mhtirogla
Home
Systems
API
Pricing
About
Log in
← Back
Home
›
Systems
›
Robotics
humanoid-robot
humanoid robot control stack
Figure, Optimus
System
Techniques · 35
Primitives · 93
humanoid-robot
Deterministic simulation testing
distributed · medium: Run the whole system in one thread under a seeded scheduler with simulated network, disk and clock, so every failure replays from its seed.
›
Primary-backup replication
distributed · medium: One node orders all writes and ships them to standbys; the acknowledgement rule (none, one, all) sets what a crash loses, and an external arbiter decides who takes over.
›
A/B partition updates
embedded · medium: Two bootable slots and a small atomic metadata block: write the new image to the idle slot, try it once, and fall back by itself unless it reports healthy.
›
Battery state estimation
embedded · medium: State of charge / health / power from coulomb counting, OCV curves and model-based observers
Safety monitor architecture
embedded · medium: Independent doer/checker safety monitor that forces a safe state when the main channel misbehaves
Domain randomization
machine-learning · medium: Randomize simulator physics and visuals so policies trained in sim transfer to real robots
Imitation learning
machine-learning · medium: Learning policies from demonstrations: behavior cloning, DAgger, covariate shift
Extended Kalman filter
robotics · low: Kalman filter for nonlinear motion and measurement models: linearize f and h with Jacobians at the current estimate each step. The default estimator in robot navigation.
›
Action chunking
machine-learning · low: Policy predicts a chunk of future actions per step, executed with temporal ensembling for smooth control
Transformer block
ml-training · low: The decoder-only pre-norm block (attention plus MLP on a residual stream) behind every modern LLM, with exact shapes, parameter, FLOP and KV-cache counts.
›
Fixed-rate control loop
embedded · low: Run a controller at an exact period using absolute deadlines and a fixed dt, so jitter never accumulates and the math stays valid.
›
Hdr histogram
data-structures · low: Log-linear bucketed histograms with bounded relative error for latency percentiles
Real time fieldbus
embedded · low: Deterministic cyclic fieldbuses (EtherCAT, PROFINET IRT): on-the-fly frames, distributed clocks
Process supervision
hardware-os · low: A parent process starts services, reaps their exits and restarts them under a delay and burst-limit policy, then stops them with SIGTERM before SIGKILL.
›
Action tokenization
machine-learning · low: Discretize or compress continuous robot actions into tokens a sequence model can predict
Weight quantization
ml-training · low: Store weights as 8/4-bit integers with per-group scales; decode is memory-bound, so 4-bit weights give about 3-4x tokens/s and fit 4x larger models.
›
Gait phase scheduling
robotics · low: Contact schedules and phase oscillators deciding stance and swing per leg
Mutual TLS
security · low: TLS where the client also proves a certificate key, so every connection carries a verified, rotatable machine identity.
›
Graceful draining
systems · low: On a termination signal, stop taking new work, finish in-flight work until a deadline, tell clients to reconnect elsewhere, then exit; clients resume from a token.
›
Cooperative scheduling
concurrency · low: Green threads/coroutines yielding at await points on a user-space scheduler
Record replay
distributed · low: Record every nondeterministic input (time, randomness, I/O, model and tool outputs, per-tick player input) and re-execute deterministically for debugging, replays and state rebuild
PRNGs (PCG, xoshiro)
numerics · low: Small, fast, statistically strong non-cryptographic generators: PCG32 and xoshiro256**, with seeding, parallel streams and unbiased ranges.
›
Leases
distributed · low: A lock that expires on its own: bounded-time ownership that survives crashes and partitions, given bounded clock drift and fencing tokens on writes.
›
+ 28 more techniques
+ 77 more primitives
System
Techniques · 35
Primitives · 93
humanoid-robot
Deterministic simulation testing
distributed · medium: Run the whole system in one thread under a seeded scheduler with simulated network, disk and clock, so every failure replays from its seed.
›
Primary-backup replication
distributed · medium: One node orders all writes and ships them to standbys; the acknowledgement rule (none, one, all) sets what a crash loses, and an external arbiter decides who takes over.
›
A/B partition updates
embedded · medium: Two bootable slots and a small atomic metadata block: write the new image to the idle slot, try it once, and fall back by itself unless it reports healthy.
›
Battery state estimation
embedded · medium: State of charge / health / power from coulomb counting, OCV curves and model-based observers
Safety monitor architecture
embedded · medium: Independent doer/checker safety monitor that forces a safe state when the main channel misbehaves
Domain randomization
machine-learning · medium: Randomize simulator physics and visuals so policies trained in sim transfer to real robots
Imitation learning
machine-learning · medium: Learning policies from demonstrations: behavior cloning, DAgger, covariate shift
Policy gradient and PPO
machine-learning · medium: Raise the log-probability of actions in proportion to their advantage; PPO clips the probability ratio so several epochs on one rollout stay safe.
