Posted 06 March 2022

I’ve pretty much finished with transitioning my autonomous wall-following robot from the old Arduino MEGA 2560 main controller to the new Teensy 3.5 main controller, and now I am moving on to actually getting Wall-E3 to do the job it was created for – namely, to follow walls autonomously. This post describes the result of a multi-lap run through my little testing ‘sandbox’, consisting of a set of barriers forming a 2m X 2m rectangular ‘room’. Here’s a short video showing the run:

I captured the telemetry output from the run and went back through it pretty much line-by-line, trying to make sure I understood all the actions displayed in the video – particularly the little off-piste excursion at about 1:00 on the second lap, just before the end of the run (the run was cancelled when a portion of the wall fell over on Wall-E3).

First Leg: 36.0- 38.9 Sec (5-8 sec in video)

In the first leg, the robot starts off parallel to the wall on the left, but too close (16cm instead of 40cm). It makes a 27.1º CW turn away from the wall to achieve a cut angle of 30º, moves forward, and then turns back 30º CCW to end up parallel to the wall, and about 36cm away – almost perfectly spaced 40cm off the wall.

Next it tracks down the wall from 14.992 sec to 17.390sec , trying (and generally succeeding) to maintain the 40cm standoff distance.

At 17.390 sec it detects an upcoming obstacle (the obstacle detection distance was set to 20cm for this run), and stops (not quite getting all the way stopped before running into the wall – oops!).

First-to-Second Leg Transition:

The handling procedure for the ‘OBSTACLE_AHEAD’ case is to stop, back straight up to achieve the nominal wall offset distance (40cm here), then make a 90º turn (CW in this case) away from the wall to orient itself parallel to the wall again.

As can be seen from the above telemetry, that is exactly what happens, backing up to the point where the front LIDAR sensor shows 38cm and then making the required 90º turn with SpinTurn(CW, 90.00, 45.00). The ‘backup and turn’ evolution is completed in approximately 1.5 sec.

Second Leg: 47.4 – 49.0 Sec (16-19 sec in video)

Second-to-Third Leg Transition:

Third Leg: 57.0 – 59.8 Sec (25-29 sec in video)

Transition and Fourth Leg: 61.0 – 70.4 Sec (30-40 sec in video)

Transition and Fifth Leg: 71.6 – 80.9 Sec (40-50 sec in video)

Fifth-to-Sixth Leg Transition: 82.1 – 88.0 Sec (50-58 sec in video)

Sixth Leg up to Anomaly 88.9 – 89.8 Sec (57-59 sec in video)

On this leg an anomaly occurred. The robot detected a ‘Stuck Ahead’ condition, defined by the condition where the mathematical variance of the last N front LIDAR distance readings falls below a set threshold. This should never happen while the robot is actually moving, but it clearly did happen in this case (unfortunately I wasn’t recording the front distance measurement or the distance measurements to the other wall, so I can’t go back and see exactly what happened). The recovery procedure for a ‘stuck ahead’ condition is to make a 90 deg turn away from the nearest wall, move forward for 1 second, and then make another 90 deg turn to return to a parallel course, but offset 10-20 cm from the previous track. In this case, the robot turned toward the nearest wall, clearly a mistake (it was a mistake in TrackLeftWallOffset() – since fixed). However, it was not a disaster, as the robot made the second turn before hitting the wall, and from there on it returned to normal left wall tracking mode.

Summary:

This first test of left wall tracking performance was very encouraging. The robot was able to continue tracking operations over several laps, including an instance where it recovered from an inadvertent ‘Stuck’ detection. The test could easily have continued until the batteries died, but had to be aborted when one section of the foam-core wall fell in on top of the robot – oops!

Also, this run pointed out the need for more focused telemetry. For this test I was only reporting the left-side and rear distances, but now I know I need to add the right-side measurements as well as the front and rear variance numbers.

09 March 2023 Update:

After cleaning up some messy initialization code, and improving telemetry readouts, I ran another complete left-side wall-tracking lap in my sandbox, as shown in the following short video:

The telemetry for this run is shown below:

From the telemetry, it takes about 8 sec for all sensor hardware initialization. After that the left/right/front/rear distance arrays are initialized, and the initial front/rear variances are calculated. All this is summarized on line 26-27.

First leg: 12.866 – 15sec (3-5 sec in video)

Left-side tracking starts on line 34. First (line 37) the robot turns to its initial offset capture heading, moves to the desired offset distance (not shown) and then turns back to parallel the wall (line 39). Actual tracking starts on line 43 at 12.866 sec elapsed time (this corresponds to about 3 sec into the video)

At line 65 (about 15 sec elapsed time) the robot ‘sees’ the upcoming wall, stops and then backs up to 38cm (16.4 – 17.3 sec, 5-6 sec in video). At line 78 it makes a 90deg CW turn to line up with the current wall section, and then navigates down the wall (18.6-21.3sec, 8-11sec in video)

Second leg: 18.6 – 21.3sec (8-11 sec in video)

The robot ‘sees’ the upcoming wall on line 119 (21.010 sec, 11sec in video), backs up (lines 123-129, 11-12 sec in video) and makes another 90deg CW turn to follow the 3rd wall

The third and 4th legs are very similar to the first two, with the robot ending back where it started at 32.574 sec (23 sec on video), ‘seeing’ the upcoming wall at line 221. At this point I transmitted the ‘C’ character over the wireless link to enter manual control to terminate the run.

Summary:

This 4-leg run was pretty much perfect. I adjusted the MIN_FRONT_OBSTACLE_DIST_CM from 20 to 30cm, and this stopped the robot from banging its head against the walls – yay! Also, the telemetry readout changes made for a much more understandable output. I was happy to see that the front variance stayed well above 10,000 the whole time, but unhappy to see that the rear variance was essentially zero the entire time. The low rear variance is due to the fact that the rear VL53L0X sensor range is only about 100cm, and after that it always reports ‘819’. This is not a real problem – it just means that I can’t use the rear variance number to detect a ‘rear stuck’ condition unless it happens within a meter or so from a wall. Hmm, maybe I could use the information from both the front & rear variance numbers to create a more robust detection system.

Stay tuned,

Frank