How to build a humoid robot
by dtsn
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Popularised by 20th century fiction (iRobot, 2001, Dr Who)
Surprised to hear that the first humanoid was created over 500 years ago
Design in 1495
Concept has been around for a long time
But why haven’t we got further
They are complicated ....
Hardware architecture, things like walking, hands, sight
But first ....
Software architecture, software behind the robot (AI?)
Hardware architecture, things like walking, hands, sight
But first ....
Software architecture, software behind the robot (AI?)
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Decision layer, higher level processing (split in sub components)
Reactive layer, for fast quick responses (mimics the spinal cord)
- Sub processors embedded into key systems like hands accelerometers etc.
- Great example of the reactive layer is the Song QRIO
Built Jan 2006, as a replacement to the popular AIBO
Can detect being off balance and moves arms to compensate, protecting the body when it falls
So lets talk about hardware, first walking
Lives in our world needs to interaction, walk up stairs open doors etc.
Walking quite a simple problem, but difficult to solve
Attempt to mimic the human gait
Guarantee the stability of the robot while it remains in the polygon of support
However knees are require to be bent to avoid singularity in knee joint
Therefore uses 4 times the amount of power
ASMIO great example, 3 joints per leg, 6 DOF
Arms - Need high DOF to reach out and twist
Hand - miniature servos, feedback wrists
Feet - Provide feedback, bigger they are the more stable the robot is
Provides Stereoscopic vision, and by turning head we can build up a 3D map of environment
With 3D environment we can use path planning to navigate
Image recognition
2 microphones either side of the head, localisation