more accurately report run times and charge times, and he’ll be able to make real 90 º turns instead of having to fake it with timing.   Now if I could only get him to take out the trash! ;-).

Stay tuned,

Frank

 

 

 

Capture Power Loss Data Using Adafruit FRAM Breakout Board

2 Replies

Posted 06 April 2018,

As an enhancement to Wall-E2, my wall-following robot I wanted a way to capture the run time at power-down so I could determine how long it has been since Wall-E2 last charged its battery, even through power cycles.

At first I tried to do this using the Arduino Mega 2560’s  onboard EEPROM, but this proved infeasible, as the time required to write to EEPROM exceeded the time available from the time power was removed to the time the Mega died.   I played around with extra capacitance on the power bus, but this still wasn’t enough to hold the power up long enough to write to EEPROM.   And, even if I finally succeeded, there was still the problem of EEPROM wear-out to deal with.

So, after some more research time with Google, I found this nice Adafruit FRAM breakout board, featuring the Fujitsu M85RC256V 32KB FRAM part

Adafruit provides a simple, but effective I2C interface library and an example sketch, and I was able to use these with a spare Arduino Uno board to verify that I could indeed write to and read from the FRAM.   However, what I really wanted to determine was whether or not the FRAM was fast enough to allow me to write data to it after power was removed from the Arduino but before the processor actually died.

I did some poking around in the Arduinio Uno schematic and determined there was a 47μF capacitor on the output of the +5V voltage regulator, and so I thought I might be able to trigger off power loss at the input to the regulator and accomplish the writes while the capacitor was still holding up the Arduino processor.   I put a 1/3:2/3 voltage divider on the +12V input line and used my trusty Tektronix 2236 scope to monitor it and the +5V regulated output.   With the scope I was able to see that the +5V output stayed up for about 5msec, and stayed above 4V for 8msec, as shown in the following scope photo.

Scope photo of Arduino Uno +5V regulated output, triggered by removal of +12V input power. Time scale 1msec/div.

The next step was to modify Adafruit’s FRAM read/write example program to implement a power-down interrupt routine to test my idea.   Here’s the code (the software is also available here)

The above code takes advantage of a modified version of Adafruit’s I2C FRAM library that facilitates writing and reading of arbitrary data types like int, long, float, etc.   The modifications were cribbed from  Nick Gammon’s wonderful ‘IC2_Anything’ library – thanks Nick!

Here’s the modified ‘Adafruit_FRAM_I2C.h’ file

With this test setup, I was able to repeatedly clear the FRAM memory and see the effect of pulling the power plug.   A typical result is shown below:

Program response when restarted with CLEAR_FRAM_PIN (pin 3) grounded

Program response after the power plug was pulled at about 8.9 sec after startup.

In the first figure above, the  CLEAR_FRAM_PIN (pin 3) was held LOW while the Arduino was restarted, resulting in zeroes being written to the first 100 FRAM locations.   In the second figure, the +12V power plug was pulled after about 9 seconds, then reconnected.   When the Arduino restarted, the power-down ISR had written program timer values from 8976 to 8990 into the first nine 4-byte segments.   This shows that the Arduino continued to operate for about 14msec after the power plug was removed.   This is very good news, as it implies that I should be able to write the current date/time value from a real-time clock (when I get it running, that is) into FRAM whenever there is a power interruption, allowing me to accurately track battery usage history.

The hardware used to perform these tests is shown in the following photos:

Experimental setup moved to new ASP solderless breadboard

Arduino Board Modification:

I ran into a problem when I started testing the power-down interrupt idea; I wanted to keep thE Arduino board connected to my PC via the USB cable, but if I did that, the Arduino would automatically switch over to USB power when I disconnected the +12V power cable. Fortunately, if you have a problem, it’s almost certain that someone else has had and solved the same problem.   In my case I found this post, that explained that T1, the automatic power crossover MOSFET switch had to be removed, as shown in the following photo.   This modification allows the USB cable to continue to supply USBVCC power to U3, the ATMEGA8U2-MU chip, which in turn allows the PC to recognize the Arduino for firmware uploads.

Loader Loading...
EAD Logo Taking too long?

Reload Reload document
| Open Open in new tab

Download

So, now that I have demonstrated the practicality of a power-down interrupt routine to capture time-of-shutdown information (at least on an Arduino Uno), the next step is to integrate this capability with the Adafruit RS3231 Precision RTC breakout board.   Stay tuned!

