Tag Archives: robots

Charging Station System Integration – Part IV

Posted xx April 2017

While doing the hallway testing that led to the discovery of the overhead IR ‘noise’ problem and the design of a ‘sunshade’ to suppress that noise and implementation of the flashlight reflector idea for the IR LED, I discovered several other problems with the operating system, as follows:

  1. Once the software detects an IR signal, it switches in to IR homing mode, but the only way back out again is to either execute the avoidance routine if it isn’t in need of a charge, or by connecting to the charger and then disconnecting once the battery is fully charged.  There’s no provision for error cases, like getting stuck on on of the lead-in rails.
  2. The charging station disconnect maneuver needs work – it doesn’t back far enough away, and doesn’t turn far enough to actually get away from the charging station.
  3. The routine that monitors the charging state needs work. On several occasions it detected ‘end of charge’ when one of the chargers momentarily switched from ‘charging’ to the ‘finished’ state and back to ‘charging’.  The software should not declare ‘end of charge’ until both chargers’ status is ‘finished’, and the software should employ integration to handle momentary state changes.

Item 1 – Exit provisions for IR homing code

This item actually turned into a full-blown rewrite of Wall-E2’s operating system software structure.  As I looked at the code to determine the best way to implement the required error case detection/responses, it became apparent that the problem was ‘baked-in’ to the software system design, and would have to be addressed at that level.  So, I went ‘back to the drawing board’ (in this case to Microsoft Visio) and reworked the system design to allow Wall-E2 to detect and respond appropriately to error conditions in any mode, not just the normal wall-following one.  The revised structure charts are shown in the following PDF document:

In the revised structure, the system always returns to the ‘Determine Op Mode’ block after each pass through the system, without getting stuck anywhere.  This means that the ‘GetOpMode()’ routine has the opportunity on each pass through loop() to detect error situations (like the ‘stuck’ condition) and respond by switching to the appropriate branch of the structure tree.

Item 2 – Charging Station Disconnect Maneuver

This one was just a matter of tweaking the ‘degrees’ parameter to the ‘RotateCWDeg((bool bRotateCW, int degrees_to_rotate)’ function.  I started out with degrees_to_rotate = 90, but then tweaked it to 120 for better disconnect performance.

Item 3 – Charge State Monitoring

In the current operating system, a function called ‘MonitorChargeUntilDone()’ is called when the robot detects that it is connected to the charging plug.  This function goes into an infinite loop, waiting for the charging status to change from ‘charging’ to ‘finished’.  While in this loop, the charger 1 and charger 2 status lines are read in about once per second, until either both ‘finished’ outputs are TRUE, or the  BATT_CHG_TIMEOUT_SEC backup timer elapses.  This logic seems OK, but I have observed several inappropriate disconnect instances where only one of the two ‘finished’ outputs were TRUE.   I suspect that there is a period of time where these two status lines oscillate from FALSE (not yet finished) to TRUE (finished) and back again, before finally settling down on ‘finished’.

In my new strategy of eliminating all inner loops, the  ‘MonitorChargeUntilDone()’ function will no longer be used.  Instead, the ‘Charge Mode’ block of the new software structure chart (shown below) will be implemented.

Updated Charge Mode Structure Chart Detail

This block will be executed on each pass through the loop() function, as long as the ‘Determine Op Mode’ block returns with the current mode set to ‘MODE_CHARGING’.  When/If the ‘Both Cells Charged’ or the ‘Charger Timeout’ reached ‘if’ statements return TRUE, then the ‘Disconnect’ function will be triggered, which will cause the robot to immediately disconnect and back away from the charging station.  This in turn will cause the ‘Determine Op Mode’ block to output a different mode value (assumed to be, but not necessarily ‘MODE_WALL_FOLLOWING’), and the appropriate portion of the overall structure diagram will be executed.

I’m away from my robot at the moment, at a bridge tournament in Gatlinburg, Tennessee, so I can’t immediately implement and test the above changes.  However, I will be back home next week and hope to have everything running by the end of May. If everything works out, I may have a fully functioning charge station operational by then, and a ‘more-or-less’ fully autonomous Wall-E2 robot.  It will be interesting to see what kind of trouble Wall-E2 can get into with the much longer run times that should be possible with autonomous charging capability.

Stay tuned!! 😉







Charging Station System Integration – Part III

Posted 15 April 2017

In my previous post on this subject, I described some IR homing tests with and without the overhead incandescent lights, and the development of a ‘sunshade’ to block out enough of the IR energy from the overhead lamps to allow Wall-E2 to successfully home in on the IR beam from the charging station.  At the conclusion of that post, I had made a couple of successful runs using a temporary cardboard sunshade, and thought that a permanent sunshade would be all that I needed.

However, after installing the sunshade (shown below), I discovered that the homing performance in the presence of overhead IR lamps was marginal when the robot’s offset distance from the wall was more than about 50 cm.

