TY - CHAP
T1 - Motion Planning Using MoDs
AU - Kucner, Tomasz Piotr
AU - Lilienthal, Achim J.
AU - Magnusson, Martin
AU - Palmieri, Luigi
AU - Srinivas Swaminathan, Chittaranjan
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Maps of dynamics can be beneficial for motion planning. Information about motion patterns in the environment can lead to finding flow-aware paths, allowing robots to align better to the expected motion: either of other agents in the environment or the flow of air or another medium. The key idea of flow-aware motion planning is to include adherence to the flow represented in the MoD into the motion planning algorithm’s sub-units (i.e. cost function, sampling mechanism), thereby biasing the motion planner into obeying local and implicit traffic rules.
AB - Maps of dynamics can be beneficial for motion planning. Information about motion patterns in the environment can lead to finding flow-aware paths, allowing robots to align better to the expected motion: either of other agents in the environment or the flow of air or another medium. The key idea of flow-aware motion planning is to include adherence to the flow represented in the MoD into the motion planning algorithm’s sub-units (i.e. cost function, sampling mechanism), thereby biasing the motion planner into obeying local and implicit traffic rules.
UR - https://www.scopus.com/pages/publications/85083963960
U2 - 10.1007/978-3-030-41808-3_5
DO - 10.1007/978-3-030-41808-3_5
M3 - Chapter
AN - SCOPUS:85083963960
T3 - Cognitive Systems Monographs
SP - 115
EP - 141
BT - Cognitive Systems Monographs
PB - Springer
ER -