TY - GEN
T1 - Modeling, design and control of low-cost differential-drive robotic ground vehicles
T2 - 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
AU - Rodriguez, Armando
AU - Puttannaiah, Karan
AU - Lin, Zhen Yu
AU - Aldaco, Jesus
AU - Li, Zhichao
AU - Lu, Xianglong
AU - Mondal, Kaustav
AU - Sonawani, Shubham D.
AU - Ravishankar, Nikhilesh
AU - Das, Nirangkush
AU - Pradhan, Pragyan A.
N1 - Funding Information:
Dr.A.A.Rodriguez is a Prof. in School of Elect., Computer & Energy Eng. (ECEE), Arizona State University (ASU), Tempe, AZ, aar@asu.edu; K.Puttannaiah, K.Mondal are Ph.D. students in ECEE, ASU; S.D.Sonawani, N.Ravishankar, N.Das, P.A.Pradhan are MS students in ECEE, ASU; Z.Lin is Ph.D student in Dept. of Elect. Eng., Univ. Maryland; J.Aldaco is with Delphi, IN. Z.Li is a Ph.D. student in Mech. & Aerospace Eng., Univ. of California, San Diego; X.Lu is with Changan US R&D Center, MI. This work has been supported, in part, by NSF Grant No. 1565177. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the NSF.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/6
Y1 - 2017/10/6
N2 - Toward the ambitious long-term goal of a fleet of cooperating Flexible Autonomous Machines operating in an uncertain Environment (FAME), this two part paper addresses several critical modeling, design and control objectives for ground vehicles. Within Part I of this paper, a low-cost differential drive robotic vehicle was introduced for FAME research. Suitable nonlinear/linear-models were used to develop inner/outer-loop control laws for a single vehicle; e.g. wheel (and vehicle translational/rotational) velocity inner-loop control, etc. Part II of this paper focusses on the coordination of multiple vehicles. The (faster) inner-loop control law discussed within Part I is used for all (slower) outer-loop control modes demonstrated within Part II. We specifically demonstrate (via simulations and hardware) the following specific outer-loop control laws: (1) Δx-θ separation-direction control, (2) collision avoidance, (3) separation control for a longitudinal platoon of vehicles. Empirically collected data is shown to agree well with simulation results. Reasons for observed differences are provided. The simple separation-direction control structure is adequate because of the (higher bandwidth) inner-loop control law. We observed (and expected) that (1) collision avoidance works well as long as the controlled vehicle is not traveling too fast with respect to obstacles. (2) with respect to platoon control, we demonstrated that feedforward of leader speed information significantly and uniformly improves separation performance as we move rearward in the platoon. In short, many capabilities that are critical for reaching the longer-term FAME goal are demonstrated within this two part paper.
AB - Toward the ambitious long-term goal of a fleet of cooperating Flexible Autonomous Machines operating in an uncertain Environment (FAME), this two part paper addresses several critical modeling, design and control objectives for ground vehicles. Within Part I of this paper, a low-cost differential drive robotic vehicle was introduced for FAME research. Suitable nonlinear/linear-models were used to develop inner/outer-loop control laws for a single vehicle; e.g. wheel (and vehicle translational/rotational) velocity inner-loop control, etc. Part II of this paper focusses on the coordination of multiple vehicles. The (faster) inner-loop control law discussed within Part I is used for all (slower) outer-loop control modes demonstrated within Part II. We specifically demonstrate (via simulations and hardware) the following specific outer-loop control laws: (1) Δx-θ separation-direction control, (2) collision avoidance, (3) separation control for a longitudinal platoon of vehicles. Empirically collected data is shown to agree well with simulation results. Reasons for observed differences are provided. The simple separation-direction control structure is adequate because of the (higher bandwidth) inner-loop control law. We observed (and expected) that (1) collision avoidance works well as long as the controlled vehicle is not traveling too fast with respect to obstacles. (2) with respect to platoon control, we demonstrated that feedforward of leader speed information significantly and uniformly improves separation performance as we move rearward in the platoon. In short, many capabilities that are critical for reaching the longer-term FAME goal are demonstrated within this two part paper.
UR - http://www.scopus.com/inward/record.url?scp=85047618100&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85047618100&partnerID=8YFLogxK
U2 - 10.1109/CCTA.2017.8062457
DO - 10.1109/CCTA.2017.8062457
M3 - Conference contribution
AN - SCOPUS:85047618100
T3 - 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
SP - 161
EP - 166
BT - 1st Annual IEEE Conference on Control Technology and Applications, CCTA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 August 2017 through 30 August 2017
ER -