Sunshade, oblique view

Sunshade, side view

Sunshade, front view

Apparently the IR interference was causing the robot to not respond to the IR beam until too close to miss the outer lead-in rail.  This issue was explored in an earlier post, but I have repeated the relevant drawings here as well.


Tilted gate option. The tilt decreases the minimum required IR beam capture distance from about 1.7m to about 1.0m

Capture parameters for the robot approaching a charging station

When the robot is ‘cruising’ at more than about 50 cm from the tracked wall,  the IR interference from the overhead lamps prevents the robot from acquiring the charging station IR beam until too late to avoid the outer lead-in rail, even in the 13º tilted rail arrangement in the first drawing above.


So, what to do?  I am already running the IR LED at close to the upper limit of the normal operating current, so I can’t significantly increase the IR beam intensity – at least not directly.  I can’t really increase the size of the ‘sunshade’ dramatically without also significantly affecting the IR beam detection performance.  What I really needed was a way of increasing the IR beam intensity without increasing the LED current.  As it turns out, I spent over a decade as a research scientist at The Ohio State University ElectroScience Lab, where I helped design reflector antenna systems for spacecraft.  Spacecraft are power and weight limited, so anything that can be done to improve link margins without increasing weight and/or power is a good thing, and it turns out you can do just that by using well-designed reflector dishes to focus the microwave communications energy much like a flashlight. You get more power where you want it, but you don’t have to pay for it with more power input; the only ‘cost’ is the insignificant added weight of the reflector structure itself – almost free!  In any case, I needed something similar for my design, and I happened to have a small flashlight reflector hanging around from a previous project – maybe I could use that to focus and narrow the IR beam along the charging station centerline.

LED flashlight reflector

So, using my trusty PowerSpec PRO 3D printer and TinkerCad, I whipped up an experimental holder for the above reflector, as shown below

Experimental 3D-printed flashlight reflector holder

Reflector mounted on experimental holder

IR LED mounted on reflector

A couple of quick bench-top tests convinced me I was on the right track; At 1m separation between the IR LED/reflector combination and the robot, I was able to drive the robot’s phototransistors into saturation (i.e. an analog input reading of about 20 out of 1024 max), where before I was lucky to get it down to 100 or so.  However, this only happened when I got the LED positioned at the reflector focal point, which was tricky to do by hand, but not too bad for a first try!

Next, I tried incorporating the reflector idea into the current charging station IR LED/charging probe fixture, as shown in the following photo. This was much closer to what I wanted, but it still was too difficult to get the IR LED positioned correctly, and this was made even more difficult by the fact that I literally could not see what I was doing – it’s IR after all!

New reflector and old charging station fixture designs

However, the reflector focusing performance should be (mostly) the same for IR and visible wavelengths, so I should be able to use a visible-wavelength LED for initial testing, at least.  So, I set up a small white screen 15-20 cm away from the reflector, and used a regular visible LED to investigate focus point position effects.  As the following photos show, the reflector makes quite a difference in energy density.

Green visible LED, hand-positioned near the focal point

Pattern without the reflector

Next, I used my Canon PowerShot SX260HS digital camera as an IR visualizer so I could see the IR beam pattern. As shown below, the reflector does an excellent job of focusing the available IR energy into a tight beam

IR beam visualized using my Canon PowerShot SX260HS digital camera

IR LED, without reflector

Next, I made another version of the reflector holder, but this time with a way of mounting the LED more firmly at (or as near as I could eyeball) the reflector focal point.

Reflector holder modified for more accurate LED mounting

With this modification, I was able to get pretty good focusing without having to fiddle with the LED location, so I set up some range tests on the floor of my lab.  With LED overhead lighting (not incandescent), I was able to get excellent homing performance all the way out to 2m, as shown in the following photos and plots

Range testing the IR reflector in the lab. Distance 2m

IR Detector response vs orientation at 2m from reflector, in the lab

IR reflector beam pattern at 2m, visualized using digital CCD camera

After this, I decided to try my luck again out in our entry hallway, with the dreaded IR interference from the overhead lighting and/or sunlight.   I installed the lead-in rails in the ’tilted’ arrangement, and then performed a response vs orientation test with the robot situated about 2.5m from the IR LED/reflector assembly, in natural daylight illumination with the overhead incandescents OFF.  This produced the curves shown in the plot below.

Robot response vs orientation test setup, 2.5 m from tilted lead-in rails & LED/reflector assembly

IR detector response vs orientation test, 2.5 m from IR LED/Reflector assembly

In the above Excel plot, the individual detector response minimums can be clearly seen, with minimum values in the 200-300 range, and off-axis responses in the 800-1000 range.  This should be more than enough for successful IR homing.

After seeing these positive responses, I ran some homing tests starting from this same general position.  In each run, the robot started off tracking the right-hand wall at about 50 cm offset.  One run was in daylight with the overhead lights OFF, and another was in daylight with the overhead lights ON.  As can be seen in the videos below.

