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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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hey, i just figured i’d put this out here in case it helps: meccanum wheels, by nature, have a LOT of slip - that’s how they’re able to move in any direction. i’ve had quite a bit of experience with the math and kinematic behind this (two libraries i’ve written/am writing, Pathfinder and Pathfinder2, as well as a library the other programmer on my team wrote, OdometryCore) and it’s VERY HARD to accurately track the position of a meccanum robot only using the encoders in the wheels. it’s not impossible, but it’s very, very challenging. the more your robot moves, the less accurate it becomes, and it will very quickly report positions that are nowhere near where your robot actually is. you can go for it, but i would strongly encourage you check out three wheel odometry instead - it’s been very accurate and allowed us to do really cool things, like accurately record a robot’s movement and play it back perfectly. you’ll have much more success with three wheel odometry - my team designed a custom odometry system and i’m sure they’d be happy to give you more information if you’d like. best of luck :)
hey, i just figured i’d put this out here in case it helps: meccanum wheels, by nature, have a LOT of slip - that’s how they’re able to move in any direction. i’ve had quite a bit of experience with the math and kinematic behind this (two libraries i’ve written/am writing, Pathfinder and Pathfinder2, as well as a library the other programmer on my team wrote, OdometryCore) and it’s VERY HARD to accurately track the position of a meccanum robot only using the encoders in the wheels. it’s not impossible, but it’s very, very challenging. the more your robot moves, the less accurate it becomes, and it will very quickly report positions that are nowhere near where your robot actually is. you can go for it, but i would strongly encourage you check out three wheel odometry instead - it’s been very accurate and allowed us to do really cool things, like accurately record a robot’s movement and play it back perfectly. you’ll have much more success with three wheel odometry - my team designed a custom odometry system and i’m sure they’d be happy to give you more information if you’d like. best of luck :)
hey, i just figured i’d put this out here in case it helps: meccanum wheels, by nature, have a LOT of slip - that’s how they’re able to move in any direction. i’ve had quite a bit of experience with the math and kinematic behind this (two libraries i’ve written/am writing, Pathfinder and Pathfinder2, as well as a library the other programmer on my team wrote, OdometryCore) and it’s VERY HARD to accurately track the position of a meccanum robot only using the encoders in the wheels. it’s not impossible, but it’s very, very challenging. the more your robot moves, the less accurate it becomes, and it will very quickly report positions that are nowhere near where your robot actually is. you can go for it, but i would strongly encourage you check out three wheel odometry instead - it’s been very accurate and allowed us to do really cool things, like accurately record a robot’s movement and play it back perfectly. you’ll have much more success with three wheel odometry - my team designed a custom odometry system and i’m sure they’d be happy to give you more information if you’d like. best of luck :)
if you’re sure you want to go the in-wheel encoder route, check out wpilib’s implementation of it here. it uses EJML for most of the math, but you can remove it if you’re comfortable with matrixes