09 April Update:   Adafruit DS3231 RTC breakout board added:

As I mentioned in my ‘Time and Memory for Wall-E2‘ post, I planned to complement the FRAM capability with the addition of an RTC module so that I could record the time & date of any power interruptions.   As I mentioned in that post, I planned to use the Adafruit DS3231 Breakout Board for this purpose.   After receiving the module, I added it to the system by daisy-chaining the I2C SCL & SDA lines from the FRAM module, and modified the software to incorporate the RTC.   I changed the FRAM_ISR() function to acquire ‘Unixtime’ from the RTC (i.e. the number of seconds since 00:00:00 UTC on January 1, 1970) and write it to the FRAM.

I tested this by uploading this firmware to the Arduino Uno, and then pulling the power plug a few seconds after the program entered the main loop.   Here’s the printout from the run

Program run with Adafruit DS3231 RTC added. Note ‘unixtime’ printout at top, and first 5 FRAM locations at bottom

As can be seen from the above printout, the power-down ISR successfully recorded the current time (in ‘Unixtime’ format) into five successive FRAM memory locations before the Arduino died.   Note also that the recorded time was eleven seconds after the time shown at the top of the printout – about right, as the upper value is the time retrieved using the PC’s __DATE__ and ___TIME___ environment variables at the time the program was compiled and uploaded to the Arduino board.

Here are some photos of the new hardware setup:

Adafruit FRAM module on the left, DS3231 RTC module on the right

Frank

 

Time and Memory for Wall-E2

2 Replies

Posted 01 April 2018 (not an April Fool’s joke)

Now that I have Wall-E2’s charging module and charging station working, I’ve moved on to some secondary, but still important, issues that need addressing.

  • Wall-E2 still can’t tell which way he is heading.   This isn’t necessarily a killer, as his current technique of simply following walls does fairly well.   However, when it comes to a human figuring out where Wall-E2 is or has been, distance to the nearest wall just doesn’t cut it.   A while ago I attempted to solve this problem using an onboard magnetometer, but ultimately concluded a magnetometer-based navigation system is doomed to failure in an indoor environment, due to too many interfering magnetic signals.   I have decided to try this again, but this time using a cheap solid-state gyroscope module from Sparkfun.    I should be able to initialize the gyroscope z-axis to an absolute heading each time Wall-E2 connects to a charging station, as their location(s) and headings are known.   As a bonus, I should be able to use the gyro to generate accurate 90 º turns, instead of the current open-loop timing method.
  • Wall-E2 remembers how long it has been since its last recharge, but only if the main power hasn’t been interrupted.   If I turn him off for any reason, that information goes away.   I dicked around with writing the current value of millis() to EEPROM on power-down, but it turns out that EEPROM writes are  way too slow for that.   After Googling around for a bit, I found a nice little FRAM (Ferro-magnetic Random Access Memory) module from Adafruit, and I believe I will be able to implement a power-down memory save feature using it.
  • Once I have a fast non-volatile FRAM solution, it occurs to me that I may want to write telemetry information to it, so it isn’t lost when Wall-E2 is out of range of the current Wixel link to my PC.   Maybe even set the FRAM (or at least part of it) up as a rate buffer between Wall-E2 and the Wixel.   The idea would be that telemetry data always goes to the FRAM at some rate A, and is then read from the FRAM to my PC via the Wixel link at rate B, where B > A.   When the link isn’t available, the telemetry data continues to be written into the FRAM, and is read back out again when the link becomes available.   As long as the link isn’t interrupted for too long, I won’t lose any telemetry data.   As part of this implementation, I would like to time-stamp the data with real date-time information, which requires a battery-backed RTC (real-time clock).   As it happens, Adafruit has one of these too, so I may be able to implement it quickly and easily.

I chose the I2C versions of all these modules, as I already have I2C implemented for acquiring steering cues from my IR Homing Module.   In theory, at least, adding three more I2C slave devices to an already existing setup should be trivial.

Stay tuned!

