Intel RealSense D435i
The default depth camera for manipulation research. Active IR stereo, 90° × 87° field of view (wide enough for a gripper's working volume), plus an IMU for VIO.
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: Grasp pose estimation, VIO, obstacle avoidance, AR.
What the numbers actually mean
The headline figure is 0.3 – 3 m (optimal), up to ~10 m (depth range), with 87° × 58° as the next most load-bearing number (depth fov). At $350 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 D435iStereo depth camera + IMU | $350 | 0.3 – 3 m (optimal), up to ~10 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
Platforms in this atlas that use something in this class: ALOHA 2, Universal Robots UR5e, Agility Digit.