Both of the above test runs were successful.  The robot started homing on the IR beam almost immediately, and was successfully captured by the lead-in rails.

So, it is clear the reflector idea is a winner – it allows the robot to detect and home in on the IR beam from far enough away to not miss the capture aperture, even in the presence of IR interference from daylight and/or overhead incandescent lighting.

Next step – reprint the IR LED reflector holder with the charging probe holder included (I managed to leave it out of the model the last time), and verify that the robot will indeed connect and start charging.















Charging Station System Integration – Part II

Posted 07 April 2017

After getting the wall-following mode re-implemented in the ‘new-improved’ Wall-E2 operating system, I re-enabled the IR homing part of the code, only to discover that Wall-E2 thought it could see the IR homing beam everywhere, in the atrium, even though the IR homing LED wasn’t even in the room (and was turned OFF, besides)!  This didn’t make a whole lot of sense, until I realized Wall-E2’s sensors were ‘seeing’ IR from the overhead floodlamps.  I confirmed this by having my ‘lovely assistant’ wife turn the atrium lights on & off and monitoring the detector outputs.  Same thing for the entry hallway (see data below)

I thought I had solved this problem way back when I first started working with the IR detection/homing idea back in October of last  year.  In that initial post where I investigated the OSEPP ‘IR Light Follower’, I found I had to turn OFF the LED track lights in my lab in order to avoid swamping the detector array.  Over the next month or so this project evolved into a custom designed array of Oshram SFH309FA-4 phototransistors (see http://fpaynter.com/2016/11/ir-light-follower-wall-e2-part-vi/), and as part of this I discovered that the Oshram devices weren’t at all sensitive to the LED track lighting in my lab.  From this I concluded (erroneously as it now turns out!) that I didn’t need a ‘sunshade’ at all, which allowed for a much simpler installation on the robot (see http://fpaynter.com/2016/11/ir-light-follower-wall-e2-part-vii/).  Finally, when this module was transferred from the 3-wheel test bed to the Wall-E2 and combined with the charging status display panel, we arrived at the ‘final’ arrangement shown in the following photo

IR detector module (red) shown beneath charging status display panel (blue)

This worked great for all my in-lab IR homing tests with my all-LED overhead track lighting, but as soon as I started testing out in the rest of the house, the overhead incandescent and halogen lamps swamped out the detectors. So, it was back to the drawing board – again :-(.

The first thing I did was to confirm that the IR detectors were indeed getting swamped by the overhead lighting, and that it was possible to prevent this by some sort of shielding.  I started with a wrap-around cardboard shield that completely covered the IR detector module, as shown below, and placed the robot on the floor of the entry hallway in a normal ‘wall-following’ position

Sunshade V0. Not very practical, but does set the baseline for the rest of the tests

Test position for 07 April 2017 sunshade tests


With this setup, Wall-E2 was pretty much deaf to the overhead lamps, showing no reaction to cycling the lights.  Of course, this configuration would also completely prevent it from detecting the charging station IR beam, but….

Next I modified the above V0 cover to allow a bit more visibility, as shown below:

Sunshade V1 oblique view

Sunshade V1 front view

This version is still a bit too restrictive for normal IR beam detection/homing, but was worth a shot for testing purposes.  With this setup, the overhead lighting is noticeable, as shown below.

Sunshade V1 at sunshade test position. Lights ON four times for 5, 5, 5 and 10 sec

As can be seen from the plot, the V1 sunshade responds to the overhead lamp IR with an average A/D reading about 700 out of 1024.

Next, I modified the sunshade again so that it would just allow the IR detector module to ‘see’ straight ahead, on the theory that that would be the minimum requirement for successful IR beam detection/homing.  With this setup, the overhead lamp response was stronger, but still not completely overbearing; the IR detector response to the overhead lights averages A/D values of about 600 out of 1024.

Sunshade V2 oblique view

Sunshade V2 front view.  Note IR detectors visible from directly in front

IR detector response to overhead lamps. ON three times for 5 sec each

When I ran a homing test with the V2 sunshade in my lab (with LED overheads, not incandescent), the robot homed successfully from about 1 m away, with the following IR detector/homing performance

In-lab (LED overhead lighting) charging station homing performance with V2 sunshade

In the above homing test, the IR detector values started out at approximately 900, 200, 450 and 750, respectively.  This means I could set the IR beam detection threshold at, say, 400 and still have a 200-count noise margin in both directions (200 down from the overhead IR flooding value, and 200 up from the typical 1-meter IR beam intensity).  From the movie it is obvious that the minimum IR reading is switching back and forth between at least two detectors, so I think it is safe to say that IR homing would occur even in the presence of a 600 unit noise level, as the 200 or lower reading switched between detectors.