›
Vision transformer
ml-training · medium: ViT: patch embeddings, position encodings, encoder blocks; vision-language connectors
Rigid body dynamics algorithms
physics · medium: Featherstone RNEA/ABA/CRBA for articulated-body inverse and forward dynamics
Field oriented control
robotics · medium: FOC of BLDC/PMSM motors: Clarke/Park transforms, current PI loops, space-vector PWM
Impedance control
robotics · medium: Make a robot behave like a spring-damper at the contact point for safe interaction
Inverse kinematics
robotics · medium: CCD/FABRIK/Jacobian solvers posing joint chains to reach targets
Model predictive control
robotics · medium: Each tick, solve a small optimization over a predicted horizon, apply only the first input, repeat. Handles constraints and multiple inputs that a PID loop cannot.
›
Visual inertial odometry
robotics · medium: Fuse camera features with IMU preintegration in a filter or sliding-window optimizer for 6-DoF pose
Whole body control
robotics · medium: Prioritized task-space control solved as a QP over joint torques and contact forces
Coverage-guided fuzzing
security · medium: Mutate inputs, run an instrumented target, and keep any input that reaches a new code edge; feedback turns blind guessing into incremental search.
›
Point-in-time recovery
storage · medium: Periodic base backups plus a continuously archived change log let you rebuild the state as of any instant, then branch from there.
›
Delta debugging
compilers · medium: Ddmin minimization of failing inputs or change sets
Binary delta diff
compression · medium: Bsdiff, VCDIFF and xdelta-style binary patches between file versions
Fault injection
distributed · medium: Inject latency, errors, kills and partitions via proxies, netem or hooks
Equivalent circuit battery model
embedded · medium: Thevenin RC-network battery models with OCV-SoC curves and parameter identification
Levenberg marquardt
numerics · medium: Damped Gauss-Newton nonlinear least squares for model calibration
Quadratic programming
optimization · medium: Convex QP solvers (active-set, interior-point, ADMM) for constrained optimization
Camera calibration
robotics · medium: Intrinsic/extrinsic calibration (Zhang's method, distortion models, bundle adjustment)
Signed update metadata (TUF)
security · medium: Separate signing roles with thresholds sign small metadata pinning file hashes, versions and expiry, so clients detect rollback, freeze and mix-and-match and recover by rotating the root.
›
ARIES recovery
storage · medium: Three-pass crash recovery (analysis, redo, undo) for steal/no-force buffer pools; repeats history, then rolls back losers with compensation log records.
›
Interior-point method (primal-dual,…
optimization · medium: Follows the central path with Newton steps on the perturbed KKT system, one sparse Cholesky per iteration; Mehrotra's predictor-corrector makes it fast.
›
Key rotation
security · medium: Rotating keys without downtime: key ids, overlap windows, re-wrapping, JWKS publication, revocation
Syscall interception
security · medium: Intercept syscalls via ptrace, seccomp user notify or a user-space kernel
Buffer pool
storage · medium: The database's own page cache (frames, page table, pin counts, dirty bits, replacement) so it, not the OS, controls eviction, write order and I/O.
›
Sparse direct solver
numerics · medium: Solve sparse Ax = b exactly by reordering, symbolic analysis, numeric LLᵀ/LU and triangular solves; fill-in, not flops per entry, decides the cost.
›
Envelope encryption
security · medium: Encrypt each object with its own data key and wrap that key under a KMS-held key, so rotation re-wraps 60 bytes and deleting a key shreds data.
›
Fill-reducing ordering
numerics · medium: Permute a sparse symmetric matrix before Cholesky/LU so the factor has few new nonzeros; minimum degree, nested dissection and RCM trade quality, speed and parallelism.
›
Graph partitioning
graphs · medium: Split a graph into k balanced parts with few edges between them; multilevel coarsen-partition-refine (METIS, KaHIP) for quality, streaming heuristics (LDG, Fennel) for one-pass scale.
›
Extended Kalman filter
robotics · low: Kalman filter for nonlinear motion and measurement models: linearize f and h with Jacobians at the current estimate each step. The default estimator in robot navigation.
›
Action chunking
machine-learning · low: Policy predicts a chunk of future actions per step, executed with temporal ensembling for smooth control
Transformer block
ml-training · low: The decoder-only pre-norm block (attention plus MLP on a residual stream) behind every modern LLM, with exact shapes, parameter, FLOP and KV-cache counts.
