Perception sensors play a key role
in AMRs, enabling them to navigate
complex environments with precision
and safety. The integration of
diverse sensors such as LiDAR,
radar, and cameras—each with
unique strengths and limitations—
demands sophisticated sensor
fusion to ensure reliable real-time
decision-making."
Preeti Udapudi
Systems Engineer, Robotics,
Texas Instruments
C h a p t e r 1 | S u b s y s t e m s o f a n A M R
classification, they are less reliable for precise depth
measurement compared to LiDAR and radar.
Because each sensor type has strengths and
weaknesses, AMRs use sensor fusion to combine
data from multiple sources and create a more reliable
understanding of their environment. However, sensor
fusion presents several design challenges:
• Data Synchronization: Each sensor operates
at a different frame rate, resolution, and latency.
Misalignment between sensor inputs can lead to
perception errors.
• Dynamic Environments: AMRs must navigate
unstructured environments where objects move
unpredictably. Ensuring robust perception and
obstacle avoidance is critical for safe operation.
• Computational Load: Processing multiple sensor
inputs in real time requires high-performance
computing. AMRs must strike a balance between
sensor accuracy and processing efficiency to avoid
delays in decision-making.
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13 Experts Discuss Autonomous Mobile Robots