Next, I moved the charging station into the entry hall so I could test IR homing performance with the overhead lights on and off.  My prediction was that Wall-E2 should be able to home successfully in both cases.  For the test, the charging station lead-in rails were oriented in the preferred ’tilted’ orientation, as that should give the best homing performance, as shown in the photos below:

Hallway IR homing test setup

Robot shown in captured position. Note lead-in rail ’tilt’ relative to the wall

I made three runs; Lights ON, lights OFF, and Lights ON, as shown in the three video clips below:


As can be seen in the videos, Wall-E2 successfully homed to the charging station with the overhead lights OFF, but not with them ON – bummer!

So, further testing will be required to determine the particulars of the two failed runs, and what – if anything – can be done about it.

After moving my laptop out into the hallway so I could capture telemetry from the robot while also filming the runs, and checking everything out, I made two successful IR homing runs – one with the overhead lights ON, and another one with them OFF.  I captured telemetry from both runs, and was clearly able to distinguish between the lights ON and OFF scenarios.  The videos and the telemetry plots are shown below:

08 April 2017 Hallway Test2 with V2 Sunshade – Lights OFF

08 April 2017 Hallway Test2 with V2 Sunshade – Lights ON

From the above plots, the lights ON & OFF conditions are readily recognizable.  In the ‘OFF’ condition, the ‘background noise’ is at about 600-700, and the IR beam is at 100-200.  In the ‘ON’ case, the noise level is higher (lower count), at about 150-250, but the IR beam is lower too – around 50-150.  I guess this makes some sort of sense, as the IR energy from the charging station beam is a separate, additive source relative to the overhead lighting.  Also, both plots show good motor response curves – the left & right motor speeds are obviously being adjusted rapidly in response to IR detector changes.

So, at this point I’m pretty convinced that the V2 sunshade is working, so I plan to print up a permanent version that will (hopefully) simply slide on to the front of the existing charge status display panel.

Stay tuned!







Charging Station Design, Part XIII – More PID Tuning

Posted 28 March 2017

After my cleanup-and-label campaign documented in my last post, I was ready to get back to PID tuning for homing in on the charging station.  When my grandson was here, he pretty much took over my primary work area, so I was forced to move my bench-top testing range to another part of my bench.  This was not quite as convenient for reprogramming the bot, but it did give me a bit more distance between the initial bot position and the IR LED in the charging station, as shown in the following photo

Wall-E2’s new PID test range

I started out by going back to the simplest possible PID setup – namely (p,i,d) = (1,0,0) and ran a series of range tests, as shown in the following video.

As is evident in the video, Wall-E2 has no difficulty homing into the charging station when initially placed near the edge of the bench, but won’t home properly from the other side.  After thinking about this for a bit, I came to the conclusion that the reason for this is that the center of the charging station is physically located near the edge of the bench, so when the bot starts at that edge, it is actually close to the centerline of the charging station, and therefore is almost perfectly lined up at the start. When starting from the other side however, the initial position is not lined up with the charging station centerline and therefore has to make more of a correction to get lined up.  From this I hypothesized that the PID setting of (1,0,0) doesn’t provide enough of a wheel-speed correction to make the required turn.

So, next I tried a PID of (2,0,0), and this worked much better, as shown in the following video

As can be seen from the first run above, the robot is doing a much better job of homing, but unfortunately ran into the left side rail instead of being captured.  This turns out not to be a PID tuning issue, but rather a problem with the IR beacon pattern relative to the lead-in rail arrangement.  The line from the robot’s starting position to the IR LED unfortunately intersected the outside of left lead-in rail instead of the inside.

As an experiment to confirm the IR beam pattern hypothesis, I printed up an auxiliary part to restrict (not collimate, as that implies shaping) the beam to a narrower pattern, as shown in the following photos ( taken with a digital camera with a wavelength range that covers the IR wavelength being used)

This experiment ‘worked’ in the sense that it showed that the IR beam was no longer visible outside the lead-in rail aperture, but it also made it so narrow that the robot had to be right on the centerline to sense the IR beam at all.  Although this solves the problem of hitting the rail, it would make it very difficult for the robot to ever find the charging station in the first place when approaching at the typical wall-following standoff distance.

So, although I plan to do a bit more fine-tuning of the PID parameters, it appears that the basic homing problem is solved, but the challenge now is getting the robot into a position where it can home in on the IR beam without running into a side rail.  The current wall-following algorithm doesn’t have a set stand-off distance, so the robot may be ‘cruising’ at anywhere from 10-70 cm from the wall being tracked.  Assuming that one lead-in rail is against the wall, the IR led is located about 20 cm out, and the front end of the outside lead-in rail is about 35 cm out.  When the robot is just captured by the outside rail, its centerline is about 16 cm out.  The angle from the IR LED to the center of the robot at this point is about 11-12º.  So, assuming the robot is wall-following and at some point intersects the IR beam and starts homing, the angle from the robot to the IR LED has to be less than 11-12º or the robot will not be captured by the lead-in rails.  The situation is shown graphically in the following diagram.

