Intel RealSense D405
Purpose-built for the last 7 cm to 50 cm — exactly the range where a robot hand actually operates. Higher depth accuracy than the D435i at that distance.
The role it plays
Sensors split into proprioception — encoders, IMUs, joint torque, motor current — which tells the robot about itself, and exteroception — LiDAR, depth, force, GNSS — which tells it about the world. Build proprioception first. A robot that does not know where its own joints are cannot use a good world model anyway.
Typical use: In-hand cameras, close grasping, inspection.
What the numbers actually mean
The headline figure is 0.07 – 0.5 m (ideal 0.07 – 0.2 m) (depth range), with 87° × 58° as the next most load-bearing number (depth fov). At $300 in the sensors tier it sits as a capital purchase. At this price you are buying documentation, repeatability and support as much as metal, and the integration cost is usually larger than the part.
How it compares
Same subsystem, closest alternatives. The primary spec column is usually the one that decides it.
| Part | Price | Primary spec | Second spec |
|---|---|---|---|
| Intel RealSense D405Short-range depth camera | $300 | 0.07 – 0.5 m (ideal 0.07 – 0.2 m) | 87° × 58° |
| AS5600 magnetic encoderAbsolute rotary encoder | $3 | 12-bit (4096 counts/rev) | I²C (also analog / PWM out) |
| AS5047P magnetic encoderAbsolute rotary encoder | $10 | 14-bit (16384 counts/rev) | SPI + ABI quadrature + UVW |
| CUI AMT102-VCapacitive incremental encoder | $25 | up to 2048 PPR (configurable) | Quadrature A/B/Z |
| BNO085 9-DOF IMUIMU with onboard fusion | $25 | 3-axis accel + gyro + magnetometer | Quaternion / Euler / rotation vector, plus raw |
Where it shows up
It is a component-level choice rather than a defining part of a named platform — pick it for the subsystem it serves, not to match a reference build.