TY - JOUR
T1 - Motivation Dynamics for Autonomous Composition of Navigation tasks
AU - Reverdy, Paul B.
AU - Vasilopoulos, Vasileios
AU - Koditschek, Daniel E.
N1 - Funding Information:
Manuscript received June 1, 2020; revised October 5, 2020; accepted November 2, 2020. Date of publication March 17, 2021; date of current version August 5, 2021. This work was funded in part by the Air Force Research Laboratory under Grant FA8650-15-D-1845 (subcontracts 669 737-1 and 669 737-6). Support was also provided by Ghost Robotics. This article was recommended for publication by Associate Editor R. Vasudevan and Editor P. Robuffo Giordano upon evaluation of the reviewers’ comments. (Corresponding author: Paul B. Reverdy.) Paul B. Reverdy is with the Department of Aerospace and Mechanical Engineering, The University of Arizona, Tucson, AZ 85721 USA, and also with Amazon, Seattle, WA 98109 USA. This work was performed before P. Reverdy joined Amazon. (e-mail: preverdy@arizona.edu).
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2021/8
Y1 - 2021/8
N2 - In this article, we physically demonstrate a reactive sensorimotor architecture for mobile robots whose behaviors are generated by motivation dynamics. Motivation dynamics uses a continuous dynamical system to reactively compose low-level control vector fields using valuation functions that capture the potentially competing influences of external stimuli relative to the system's own internal state. We show that motivation dynamics naturally accommodates external stimuli through standard signal processing tools, and can effectively encode a repetitive higher level task by composing several low-level controllers to achieve a limit cycle in which the robot repeatedly navigates toward two alternatively valuable goal locations in a commensurately alternating order. We show that these behaviors are robust to perturbations, including imperfect models of robot kinematics, sensor noise, and disturbances, resulting from the need to traverse difficult terrain. We argue that motivation dynamics can provide a useful alternative to controllers based on hybrid automata in situations where the control operates at a low level close to the physical hardware.
AB - In this article, we physically demonstrate a reactive sensorimotor architecture for mobile robots whose behaviors are generated by motivation dynamics. Motivation dynamics uses a continuous dynamical system to reactively compose low-level control vector fields using valuation functions that capture the potentially competing influences of external stimuli relative to the system's own internal state. We show that motivation dynamics naturally accommodates external stimuli through standard signal processing tools, and can effectively encode a repetitive higher level task by composing several low-level controllers to achieve a limit cycle in which the robot repeatedly navigates toward two alternatively valuable goal locations in a commensurately alternating order. We show that these behaviors are robust to perturbations, including imperfect models of robot kinematics, sensor noise, and disturbances, resulting from the need to traverse difficult terrain. We argue that motivation dynamics can provide a useful alternative to controllers based on hybrid automata in situations where the control operates at a low level close to the physical hardware.
KW - Autonomous systems
KW - nonlinear control systems
KW - nonlinear dynamical systems
KW - path planning
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U2 - 10.1109/TRO.2020.3043720
DO - 10.1109/TRO.2020.3043720
M3 - Article
AN - SCOPUS:85103155325
VL - 37
SP - 1239
EP - 1251
JO - IEEE Transactions on Robotics
JF - IEEE Transactions on Robotics
SN - 1552-3098
IS - 4
M1 - 9380469
ER -