Capture parameters for the robot approaching a charging station

As shown above, if the robot is ‘cruising’ at 45 cm from the wall, then it has to start homing from no less than 1.7 m or so from the charging station in order to get captured by the lead-in rails.  This is a large, but impossible distance.  The robot can currently home from about 1 m out, so getting out to 1.7 m might be as easy as increasing the IR LED current;  it is currently running at about 30 mA, and it is rated for 100.

Another possibility is to angle the capture gate out slightly with respect to the wall. There’s no real reason the charging station rails need to be parallel to the wall – it’s just my neat-freak mentality that makes me do things that way.  If I angle it such that the inside lead-in rail touches the wall at both its forward and trailing ends, that will angle the beam out at about 13º, and move the minimum capture distance in to about 1.0 m, as shown in the following diagram.  1.0 m is just about where the robot is capturing now – yay!!

Tilted gate option. The tilt decreases the minimum required IR beam capture distance from about 1.7m to about 1.0m

So, it appears that tilting the capture gate is the way to go; this doesn’t cost anything but a slight ding in my ‘neat-freak’ index, and should eliminate or greatly reduce problems with charging station capture failures.

Stay tuned,



Charging Station Design, Part XII – A Pause to Clean Up

Posted 22 March 2017

This last weekend was devoted to a whirlwind visit by the St. Louis family, which includes my 13-year old, growing-like-a-weed, 3D printing enthusiast grandson.  So, I didn’t get a whole lot of time to work on Wall-E2’s problems, as Danny basically took over my entire lab ;-). So, now that the horde (can one 13 year-old kid constitute a ‘horde’?) has departed, I can get back to some sort of normalcy and make some progress.

At the end of my last post on this subject, I had concluded that I needed to go back and verify the details of the IR homing hardware and software, as the results I was getting didn’t make sense.  So, I set up some experiments where I could carefully watch the raw output from all 4 IR detectors, and the changes from physically blocking one IR LED at a time.  This experiment convinced me that something was definitely wrong with the hardware; at least one detector appeared to be dead, and it also looked like blocking one detector affected the outputs of more than one – strange!

So, back to the hardware; After dismounting the combined charge status display panel/IR detector module and separating the two, and physically inspecting the IR detector module I  found a bad solder joint (what – a bad solder joint!?  I never make bad solder joints! – must have been someone else!) on one of the detector connections to the interface  header.

After repairing the bad solder joint, I carefully worked my way through the cabling maze on Wall-E2 to the microcontroller end of the IR detector cable, to verify proper connection on that end.  The connections looked good, so I did some more testing, only to find that one of the IR detector outputs appeared to be dead – it’s analog reading stayed around 4-500 no matter what I did.  Some more physical inspection revealed the problem – my 4-pin IR detector cable was connected to A2-A6 on the Mega board, but I was reading A1-A5, so the A1 input was essentially ‘open-circuit’ – oops!

After fixing this booboo, things started to perk up and act a *lot* more normally! ;-).  However, instead of immediately going back to testing mode, I decided that I needed to get serious about labeling and indexing cables (I use red fingernail polish to index one end of each connector to the corresponding microcontroller pin) and connectors on Wall-E2, so I would have less trouble in the future with the large number of ribbon cables and loose wires now festooning the robot.   Fortunately I have my wonderful Brother P-touch label maker to help me with this task. As an aside, if you are a ‘maker’ hobbyist like myself, a label maker is an absolute godsend, and I can’t recommend the Brother P-touch highly enough.

After my labeling and cleanup campaign, Wall-E2 is  a lot more self-documenting, as shown in the following photos

Charging Station Design, Part XI – PID Tuning

Posted 14 March 2017

As I was doing the IR homing tests described in my last post, I noted that Wall-E2 wasn’t all that great at homing; in particular it missed the opening in the lead-in rails on several occasions, instead hanging up on one side or another.  This was a bit mystifying to me, as I thought I had the homing code working very well with my old 3-wheel robot (see ‘IR Light Follower for Wall-E2, Part X – More PID Tuning‘).  At the time, I decided to use one of my best scientific research tools and simply ignore the problem, hoping it would either go away, or my subconscious mind (by far smarter than my conscious one!) would figure it out in the shower or while drifting off to sleep.

And, in fact, last night while drifting off to sleep, I remembered that the PID tuning for the 3-wheel robot had to take into account the fact that even small differences in drive wheel speeds get magnified by the free-castering front wheel.  Wall-E2, with its all-wheel drive behaves entirely differently, and since small wheel speed differences don’t get amplified into big directional changes, the PID tuning parameters appropriate for the 3-wheel version are too passive for the 4-wheel one.

