TY - GEN
T1 - Hierarchical Behaviour for Object Shape Recognition Using a Swarm of Robots
AU - Rubio-Solis, Adrian
AU - Martinez-Hernandez, Uriel
PY - 2019/7/6
Y1 - 2019/7/6
N2 - A hierarchical cognitive architecture for robot exploration and recognition of object shape is presented. This cognitive architecture proposes the combination of multiple robot behaviours based on (1) Evolutionary, (2) Fuzzy Logic and (3) Bayesian approaches. First, the Evolutionary approach allows a swarm of robots to locate and reach an object for exploration. Second, Fuzzy Logic is used to control the exploration of the object shape. Third, the Bayesian approach allows the robot to detect the orientation of the walls of the object being explored. Once the exploration process finishes, the swarm of robots determine whether the object has a rectangular or circular shape. This work is validated in a simulated environment and MATLAB using a swarm of E-puck robots. Overall, the experiments demonstrate that simple robots are capable of performing complex tasks through the combination of simple collective behaviours while learning from the interaction with the environment.
AB - A hierarchical cognitive architecture for robot exploration and recognition of object shape is presented. This cognitive architecture proposes the combination of multiple robot behaviours based on (1) Evolutionary, (2) Fuzzy Logic and (3) Bayesian approaches. First, the Evolutionary approach allows a swarm of robots to locate and reach an object for exploration. Second, Fuzzy Logic is used to control the exploration of the object shape. Third, the Bayesian approach allows the robot to detect the orientation of the walls of the object being explored. Once the exploration process finishes, the swarm of robots determine whether the object has a rectangular or circular shape. This work is validated in a simulated environment and MATLAB using a swarm of E-puck robots. Overall, the experiments demonstrate that simple robots are capable of performing complex tasks through the combination of simple collective behaviours while learning from the interaction with the environment.
KW - Bayesian perception
KW - Hierarchical control
KW - Swarm robotics
UR - http://www.scopus.com/inward/record.url?scp=85069528069&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-24741-6_37
DO - 10.1007/978-3-030-24741-6_37
M3 - Chapter in a published conference proceeding
AN - SCOPUS:85069528069
SN - 9783030247409
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 355
EP - 359
BT - Biomimetic and Biohybrid Systems. Living Machines 2019
A2 - Martinez-Hernandez, Uriel
A2 - Vouloutsi, Vasiliki
A2 - Mura, Anna
A2 - Mangan, Michael
A2 - Prescott, Tony J.
A2 - Asada, Minoru
A2 - Verschure, Paul F.M.J.
PB - Springer Verlag
CY - Cham, Switzerland
T2 - 8th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2019
Y2 - 9 July 2019 through 12 July 2019
ER -