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After months of confusion, my DIY rover's path planning is no longer a disaster, lmao
I've been working on a custom robot platform and the A* algorithm kept generating these janky, inefficient routes that caused constant stalls. By integrating a simple cost map and tweaking the heuristic weights based on real-time sensor feedback, the bot now smoothly navigates around my workshop obstacles. It's a small step, but finally seeing it execute clean turns and avoid my toolboxes feels like a huge personal breakthrough in understanding autonomous systems.
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the_barbara15h ago
Sensor hysteresis gave me nightmares too until recalibration.
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emeryb3418h ago
Struggled with similar A quirks on my own rover project last year. Found that adding a penalty for directional changes smoothed out those jagged paths immensely. I also layered in a simple sensor fusion step that adjusted node costs based on proximity data, which killed most of the hesitation near obstacles. Tuning the heuristic to be less greedy made the bot prioritize smoother arcs over raw shortest distance. That breakthrough moment when it finally navigates cleanly is just the best feeling, isn't it? What sensor feedback are you using for your real-time adjustments?
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robin8366h ago
Tuning that heuristic felt like wrestling ghosts, but man, seeing it carve smooth paths was pure magic.
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