So, I went back to the drawing board (again!) for PID tuning for the 4WD Wall-E2, starting with the current 3-wheel parameters as the ‘too passive’ baseline.  From my previous article, the final PID parameters were P = 0.1, I = 10, D = 0.2, with the input scaled by 1, 5, or 10 depending on IR beam signal strength.  My initial thought is that the 4WD robot needs a lot more ‘D’ (differential) to increase its turn rate with respect to IR beam heading changes, so I tried a couple of runs with the D value increased from 0.2 to 2 (factor of 10 increase).  As the following video shows, this did seems to increase Wall-E2’s agility somewhat, but still not enough to overcome even minor initial heading offsets, especially to the left.

After some more testing with different values of P,I,D, I began to wonder if I might be having problems with the basic IR detection hardware and homing software, independent of the PID tuning issue.  When I did the previous PID study, I also captured the raw detector data, which allowed me to determine how the PID tuning and the basic detection hardware/software were interacting.  I may have to go back and do that again with the 4WD setup

Stay tuned,




Charging Station Design, Part X

Posted 11 March 2017

The last few days have been spent partially implementing the software structure and state design described in my ‘Wall-E2 Operating Mode Review‘ of 06 March.  Up to this point, the only thing Wall-E2 knew how to do was wall-following, but there were (and still are) a number of ‘sub-modes’ associated with wall-following.  Now all of this code has to be grouped into the ‘Wall-Following’ state/function under the main program, and the new ‘Charging’ and ‘IR Homing’ state/functions added.

For purposes of testing, I decided to basically comment out all the wall-following code and concentrate on the IR Homing and Charge modes.  To do this, I added the new operating mode determination and top-level case switching code at the top of ‘loop()’, and left the MODE_WALLFOLLOW: case un-implemented.  the MODE_CHARGING code is all new, but the MODE_IRHOMING code was copied from my previous work with the 3-wheel robot last November.

After getting most of the MODE_CHARGING and MODE_IRHOMING code implemented, I ran some bench tests to see how well things work.  After finding and fixing a number of typos, logic errors, and downright goofs, I was able to video a successful IR home to charge, followed by a charge-completion disconnect (instead of waiting for a full charge termination, I tied execution to manual charge plug disconnect).  Here is the video


A couple of side notes from the above video

  • It is evident that the IR homing with PID works very well, to the point where the lead-in side rails almost aren’t needed (but only ‘almost’, I fear)
  • The fixed charging station fixture isn’t quite high enough.  In order to more accurately line up with the center of the charging port, I had to raise the fixture by about 5mm
  • The disconnect routine backs up far enough, but doesn’t quite make a complete 90º turn.  I should be able to tweak the turn duration a bit to make that happen.

So, at this point, I think I have most of the new parts of the operating system working, although some parts are hard to test due to the long charge times.  Here’s what I think remains to be done:

  • Reconnect and test the LIDAR and ping sensor hardware; this will be required to test wall-following and the charge station avoidance sub-mode
  • Reprint the charging station fixture with 5mm more height
  • Set up the full lead-in rail arrangement and confirm proper homing/engagement, along with proper dis-engagement, and proper avoidance when the battery isn’t low.
  • re-implement and test the wall-following code in the new structure, as MODE_WALLFOLLOW.  This should be just a bunch of cut-and-paste operations.
  • test the various ‘normal’ state transitions; wall-follow to IR homing to charge monitoring to wall-following
  • test the wall-follow to IR homing to charge station avoidance transition.
  • fully test the end-of-charge scenario.

12 March Update

I reconnected the LIDAR and ping sensor hardware, and confirmed (not without some wailing and gnashing of teeth!) proper operation.

I reprinted the charging station fixture with a 5mm pedestal, and transferred the LED/charging plug from the old fixture to the new one.

Set up the lead-in rails on my benchtop so that I could test both the ‘hungry’ and ‘not hungry’ IR homing scenarios.

Tested the ‘not hungry’ scenario by setting the ‘full’ threshold back down to 7.4V (50% charge, per http://batteryuniversity.com/learn/article/lithium_based_batteries).  The following video shows one of the test runs:


13 March Update:

After a bunch of software and hardware bugfixes, I think I finally have the ‘home to charge’ scenario working, as shown in the following video clip and edited telemetry capture:

The significant parts of the video are:

  • The POST test in the first few seconds
  • The successful IR homing operation
  • The successful charger plug engagement.  When the robot senses the charger plug, it commands the motors to stop.
  • Just after the charger plug engages, the charger’s battery relay is enabled, which disables power to the motors (note the red motor controller power LED goes OFF).
  • For this test, the BATT_CHG_TIMEOUT_SEC parameter was set to 10 seconds.  Rather than wait the entire 10sec, all but the first few and last few seconds were clipped.  Note that after the 10sec timeout, the robot disables the charger relay which re-applies motor power to the robot (note the red motor controller LED is re-enabled), and the robot backs off the charger plug.
  • The robot now backs completely clear of the lead-in rails, and turns away from the nearest wall before going back to wall-following mode.