Frank

 

Charging Station Voltage Change From +5 to +12V

Leave a reply

Posted 22 March 2018

With the replacement of my Power Boost 1000C – based charger module with the TP5100, I needed to change the charging station supply voltage from +5V to +12V.   Unfortunately, the modulated IR beam signal is generated by a Teensy 3.2 module, which requires +5V (it’s actually a 3.3V module, but can accept power of up to +5V), so now I needed both +5 and +12V on the charging station.   The answer was to add a simple 3-pin regulator, as shown in the schematic below

Updated charging station schematic showing addition of a 3-pin 12-to-5V regulator

The original Teensy 3.2 side

The original 5V charging station layout, rear view

The new +12 to +5V regulator side

Updated charging station assembly, rear view

 

A matter of voltage

Leave a reply

Posted 20 March 2018

I think it is important that Wall-E2 have an accurate measurement of battery voltage, so that he knows when he should be looking for his next charging fix, and more importantly, so he can stop and yell for help if the battery voltage gets dangerously low.   In addition, I would like to monitor the battery voltage during charge, so Wall-E2 can report & display charging progress to any interested humans (like me). ;-).

From what I’ve read, it appears a LiPo cell can go down to about 3V without damage, or 6V for my 2-cell stack.   So, my operating voltage range is from full charge (approx 8.4V) to empty (6.0V).   My first cut at battery voltage monitoring was a simple 1/3 – 2/3 resistive voltage divider tied to an analog input; simply measure the voltage, multiply by 3, and voila – battery voltage!

Only it didn’t work that way; once the battery voltage dropped below about 7V, the drop across the Arduino Mega’s voltage regulator wasn’t sufficient to maintain regulated 5V, so the Mega’s bus voltage began to drop.   At Vbatt = 6V, the Mega was still running OK, but the bus voltage was down to 4V, and the A/D reference was no longer what it should be – rats!

In addition, once I started looking at this issue, I realized I was throwing away most of the A/D dynamic range with the divider idea.   with a 5V A/D reference and a 1/3 divider, the A/D input voltage only varies between 2.0 and 2.8V for an input range between 6 and 8.4V.   In other words, I’m only using 0.8V of the available 5V range or about 16%.

So, I thought that maybe I should implement a level shifter, so the sensed voltage varies from 0 to 2.4 as the battery voltage varies from 6 to 8.4 – and then use the Mega’s internal 2.56V reference for the A/D operation.   This would mean an immediate increase in dynamic range usage from 16% to almost 94%, and would increase resolution from about 15mV/count to about 2.5mv/count.   To do the level shifting, I’ll need a 6V zener, such as the  1N5233B, available from Mouser for a few pennies each.

One last voltage issue to be addressed is the problem with the Mega’s onboard regulator dropping out for battery voltages between 7 and 6V – this is almost half of the available voltage range.   Eventually I decided to address this problem by replacing (or rather, bypassing) the onboard regulator with a low dropout (LDO) regulator such as the  LF50CV-DG  , available from Mouser for less than $1 each.   The  LF50CV-DG can maintain 5V output down to well below my 6V battery voltage cutoff limit, so it is a good match.

23 March 2018 Update:

I just received the LF50CV-DG regulator and  1N5233B parts from Mouser, so I’m in the process of installing them onto Wall-E2.   The regulator will take the place of the MOSFET low-drop diode I installed on the Pololu Wixel Shield some time ago as part of my old PB1000C-based charging subsystem, and is now no longer needed.   The following photos show the installation:

Wixel shield showing MOSFET diode to be replaced by LDO 5V regulator

LF50CV-DG LDO 5V regulator and 1N5233B 6V Zener diode installed on Wixel shield

Rear of Wixel shield showing regulator output connection to +5V bus

25 March Update:

While testing the above arrangement, I managed to somehow kill my Mega 2560 SBC (I think my old power supply did it in, but I’m not sure).   So, in the process of recovering from this mess, I also decided to replace my old Wixel shield for the latest version (v1.1) with updated level-shifting circuits and carry-throughs for the added pins on the UNO R3, Mega, and cousins.   The new layout is shown below

Updated Wixel shield board with LDO 5V regulator and level-shifter circuit installed

Once I got everything back together, I started over with testing the LDO 5V regulator and level shifter performance, and ran into another problem.   The original idea was to use the 1N5233B 6V zener to level shift 6-8.4V to 0-2.4V so the range would fit into the range obtainable using the Mega’s internal 2.56V ADC reference.   This worked  almost perfectly, but the combination of a slightly lower Vz (5.84 vs 6.00V) and a slightly lower Vref (2.42 vs 2.56V) caused the ADC to hit full scale (1023 counts) at about 8.26V (2.44Vref + 5.84Vz = 8.26V).    Most unfortunate, as I really needed to accurately measure Vbatt to at least 8.4V, nominal end-of-charge voltage for a 2-cell LiPo stack.