›
Fixed-rate control loop
embedded · low: Run a controller at an exact period using absolute deadlines and a fixed dt, so jitter never accumulates and the math stays valid.
›
Hdr histogram
data-structures · low: Log-linear bucketed histograms with bounded relative error for latency percentiles
Real time fieldbus
embedded · low: Deterministic cyclic fieldbuses (EtherCAT, PROFINET IRT): on-the-fly frames, distributed clocks
Process supervision
hardware-os · low: A parent process starts services, reaps their exits and restarts them under a delay and burst-limit policy, then stops them with SIGTERM before SIGKILL.
›
Action tokenization
machine-learning · low: Discretize or compress continuous robot actions into tokens a sequence model can predict
Weight quantization
ml-training · low: Store weights as 8/4-bit integers with per-group scales; decode is memory-bound, so 4-bit weights give about 3-4x tokens/s and fit 4x larger models.
›
Gait phase scheduling
robotics · low: Contact schedules and phase oscillators deciding stance and swing per leg
Mutual TLS
security · low: TLS where the client also proves a certificate key, so every connection carries a verified, rotatable machine identity.
›
Graceful draining
systems · low: On a termination signal, stop taking new work, finish in-flight work until a deadline, tell clients to reconnect elsewhere, then exit; clients resume from a token.
›
Cooperative scheduling
concurrency · low: Green threads/coroutines yielding at await points on a user-space scheduler
Record replay
distributed · low: Record every nondeterministic input (time, randomness, I/O, model and tool outputs, per-tick player input) and re-execute deterministically for debugging, replays and state rebuild
PRNGs (PCG, xoshiro)
numerics · low: Small, fast, statistically strong non-cryptographic generators: PCG32 and xoshiro256**, with seeding, parallel streams and unbiased ranges.
›
Leases
distributed · low: A lock that expires on its own: bounded-time ownership that survives crashes and partitions, given bounded clock drift and fencing tokens on writes.
›
Write-ahead log
storage · low: Append each change to a checksummed sequential log and fsync it before touching data pages; the basis of crash durability in nearly every database.
›
Health checking
systems · low: Decide per backend whether to route to it using probes and real-traffic errors, with consecutive-count hysteresis, capped ejection and a panic fallback.
›
Watchdog timer
embedded · low: A hardware down-counter that resets the chip unless software proves, in time and in a plausible pattern, that it is still healthy.
›
CRC32C checksums
hardware-os · low: The Castagnoli CRC-32 with dedicated instructions on x86 (SSE4.2) and ARMv8. It is the standard fast integrity check for storage blocks, logs and network frames.
›
Secure boot chain
security · low: Each boot stage verifies the signature of the next before running it, anchored in an immutable ROM key hash, with version counters against downgrade and a TPM log of what ran.
›
Spline interpolation
numerics · low: Linear, bilinear/trilinear and cubic spline interpolation on grids and tables
End to end protection e2e
embedded · low: Per-message counter, ID and CRC over a black channel to detect loss, repetition, corruption, delay
Memory protection unit
embedded · low: A handful of base/size regions with permissions, checked on every access by the CPU, give microcontroller tasks isolation and stack-overflow traps without an MMU.
›
Redundancy voting
embedded · low: N-modular redundancy and MooN voting (2oo3, TMR) with discrepancy detection
Data augmentation
machine-learning · low: Generate label-preserving variants of each training example on the fly to enlarge the effective dataset and bake in invariances.
›
Rigid-body dynamics
physics · low: Advance one 3D rigid body per step from force and torque: semi-implicit Euler for position, an inertia tensor in the body frame, and quaternion orientation updated by the exponential map.
›
Loss functions
machine-learning · low: The scalar a model minimizes: cross-entropy for classes and tokens, MSE or Huber for values, each with a stable form and simple gradient.
›
AdamW
ml-training · low: Adam's per-parameter adaptive steps with weight decay applied directly to the weights; the default optimizer for transformers and LLM pretraining.
›
Gradient clipping
ml-training · low: Clipping gradients by global norm (or value) to prevent loss spikes; interaction with mixed precision
Reverse-mode automatic differentiat…
ml-training · low: Record the forward computation on a tape, then sweep it backwards once to get the gradient of a scalar loss for all inputs.
›
Attention variants
machine-learning · low: Multi-head, multi-query, grouped-query, sliding-window and latent attention; same softmax(QKᵀ/√d)V core, different trade-offs between quality and KV-cache size.
