02 Apr

End-to-end port arrays with new microcontroller definition!

Richard Lin (Ducky) ducky edg edg-model port-arrays

Finally, payoff for a feature that's been in low-level development for over a year, and in heavy development for the past few weeks! Port arrays are now advanced enough to implement an abstract microcontroller class, and the end-to-end demo is apparent from the source-measure unit example layout:

smu-new

It looks mostly the same - which means that everything I did before, is still supported, all the way down to the manually assigned pinnings. The parts that have changed (the parts scattered across the top) are changes in names, both from the refactoring of the microcontroller block to incorporate the programming header and crystal, and a prior refactor of power converters.

So... why all this work to end up with more of the same? What does all this give us?

  • A more encapsulated microcontroller abstract block. The idea behind the new microcontroller block is that you give it power and IOs, and it figures out the rest. Have frequency requirements, as inferred from connected USB or CAN ports? It'll automatically generate a crystal for you. You almost certainly need a programming port, so it'll automatically create that too.
  • This also provides the ability to switch microcontrollers from the refinements system... and eventually have microcontrollers be part of the search space when we get around to design space exploration. No need to go into your system description, change out the microcontroller, and perhaps deal with ripple effects like changing the programming header.
  • A completely revamped pin mapper. The prior pin mapper wasn't very principled, largely based around pin numbers without a concept of pin models, but the new one models individual pins, including when part of a bundle (like SPI or I2C) and when different (like when some, but not all, are 5v tolerant). Furthermore, it also defines the pin name, so in the future we can auto-generate header files for firmware that define the pins and interfaces.
  • Flexible IOs, instantiated on-demand. Previously, the system had to instantiate every possible port provided, even in impossible combinations; now we dynamically generate pins according to how many are requested, up to what can be allocated from the pin pool.
  • Cleaner syntax for pin assignment. Previously, it relied on net naming, which resulted in a nasty top-level syntax where we had to name all the nets. Under the new syntax, allocations can be given a name, and the pin assignment specifier can directly refer to that.
  • ... and because we've obsoleted the above, a lot of cruft code can be removed. Always nice when it's possible to have more deleted lines than added lines!

Continuing work will need to refactor all the other examples (which should be more straightforward given what is one of the more complex proof-of-concepts), then we can move onto array-to-array connections (probably 2-3 weeks), multipack devices (hopefully more straightforward, but probably 2-3 weeks too), and another iteration of example devices that is more optimized and cleaner.

Next Post Previous Post

Search

Popular Tags

foray origami robots blimp ducky vr edg SLAM computer vision computational design roco slam Origami rocolib arduino RoCo design Robot Compiler simulation Motion Planning autonomy edg-model mesh reinforcement learning; multi-agent; mean-field; logics create; kalman filter; motors imu friction mesh network tank esp32 networking contacts multi-agent pushing auxetic machine learning dynamics esp now visual processing wireless control communication webapp pcbs structure ROCO i2c path planning cars Robotica reinforcement learning computer skill openmv test motor dataset visual DARPA odometry Battery surface structure power consumption dash port-arrays modeling origami paper frequency diversity semantic infrastructure auxetics feedback gondola machine vision Consensus bistable auxetic controller gestural intuition mixed reality unit cell robot crawler gestural interface open house network create; kalman filter; EM; refactoring 4-wheeled darpa; create; icra2021 apriltags lidar logic control FORAY perception Quantum Information crazyflie 433mhz optimization propeller Foray structures sensors environmental design radio DER Kullback-Leibler Divergence lasercutter tutorial von Mises Fisher Distribution IR simulink legs project management localization distributed optimization blynk Auxetics painlessmesh experiment results offline reinforcement learning exam research proposal altimeter thrust PCB sensor fusion gate or webots multi-agent path planning UAV RL integration test arnhold joystick balloon test vision processing pushing problem modeling contacts mesh networking motor configuration nodemcu swarm object detection fusionbot ros2 rviz2 gazebo conference matlab arduino nano decentralized surfaces keyboard IROS Integrated Demo throughput peripheral device paper review reinforcement learning; motorized boats Writing slam; paper review rhino Short Post range distance surp origami robot nylon pvdf elastic polymers plastic hot plates reinforcement learning; multi-agent; mean-field; game theory; mean field; reinforcement learning current reinforcement learning; multi-agent; Xbee Zigbee robot compiler spi contact neural network dynamic modeling quasi-static modeling edg-examples Kalman Filter port-array von Mises Fisher von Mises-Fisher literature review multipack car Zero Elastic Energy modes swarm control solar cars system ID serial monitor edg-ide Discrete Elastic Rods ceres debug Consensus Algorithms coriolis force dynamic model proposal wtf deep learning pdms interpolation wireless signal strength reinforcement learning; multi-agent; decentralized misc reinforcement learning; multi-agent; mean-field; stationary demo video flytrap papers steering structured field pivoting differential power detectionrate color shape edg-refactoring pain python vision Machine Learning Q-Learning Model-Free release conferences quasi-static pushing liquid crystal elastomer nonholonomic systems iot grant feedback-controlled controls trajectory optimization surface contact Characterization tool ML multi-agent path finding Liquid Crystal Elastomers Learning kinematic_model reservoir computing 2.4 GHz concept 433 MHz Bayesian Network creative Computer skill internal silicone integrated system instance segmentation marginal cost pricing bootstrapping Bayesian networks ensemble methods offline Rl hardware manipulation COVID 19 paper cutter ESP32 kalman filter; multi-robot state space delta tolling buoyancy chiral square unit cell pressure distribution model prediction thrust configuration grid fabrication firmware protobuf #activecapturingmechanism #claw 3D-CHESS; kalman filter boxboat tracking model-based RL von Mises Distribution slam; flowchart; spring-mass 3D-CHESS; 433 rssi signal strength multirobot system writing in-situ design buoyancy equations boat deployment cell cameras der newton's method Barycenter Euler-Bernoulli beam sma-based actuator game theory Bessel functions von Mises-Fisher Distributions ide HDL board design battery current sensor ZMP center of friction Multi-Agent Systems code balloon semantic segmentation MIMO communications ICRA ICML guassian processes probabilistic neural networks graph generators MBRL batch learning ros edg-compiler multirobot optitrack adaptive control motor driver submission DNN kalman filtering point cloud 2.4ghz latency scenic codesign presentations machine training preliminary exam multiple devices inkscape material multi-object tracking ICLR Python actuation catching mechanism integration flapping color_segmentation lab_data result segmentation on multiple object and centers finding competition prelab multiple blimps pid defender Synthesizable Radio 3d printing kalman filter motor distribution barometer detection lift force depth estimation cad solidworks design tool pixracer pixhawk ardupilot flight controller regression fly test sensor selection