I have also posted an edited version of the telemetry captured during this test.  As you can see, the robot transitions to IR homing mode, successfully homes on and engages with the charging plug, monitors the charging process, an then executes the ‘ExecDisconManeuver()’ to disengage from the charger and back out of the charging station area.


Stay tuned,



Wall-E2 Operating Mode Review

Posted 06 March 2017

At this point in the 4WD robot’s development, I think it might be time to review all of Wall-E2’s different operating modes, and what external sensor conditions determine which operating mode is active.  Previous to this point, the robot had only one operating mode – the ‘Wall-Following’ mode.  Now that the new battery pack has been added, along with the new capability for homing in on an IR beam to connect to a charging station has been added, the robot operating system must be enhanced to manage the additional operating modes.

Operating Modes/States:

  • Wall-Following:  This is the ‘normal’ operating mode, active when nothing else is going on (no IR beam present, no charging voltage present)
  • IR Beam Homing: Occurs when an IR beam is detected.  In this mode, a PID controller determines wheel speeds in an attempt to home in on the IR source.  This mode has two distinct sub-modes, depending on the battery state of charge.  if the battery is relatively full, then the front obstacle avoidance distance is increased such that the obstacle avoidance turn will occur before the robot gets captured by the lead-in side rails.  Otherwise, the obstacle avoidance distance is disabled entirely, allowing the robot to be captured and the charging connection to be made
  • Charging:  Occurs when the robot is connected to the charger.  In this mode, the charging status lines are monitored to detect end-of-charge (EOC).  When EOC is detected, the robot backs straight out of the lead-in rail area, and then turns 90º away from the nearest wall and transitions to wall-following mode.

Here is a draft state-transition diagram for the system

As can be seen from the diagram, the system starts out in the POST (Power On Self Test) state, and transitions to one of the other states depending on sensor input.

  • If no IR beam is detectable, and the charging station is not connected, then the system transitions to the normal ‘Wall-Following’ state.  The wall-following state continues until either an IR beam is detected, or a physical connection to a charging station is detected.  The normal exit condition from the wall-following state is via detection of an IR beam, which causes transition to the ‘IR Homing’ state.
  • In the IR Homing state, there are two possible behaviors; if the battery is more than 3/4 full (not quite sure how I’m going to define that, but…), then the robot will actively avoid the charging station by performing an obstacle avoidance 90º degree turn at a front distance larger than the extent of the charging station lead-in gate, and transitioning back to the ‘Wall-Following’ state.  If the battery is less than 3/4 full and a charge is desired, then the robot will continue to home in on the IR beam until a physical connection to the charging station is detected, whereupon the system transitions to the ‘Charging’ state.
  • In the Charging state, the system monitors the charging status signals, waiting for both ‘Fin1’ and ‘Fin2’ signals to become TRUE.  When this happens, the robot backs out of the charging station lead-in gate area, executes a 90º turn away from the nearest wall, and transitions back to the ‘Wall-Following’ state.

Here is a first cut at a system software structure chart that incorporates the above modes/states

Wall-E2 System Documentation

Posted 27 February 2017

In a previous post I described a charging status display panel that was co-mounted with the front-mounted IR detector assembly. The status panel showed charging power, ‘on-charge’, and ‘Finished charging’ status lights for both chargers.  This is what I was after with this panel, but I ran into some problems that led me to reconsider this whole arrangement.

  • In the original design, the status signal lines from the charger module ran directly to the display panel, but not to the controller.  The controller has to be ‘in the loop’ for charging status, as it has to decide when to disconnect from charging  power and from the charging station.  I added lines to piggyback the signals to the controller, but this became ugly very quickly
  • The physical panel I came up with worked OK, but was more than a little un-elegant; the LED mounting holes were way too big, so the physical alignment of the LEDs was very poor.

So, I decided to re-do this entire physical module and wiring layout.  When considering the wiring, I had a couple of alternatives.

  • I could essentially re-do the original wiring plan – i.e. run a cable from the charging module to the display panel, and then tap off this cable to the controller.  This is messy, but only uses 6 controller pins.
  • I could run the cable from the charging module directly to the controller, and then run a separate cable from the controller to the display panel.  This uses 12 controller pins, but has the advantage of being much neater, and considerably simplifies the display panel wiring.

