Visual-Inertial Odometry vs SLAM
Compare visual-inertial odometry and SLAM by state, map, drift, loop closure, relocalization, calibration, frames and robot validation.
English articles about robot data and hardware at Physical AI Lab.
Compare visual-inertial odometry and SLAM by state, map, drift, loop closure, relocalization, calibration, frames and robot validation.
Compare 2D and 3D LiDAR for AMRs by scan geometry, localization, obstacle height, point density, timing, compute, environment and safety tests.
Calibrate robot IMU bias, drift, scale, alignment, temperature, vibration and timing, then validate covariance and mission residuals.
Compare robot event and frame cameras by signal, latency, motion blur, dynamic range, static detail, bandwidth, synchronization and task tests.
Estimate robot joint torque from motor current using calibrated torque constant, gearbox efficiency, dynamics, friction, residuals and load-cell tests.
Design robot dual-encoder feedback with motor and load sensors, ratio, zero, timing, backlash, compliance, nested loops and fault tests.
Design robot regenerative braking with DC-link energy, battery charge limits, shared axes, brake resistors, choppers, overvoltage and fault tests.
Design robot cable harnesses for flex, torsion, strain relief, shielding, grounding, EMI, signal integrity, heat and motion-cycle tests.
Estimate robot battery SoC and SoH using current integration, OCV correction, capacity, resistance, cell imbalance and mission runtime tests.
Select a robot DC bus across 24 V, 48 V and higher options using current, wiring, motor speed, regeneration, component and safety limits.