So, I needed to expand the measurable voltage range at least a little bit on the top end.   With the installation of the LF50CV LDO 5V regulator, I could now do that by reverting to the internal 5V reference, as the LDO easily maintains 5V output all the way down to 6V, the cutoff voltage for my battery stack.   But, this wastes half the available ADC range, as the ADC input voltage for Vbatt = 8.4 is only 8.4-5.84 = 2.56V.   So, after some more Googling through Arduino-space, I realized I could tie the Mega’s AREF pin to the Mega’s 3.3V output line and use ‘analogReference(EXTERNAL)’ to obtain an ADC range from 0-3.3V, corresponding to a Vbatt range of 0 to (5.84+3.3)= 9.14V – perfect!

After making this change I ran some measurements to verify the input range and accuracy, as displayed in the following Excel plot

Measured vs Calculated Vbatt, with raw ADC values

As can be seen in the above plot, the measured and calculated voltage plots are almost perfectly overlaid, and well within the accuracy requirements for effective battery management.

Summary:

As usual, what started out as a simple plan (in this case, to accurately measure the battery voltage) rapidly metastasized into a full-blown hardware and software project, complete with howls of anguish and gnashing of teeth.   The first idea was to use a simple 1/3 resistive voltage divider input to a ADC port referenced to 5V. This worked OK, but failed at battery voltages below 7V because the Mega’s onboard voltage regulator requires an approximately 2V input-output offset.   Since I needed to measure Vbatt down to 6V, this was never going to work.   In addition, the available measurement accuracy sucked because the 2.5V range of interest was being compressed into 2.5/3 = 0.833V, and with a 5V reference I was using less than 20% of the available ADC counts. The next idea was to replace the onboard regulator with the LF50CV LDO regulator, and use a 6V zener to level shift the range of interest to under 2.56V so that the Mega’s internal 2.56V reference could be used.   This  almost worked, but I ran out of ADC counts before I ran out of battery voltage – oops.   The third (and last, I hope) idea was to change the ADC reference from internal 2.56V to external 3.3V using the AREF pin tied to the Mega’s 3.3V regulated output.   This allowed the top voltage to go to a little over 9V, just about perfect for this application.

 

 

Stay tuned,

Frank

 

 

To a man with a hammer, …

Leave a reply

Posted 17 March 2018,

To paraphrase the saying, “to a man with a hammer, every problem looks like a nail”, “to a man with a 3D printer, every problem looks like a 3D printing opportunity”.   And that’s pretty much what happened when I ran across the problem of adapting some  80mm wheels to my Wall E-2 robot, which came originally with 65mm versions.   The extra 15mm diameter/7.5mm radius doesn’t sound like much, but it makes a  huge difference when navigating over carpet or other small obstacles (like my wife’s slippers).

After a  lot of work, I finally was able to print four reasonable quality adaptors, and thought I was home free.   Unfortunately, I soon learned that despite my best efforts, the printed adaptors were no match for physics; the wheel eventually worked its way off the motor shaft, just as before – it just took a little longer ;-).

After the usual number of curses, imprecations, and woe-is-me’s, I finally decided to use whatever was left of my engineering brain to actually look at the physics of the situation.   When I did so, I realized that my adaptor idea was never going to work.   While the adaptor did indeed (after the aforementioned ‘lot of work’) provide for a better fit between the 80mm wheel receptacle and the motor shaft, it also moved the wheel another 9mm or so away from the robot chassis, which put the wheel center of pressure (CP) well outside the adaptor-to-motor shaft parting plane.   This meant that the wheel would always be trying to pry the the adaptor off the shaft, and it didn’t take all that long for it to succeed :-(.   The following photo illustrates the problem

80mm wheel with 3D-printed adaptor on the left, same wheel directly attached to motor shaft on the right

So, contemplating this problem while drifting off to sleep I was struck by a solution; I could use a small roll pin inserted through the wheel and motor shafts to literally pin them together.   The geometrical physics would still cause the wheel to flex the shaft, but the forces wouldn’t be able to overcome the strength of the metal roll pin.   Because I knew I would forget this insight if I left it until morning, I staggered out of bed and jumped onto the McMaster-Carr site (they have  everything!) to look for an appropriately sized roll pin.   I found a 1 x 6mm roll pin that would be perfect for the job, and if I ordered them now they would probably already be on my doorstep when I woke up in the morning.

