Humanoid robot sensing

Infineon humanoid robot sensors help robots see, hear, detect, and respond to dynamic surroundings with 3D vision, radar, sound, and pressure sensing

Overview

Humanoid robots must understand objects, people, spaces and changing conditions to operate safely and effectively in human environments. Infineon sensing solutions combine ToF, radar, MEMS microphones, pressure sensors, and embedded processing to support robot vision, collision avoidance, natural interaction, indoor navigation awareness, sensor fusion, and Vision-Language-Action applications for physical AI designs.

Benefits

  • See in 3D
  • Avoid collisions
  • Operate in darkness
  • Hear surroundings
  • Detect nearby people
  • Fuse sensor data

About

Give humanoid robots reliable 3D object vision with Infineon REAL3™ Time-of-Flight sensing. Dense 3D depth data helps robots recognize objects, estimate distance and shape, and support precise gripping or placement tasks. It can also complement Vision-Language-Action (VLA) models with depth context for objects, distances and surroundings.

For small-object handling, there is a need for high-density 3D information on objects smaller than 1 x 1 x 1 cm within about 1 m, enabled by the REAL3™ VGA iToF IRS2976C sensor with 640 x 480 depth data. Time-of-Flight also supports dark operation and can complement RGB or stereo vision through sensor fusion.

Relevant Infineon technologies include:

  • REAL3™ VGA iToF sensors like IRS2976C - captures dense 3D depth data for object detection and precise handling
  • IRS2976C-based ToF camera modules - speed evaluation and reduce integration effort
  • Dense 3D scene data - helps complement VLA models with depth context
  • IR data and point-cloud output - combines depth and image information for robust perception
  • Sensor fusion with RGB or stereo vision - improves performance across varied lighting and objects

Support collision avoidance and environmental sensing in crowded places, narrow aisles and changing indoor environments. Infineon REAL3™ iToF cameras provide high-density 3D information, fast depth updates such as 30 fps, and accurate depth data for objects and obstacles.

This helps humanoid robots detect people, furniture, objects and open paths while operating with compact, low-power camera modules. REAL3™ hybrid Time-of-Flight can combine high-resolution flood illumination for obstacle avoidance with precise spot illumination for SLAM and 3D mapping.

Relevant Infineon technologies include:

  • REAL3™ iToF cameras - help humanoid robots detect obstacles and navigate dynamic indoor environments
  • REAL3™ hybrid Time-of-Flight - combine obstacle avoidance and mapping functions in a compact sensing approach
  • Flood illumination for obstacle avoidance - helps detect nearby objects with high lateral resolution
  • Spot illumination for SLAM and mapping - helps generate precise long-distance 3D point-cloud data for navigation
  • Compact low-power ToF camera modules - help reduce space, heat and power challenges in humanoid robot designs

Enable humanoid robots to hear and localize their surroundings with Infineon XENSIV™ MEMS microphones. High-performance microphones support environmental awareness, speaker identification and source localization, helping robots respond more naturally to voice and acoustic events.

In sensor fusion for humanoid robot designs, audio can complement robot vision, radar and pressure sensing to improve interaction quality and situational awareness in dynamic environments.

Relevant Infineon technologies include:

  • XENSIV™ MEMS microphones - help robots capture voice and environmental sound with high audio quality
  • Environmental awareness - helps robots detect acoustic events and respond to changes in their surroundings
  • Speaker identification - helps support more natural human-robot interaction in shared spaces
  • Source localization - helps robots determine where a voice or sound is coming from
  • Audio sensing for interaction - helps complement visual sensing when robots need to perceive people and activity around them

Add pressure sensing to support floor-level detection, fall detection and environmental awareness in humanoid robots. Barometric pressure sensors can help robots support indoor navigation by detecting position changes within a building through air-pressure differences.

Sudden pressure jumps can indicate a fall event, while pressure sensors placed across the robot can provide additional environmental context alongside joint position data, robot vision and other sensor inputs. This makes pressure sensing a useful part of sensor fusion for humanoid robot designs operating in multi-level indoor environments.