›
Embeddings
machine-learning · low: A learned table mapping discrete ids to dense vectors: gather forward, sparse scatter-add backward, row-wise optimizers to keep huge tables cheap.
›
Quaternion rotations
geometry · low: Unit quaternions as 3D rotations: 4 floats, cheap composition, no gimbal lock, plus the conversions, interpolation choices and numerical care needed in practice.
›
LU and Cholesky factorization
numerics · low: Factor A = PLU (any square matrix, partial pivoting) or A = LLᵀ (SPD) once in O(n³), then solve each right-hand side in O(n²).
›
Rigid-body transforms (SE(3) poses)
robotics · low: Represent, compose, invert, integrate and interpolate 3D poses as unit quaternion plus translation, with exp/log maps for small motions and uncertainty.
›
PWM generation
embedded · low: A timer's counter, period and compare registers draw the pulse train; preload, dead time and DMA make duty changes glitch-free, shoot-through-free and cheap.
›
PID controller
robotics · low: Drive a measured value to a setpoint with three terms on the error: proportional, integral, derivative. The default feedback loop for motors, heaters, drones and gimbals.
›
Phase-locked loop (digital)
signal-processing · low: Feedback loop that locks a local oscillator to the phase and frequency of an input tone; the core of carrier recovery, clock recovery and GNSS tracking.
›
PCA and SVD
machine-learning · low: Find orthogonal directions of maximum variance by an SVD of the centred data; randomized SVD gets the top k components in a few passes.
›
Runge-Kutta 4
numerics · low: The classic four-stage, fourth-order ODE step; error drops 16× when the step halves, with no derivatives or past steps needed.
›
Kalman filter
robotics · low: Optimal recursive estimator for a linear system with Gaussian noise: fuses a motion model with noisy measurements into a state estimate plus its covariance.
›
Image pyramids
graphics · low: Gaussian/Laplacian pyramids and tiled multi-resolution images for zoom and blending
Feature detection orb
robotics · low: FAST corners with oriented BRIEF descriptors and Hamming matching for tracking and relocalization
Code coverage instrumentation
compilers · low: Insert counters into compiled code to record which blocks, edges or lines ran; a spanning tree of the control-flow graph cuts the counters needed.
›
Fast hash functions
data-structures · low: Non-cryptographic hashes built from 64×64→128-bit multiplies and xor-shifts; pick by key size, trust level and whether the hash is persisted.
›
Sanitizers
security · low: ASan/UBSan/TSan shadow memory and instrumentation to catch memory bugs
Object storage
cloud · low: S3-compatible blob storage at cents per GB-month with 11 nines durability; pick by egress price, request price and latency, not by storage price alone.
›
Copy on write snapshots
storage · low: Point-in-time snapshots by sharing pages/extents and copying only on write
Failure bisection
search-sort · low: Binary search over commits, batches or inputs to isolate a failure
Delta encoding
compression · low: Store differences between consecutive values instead of the values, turning sorted IDs, timestamps and counters into small numbers that pack into few bits.
›
LZ77
compression · low: Replace repeated byte strings with (distance, length) back-references into a sliding window; the parsing stage of gzip, LZ4, zstd, Brotli and xz.
›
Rolling hash
data-structures · low: Rabin-Karp polynomial rolling hashes and winnowing for substring fingerprints and document matching
Suffix array
search-sort · low: Sorted array of all suffix start positions of a text; finds every occurrence of any substring by binary search, at 4-5 bytes per text byte.
›
Transparent interception
networking · low: Redirect traffic to a local proxy (iptables TPROXY/REDIRECT, eBPF) without app changes
Explicit Euler
numerics · low: Step an ODE forward by its current slope, y += h·f(t, y); first-order, one evaluation per step, the baseline every other integrator is measured against.
›
Finite differences
numerics · low: Replace derivatives with weighted differences of grid values; simple stencils plus a stability condition (CFL) turn PDEs like heat, advection and waves into array loops.
›
Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
Homogeneous transforms
geometry · low: 4x4 affine and projective matrices, homogeneous coordinates, view and projection, normal matrices
Lens distortion correction
graphics · low: Pre-warp rendered frames for headset optics: barrel distortion mesh and chromatic aberration
Deterministic serialization
finance · low: Canonical byte encodings (RLP, SSZ, canonical CBOR) so every node hashes identical bytes
Cryptographic hashes (SHA-2, BLAKE3)
security · low: Collision-resistant fingerprints of data; SHA-256 for interoperability, BLAKE3 for speed, HMAC/HKDF for keyed uses.
›
Digital signatures (Ed25519)
security · low: Small, fast, deterministic public-key signatures that prove who produced a message; the default for tokens, releases and protocols.
