TY - JOUR
T1 - Frugal random exploration strategy for shape recognition using statistical geometry
AU - Hidalgo-Caballero, Samuel
AU - Cassinelli, Alvaro
AU - Fort, Emmanuel
AU - Labousse, Matthieu
PY - 2024/4
Y1 - 2024/4
N2 - Very distinct strategies can be deployed to recognize and characterize an unknown environment or a shape. A recent and promising approach, especially in robotics, is to reduce the complexity of the exploratory units to a minimum. Here, we show that this frugal strategy can be taken to the extreme by exploiting the power of statistical geometry and introducing different invariant features. We show that an elementary robot devoid of any orientation or location system, exploring randomly, can access global information about an environment such as the values of the explored area and perimeter. The explored shapes are of arbitrary geometry and may even nonconnected. From a dictionary, this most simple robot can thus identify various shapes such as famous monuments and even read a text. © 2024 American Physical Society.
AB - Very distinct strategies can be deployed to recognize and characterize an unknown environment or a shape. A recent and promising approach, especially in robotics, is to reduce the complexity of the exploratory units to a minimum. Here, we show that this frugal strategy can be taken to the extreme by exploiting the power of statistical geometry and introducing different invariant features. We show that an elementary robot devoid of any orientation or location system, exploring randomly, can access global information about an environment such as the values of the explored area and perimeter. The explored shapes are of arbitrary geometry and may even nonconnected. From a dictionary, this most simple robot can thus identify various shapes such as famous monuments and even read a text. © 2024 American Physical Society.
U2 - 10.1103/PhysRevResearch.6.023103
DO - 10.1103/PhysRevResearch.6.023103
M3 - RGC 21 - Publication in refereed journal
VL - 6
JO - Physical Review Research
JF - Physical Review Research
SN - 2643-1564
IS - 2
M1 - 023103
ER -