Relevant Infineon technologies include:

  • XENSIV™ barometric pressure sensors - add altitude and pressure awareness in compact robot systems
  • Floor-level detection - helps robots recognize vertical position changes in multi-level buildings
  • Fall detection - helps identify sudden pressure changes that may indicate a fall event
  • Indoor navigation support - complements visual and motion sensing indoors
  • Pressure-based environmental awareness - adds a sensing layer beyond cameras and radar
  • Sensor fusion support - combines pressure data with vision, radar and motion information

Use Infineon XENSIV™ radar sensing to detect presence, movement, and approaching people or objects. Radar can support collision avoidance, virtual fencing, and wake-up functions by helping a humanoid robot detect when a person enters a defined perimeter or approaches the system. For example, Infineon's 60GHz BGT60CUTR13AIP CMOS radar solution with multiple-target detection, pre-processed data via SPI, integrated hardware acceleration, and long-range presence detectionm, is a perfect fit.

Relevant Infineon technologies include:

  • XENSIV™ radar sensing - helps robots detect presence and movement even when visual sensing is limited
  • XENSIV™ BGT60CUTR13AIP - helps designers add compact 60 GHz radar sensing with integrated processing
  • Presence detection - helps robots identify when people or objects are nearby
  • Virtual fencing - helps define safety or interaction zones around the robot
  • Wake-up on approach - helps reduce power consumption by activating functions only when needed
  • Collision avoidance - helps complement 3D vision with another sensing modality for obstacle detection

Humanoid robots need to combine multiple sensing inputs to understand complex, changing environments. Vision, radar, sound and pressure data each provide different information about the robot's surroundings. Sensor fusion helps bring these inputs together so the robot can interpret objects, people, movement, sound direction and position changes more reliably.

For designers, sensor fusion can help improve perception robustness, reduce blind spots and support more responsive robot behavior. By combining complementary Infineon sensing technologies with embedded processing, humanoid robots can move from single-sensor detection toward richer environmental awareness.

Relevant Infineon technologies include:

  • Time-of-Flight sensing - provides dense 3D depth data for object detection and navigation
  • Radar sensing - detects presence and movement as an added awareness layer
  • MEMS microphones - localize sound and support more natural interaction
  • Barometric pressure sensing - adds floor-level and fall-detection context
  • Embedded processing - combines sensor inputs closer to the robot system
  • Multi-sensor system design - improves robustness by reducing reliance on one modality

Give humanoid robots reliable 3D object vision with Infineon REAL3™ Time-of-Flight sensing. Dense 3D depth data helps robots recognize objects, estimate distance and shape, and support precise gripping or placement tasks. It can also complement Vision-Language-Action (VLA) models with depth context for objects, distances and surroundings.

For small-object handling, there is a need for high-density 3D information on objects smaller than 1 x 1 x 1 cm within about 1 m, enabled by the REAL3™ VGA iToF IRS2976C sensor with 640 x 480 depth data. Time-of-Flight also supports dark operation and can complement RGB or stereo vision through sensor fusion.

Relevant Infineon technologies include:

  • REAL3™ VGA iToF sensors like IRS2976C - captures dense 3D depth data for object detection and precise handling
  • IRS2976C-based ToF camera modules - speed evaluation and reduce integration effort
  • Dense 3D scene data - helps complement VLA models with depth context
  • IR data and point-cloud output - combines depth and image information for robust perception
  • Sensor fusion with RGB or stereo vision - improves performance across varied lighting and objects

Support collision avoidance and environmental sensing in crowded places, narrow aisles and changing indoor environments. Infineon REAL3™ iToF cameras provide high-density 3D information, fast depth updates such as 30 fps, and accurate depth data for objects and obstacles.

This helps humanoid robots detect people, furniture, objects and open paths while operating with compact, low-power camera modules. REAL3™ hybrid Time-of-Flight can combine high-resolution flood illumination for obstacle avoidance with precise spot illumination for SLAM and 3D mapping.