›
Newton root finding
numerics · low: Linearize at the guess and jump to the tangent root; quadratic convergence near a simple root, made robust by brackets (1D) or line search.
›
Secrets management
security · low: Keep keys and passwords out of code and logs, give workloads short-lived identity instead of static keys, and make rotation routine.
›
Cron scheduling
systems · low: Cron expression parsing and next-fire-time computation, with catch-up and time-zone rules
Ebpf
hardware-os · low: Verified in-kernel programs on hooks (kprobes, XDP, tc) with maps
Ptrace process control
hardware-os · low: Ptrace: attach, read and write registers and memory, single-step, intercept signals
Seccomp bpf
security · low: Syscall filtering with seccomp BPF programs
fsync, O_DSYNC and O_DIRECT
hardware-os · low: What fsync, fdatasync, O_DSYNC, O_DIRECT and F_FULLFSYNC really guarantee on Linux and macOS, and the exact call sequences for crash-safe files.
›
LRU and CLOCK
systems · low: LRU evicts the least recently used entry via hash map plus linked list; CLOCK approximates it with a reference bit, so hits take no lock.
›
S3-FIFO
systems · low: Three FIFO queues (small, main, ghost) that evict one-hit wonders quickly and keep reused objects; low miss ratios with no list moves on hits.
›
AEAD (AES-GCM, ChaCha20-Poly1305)
security · low: Authenticated encryption that encrypts and detects tampering in one call; the only kind of symmetric encryption you should use.
›
Aes key wrap
security · low: AES Key Wrap (RFC 3394/5649) and AES-GCM-SIV for deterministic, authenticated wrapping of key material
Csprng
security · low: OS-backed cryptographically secure random numbers (getrandom), and when a fast PRNG is not enough
d-ary heap
data-structures · low: Array heap with d children per node (d = 4 typical): half the binary heap's depth, siblings in one cache line, faster priority queues.
›
Control-flow graph
compilers · low: Split a linear instruction list into basic blocks and connect them by jumps; the graph every optimizer, SSA builder and dataflow pass walks.
›
Bit packing and PFOR
compression · low: Store blocks of integers with exactly b bits each and patch rare outliers separately (PFOR); the fastest integer codec family, billions of values per second.
›
Varint (LEB128)
compression · low: Variable-length integers in 7-bit groups with a continuation bit; small numbers take 1 byte, the wire format of Protobuf, WebAssembly and DWARF.
›
Fencing tokens
distributed · low: A number that grows with every lock grant and is checked by the protected resource, so a paused ex-holder's late write is rejected.
›
Dma transfers
embedded · low: DMA controllers: descriptors, circular buffers, cache coherence for zero-CPU data movement
Fixed timestep loop
graphics · low: Fixed simulation dt with accumulator, render interpolation, spiral-of-death guard
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Minimum spanning tree
graphs · low: Cheapest set of edges connecting all vertices; Kruskal sorts edges and joins components with union-find, Prim grows one tree, Boruvka merges in parallel rounds.
›
Union-find
graphs · low: Disjoint-set forest with union by size and path compression; merges sets and answers same-set queries in effectively constant time.
›
SIMD programming
hardware-os · low: Process 4-16 lanes per instruction with AVX2, AVX-512 or NEON via Rust std::arch, with runtime dispatch and a portable fallback.
›
Low precision number formats
numerics · low: Bf16, fp16, fp8 (E4M3, E5M2), MX block formats and int4: ranges, rounding, scaling
Semi-implicit Euler
numerics · low: Update velocity from forces first, then position with the new velocity: explicit Euler cost, but symplectic and stable; the default game-physics integrator.
›
Thomas tridiagonal solver
numerics · low: O(n) tridiagonal linear solve used in implicit finite-difference and spline schemes
Radix sort
search-sort · low: Non-comparison sort that distributes keys by 8-bit digits; several times faster than comparison sorts on large arrays of integers, floats or fixed-size keys.
›
Constant time code
security · low: Writing secret-dependent code without branches or memory lookups on secrets; constant-time compare and select
JSON Web Token (JWT)
security · low: A signed, URL-safe token carrying claims; the verifier's job is the checklist (pinned algorithm, key by kid, exp, aud, iss), not the format.
›
OAuth 2 and OpenID Connect
security · low: Delegated authorization (OAuth 2) and login on top of it (OIDC); use authorization code + PKCE for every user-facing client.
›
Copy for AI
Similar systems
Share the most building blocks with this one.
motor-drive
33 %
legged-control
31 %
infusion-pump
27 %
traffic-signal-control
26 %
robot-vacuum
24 %