Considering these two alternatives, the natural question becomes ‘can I afford to waste 6 controller pins just for neatness/elegance?’  To answer this question I decided to do an audit of the current Mega pin usage.  I created a nice little Excel spreadsheet listing all the available Mega pins, their nominal functions (analog/digital/serial) and their current assignments, as shown below:

As can be seen from the document, there are lots of unused pins available, so using an additional 6 pins for neatness/elegance seems like a pretty easy trade-off.  So, my plan is to run the charger module status cable to controller pins 34, 32, 30, 28, 26, 24 & 22 (Pwr1, Chg1, Fin1, Coil En, Fin2, Chg2, Pwr2), and a corresponding LED drive cable from controller pins 35, 33, 31, 29, 27 &  25

04 March 2017 Update

After adding all the status signal input and status LED output lines associated with the Charger Module and moving the ‘Charger Connected’ line from pin 2 to pin 23 to be in the same group with all the other charger-associated lines, I updated the pin assignment spreadsheet as shown in the following PDF document:

The  next challenge was to reorganize and update the system schematic to reflect all the new inputs, outputs, and function blocks.  The complete system schematic is shown below:




4WD Robot System Schematic with pin assignments as of 05 March 2017

For completeness, I have included front, rear and both side views of Wall-E2 in its current state of construction.  The new battery pack and associated charging electronics has been fully integrated into the internal volume, and all the charging-station related modules/electronics have also been mounted.   The only thing missing physically at this point is the second deck with its two sonar ping sensors, the LIDAR forward distance sensor, and the forward red laser pointer

Front view showing charger jack coupler and new charge status display

Left-side view. Nothing much has changed in this view

Rear view showing ‘taillight’ assembly. Loose cabling is for 2nd deck ping sensors

Right-side view showing some of the new cable bundles



Charging Station Design, Part IX

Posted 20 February 2017

As part of the project to implement autonomous charging capability for Wall-E2, I needed a way to monitor main battery voltage in normal ‘run’ mode, in order to tell when to start searching for a charging station.  The main battery is a 2-cell LiPo stack, and so has a nominal stack voltage of around 7.5-8V when fully charged.  Since this is well above the Arduino Mega’s internal +5V operating voltage, I can’t measure this directly via the analog input ports.  So, I installed a 1/3-2/3 resistive voltage divider between the main battery voltage input, analog input A0, and ground, as shown in the following schematic detail.

System schematic detail showing resistive voltage divider for battery voltage monitoring

The nominal reading at A0 is 1/3VBatt.  Using the Arduino’s internal +5V regulator as the reference, the nominal battery voltage is 5*[A0/1023]*3.

To test this arrangement, I modified the operating software to print out the raw and calculated battery voltage values, and got the following printout.

BattMonVol: Raw 568 pin 2.78V TTL Batt 8.33V
BattMonVol: Raw 569 pin 2.78V TTL Batt 8.34V
BattMonVol: Raw 539 pin 2.63V TTL Batt 7.90V
BattMonVol: Raw 559 pin 2.73V TTL Batt 8.20V
BattMonVol: Raw 567 pin 2.77V TTL Batt 8.31V
BattMonVol: Raw 570 pin 2.79V TTL Batt 8.36V
BattMonVol: Raw 568 pin 2.78V TTL Batt 8.33V
BattMonVol: Raw 554 pin 2.71V TTL Batt 8.12V
BattMonVol: Raw 553 pin 2.70V TTL Batt 8.11V
BattMonVol: Raw 566 pin 2.77V TTL Batt 8.30V

In addition, I measured the battery voltage directly using my trusty multimeter, and got 8.03V, so a pretty reasonable monitor setup.


Next up; I had previously added the 4-detector IR module to the robot, and now I needed to integrate the IR detector measurements into the telemetry stream.  The battery monitor is on A0, and the 4 detectors are on A1-A5.  After adding the telemetry code, I got the following printout.

Time Batt DET1 DET2 DET3 DET4
0.20 8.15 937 935 651 950
0.40 8.01 943 934 739 952
0.60 7.61 934 935 792 953
0.80 7.90 932 937 824 955
1.00 8.14 940 940 847 957
1.20 8.04 927 937 862 956
1.40 7.70 930 939 876 957
1.60 7.70 932 942 889 959
1.80 8.11 935 940 898 957
2.00 8.06 929 941 899 959
2.20 7.89 944 943 904 960

Now I will add back in the left/right/forward distances, the forward variance, and the left/right wheel speeds.  After adding everything back, I get the following telemetry stream:


Time	Batt	DET1	DET2	DET3	DET4	Left	Right	Front	Track	Var	LSpd	RSpd
0.20	8.12	933	944	748	956	200	200	400	IR	407	127	127
2.00	7.65	936	941	818	955	200	200	48	IR	446	127	127
3.81	8.08	924	934	821	951	200	200	64	IR	516	127	127
5.61	8.08	942	933	830	951	200	200	85	IR	641	127	127
7.42	8.15	938	943	829	956	200	200	65	IR	705	127	127
9.22	7.92	939	945	832	958	200	200	71	IR	781	127	127
11.02	8.01	944	939	827	954	200	200	73	IR	858	127	127
12.83	8.11	941	932	826	950	200	200	69	IR	921	127	127