Relevant Infineon technologies include:

  • REAL3™ iToF cameras - help humanoid robots detect obstacles and navigate dynamic indoor environments
  • REAL3™ hybrid Time-of-Flight - combine obstacle avoidance and mapping functions in a compact sensing approach
  • Flood illumination for obstacle avoidance - helps detect nearby objects with high lateral resolution
  • Spot illumination for SLAM and mapping - helps generate precise long-distance 3D point-cloud data for navigation
  • Compact low-power ToF camera modules - help reduce space, heat and power challenges in humanoid robot designs

Enable humanoid robots to hear and localize their surroundings with Infineon XENSIV™ MEMS microphones. High-performance microphones support environmental awareness, speaker identification and source localization, helping robots respond more naturally to voice and acoustic events.

In sensor fusion for humanoid robot designs, audio can complement robot vision, radar and pressure sensing to improve interaction quality and situational awareness in dynamic environments.

Relevant Infineon technologies include:

  • XENSIV™ MEMS microphones - help robots capture voice and environmental sound with high audio quality
  • Environmental awareness - helps robots detect acoustic events and respond to changes in their surroundings
  • Speaker identification - helps support more natural human-robot interaction in shared spaces
  • Source localization - helps robots determine where a voice or sound is coming from
  • Audio sensing for interaction - helps complement visual sensing when robots need to perceive people and activity around them

Add pressure sensing to support floor-level detection, fall detection and environmental awareness in humanoid robots. Barometric pressure sensors can help robots support indoor navigation by detecting position changes within a building through air-pressure differences.

Sudden pressure jumps can indicate a fall event, while pressure sensors placed across the robot can provide additional environmental context alongside joint position data, robot vision and other sensor inputs. This makes pressure sensing a useful part of sensor fusion for humanoid robot designs operating in multi-level indoor environments.

Relevant Infineon technologies include:

  • XENSIV™ barometric pressure sensors - add altitude and pressure awareness in compact robot systems
  • Floor-level detection - helps robots recognize vertical position changes in multi-level buildings
  • Fall detection - helps identify sudden pressure changes that may indicate a fall event
  • Indoor navigation support - complements visual and motion sensing indoors
  • Pressure-based environmental awareness - adds a sensing layer beyond cameras and radar
  • Sensor fusion support - combines pressure data with vision, radar and motion information

Use Infineon XENSIV™ radar sensing to detect presence, movement, and approaching people or objects. Radar can support collision avoidance, virtual fencing, and wake-up functions by helping a humanoid robot detect when a person enters a defined perimeter or approaches the system. For example, Infineon's 60GHz BGT60CUTR13AIP CMOS radar solution with multiple-target detection, pre-processed data via SPI, integrated hardware acceleration, and long-range presence detectionm, is a perfect fit.

Relevant Infineon technologies include:

  • XENSIV™ radar sensing - helps robots detect presence and movement even when visual sensing is limited
  • XENSIV™ BGT60CUTR13AIP - helps designers add compact 60 GHz radar sensing with integrated processing
  • Presence detection - helps robots identify when people or objects are nearby
  • Virtual fencing - helps define safety or interaction zones around the robot
  • Wake-up on approach - helps reduce power consumption by activating functions only when needed
  • Collision avoidance - helps complement 3D vision with another sensing modality for obstacle detection

Humanoid robots need to combine multiple sensing inputs to understand complex, changing environments. Vision, radar, sound and pressure data each provide different information about the robot's surroundings. Sensor fusion helps bring these inputs together so the robot can interpret objects, people, movement, sound direction and position changes more reliably.

For designers, sensor fusion can help improve perception robustness, reduce blind spots and support more responsive robot behavior. By combining complementary Infineon sensing technologies with embedded processing, humanoid robots can move from single-sensor detection toward richer environmental awareness.

Relevant Infineon technologies include:

  • Time-of-Flight sensing - provides dense 3D depth data for object detection and navigation
  • Radar sensing - detects presence and movement as an added awareness layer
  • MEMS microphones - localize sound and support more natural interaction
  • Barometric pressure sensing - adds floor-level and fall-detection context
  • Embedded processing - combines sensor inputs closer to the robot system
  • Multi-sensor system design - improves robustness by reducing reliance on one modality
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