McMaster-Carr metric roll pins

However, while I was doing the necessary measurements on the motor shaft, I noticed the motor shaft had a axial hole in it, and so did the wheel; hmm, maybe I could simply run the roll pin through the axial hole, instead of cross-wise?   Then I thought – wait that hole looks to be slightly smaller than 3mm – maybe I could simply drill/tap it for 3mm and use a 3mm screw (of which I had plenty in different lengths) instead of a roll pin?

So, in just a few minutes I had drilled & tapped the axial hole in the motor shaft of one of my spare motors, drilled out the wheel hole for 3mm clearance, and firmly screwed the wheel to the shaft (the right-hand wheel in the first photo above) – cool!

Now all I have to do is modify all four wheel shafts for 3mm clearance, and all four motor shafts to accept a 3mm screw – piece of cake!

As can be seen in the above photos, the 80mm wheels are now much closer to the chassis.   The wheel guards are now much too wide, but I may keep them that way for the moment, as I have already adjusted the charging station lead-in rails to accommodate the (now unnecessary) greater wheelbase – oh well 😉

So, the moral of this little story is:   Just because you have a 3-D printer doesn’t mean the solution to every problem is a new 3-D printed piece; and maybe to keep one’s eyes/brain open for even better solutions as they might come along when least expected!

Stay tuned,

Frank

 

 

 

 

 

 

 

New TP5100-based Battery Pack for Wall-E2

1 Reply

Posted 13 March 2018

In a recent post, I described my study of the widely available and dirt-cheap TP5100 1/2-cell LiPo battery charger as a possible replacement for my current Adafruit PB1000C-based battery charger.   Based on the results of this study, it was clear the TP5100-based system was superior in all respects to my home-brew system:

  • Twice the charge current (2A vs 1A) means significantly shortened charge times
  • Much smaller and simpler
  • Charger current path independent of load path – much lower IR drop
  • Battery always connected to the system, so no requirement for ultra-low-drop MOSFET diode
  • Much simpler software – no requirement to monitor status of two separate chargers
  • No electromechanical relay to screw up.

I constructed a small charger module using some perfboard and a couple of 2-place screw terminals, as shown below (with the previous module shown for size comparison).

New TP5100-based charger module, with previous Adafruit PB1000C-based module below for size comparison. The orange box contains 4 Panasonic 18650 cells.   Note the separate charge & load circuits

The following figures show the old and new schematics:

Old battery pack schematic

New battery pack schematic

Now that the load current doesn’t have to go through the charging module, I was able to replace all main battery wiring with #20 wire for lower IR drops, as shown below

Power wiring replaced with #20 wiring, and 2-pin Deans connectors

#20 wiring to main battery buss. Note in-line safety disconnect

 

The change to the new battery pack also considerably simplified the system hardware and software.   The changes to the system schematic are shown below:

Old system schematic. Note the ultra-low-drop MOSFET diode required to keep Arduino Mega alive during charge. and the number of pins required for charge monitoring.

New system schematic. No requirement for diode, as full battery voltage is available at all times. Also, only two pins are required for charge monitoring

The operating system software has also been simplified.   Now, instead of monitoring both cell voltages and four different status lines, only two lines have to be monitored.   Also, there is now no requirement to correctly sequence the ‘Charger Connect’ and ‘Coil Enable signals in order to accomplish correct charging station connect-disconnect behavior.   Now the system simply shuts off the motors when the robot connects to the station, and turns them back on again to disconnect.   As an added benefit, the six charge status LEDs have been repurposed to show a crude approximation (based on battery voltage only for the moment) of charge status.

All these changes have caused one minor hiccup in the implementation of the charging station; the new charging voltage is +12V vs +5V as before.   As you may recall, the charging station implements a square-wave modulated IR signal, and this signal is produced by a Teensy 3.2 and some associated circuitry, all of which expect +5V.   This will require either a dual-output supply, or the addition of an on-board 12-to-5V regulator. This is still up in the air, but I suspect it will land on a simple 3-pin regulator.

So far, all the hardware changes (except for the charging station changes) have been accomplished, but the software changes have yet to be implemented and tested. Stay tuned!

Frank