Robust Distributed Planar Formation Control for Higher Order Holonomic and Nonholonomic Agents

被引:23
作者
Fathian, Kaveh [1 ]
Safaoui, Sleiman [2 ]
Summers, Tyler H. [3 ]
Gans, Nicholas R. [4 ]
机构
[1] MIT, Dept Aeronaut & Astronaut, Cambridge, MA 02139 USA
[2] Univ Texas Dallas, Dept Elect Engn, Richardson, TX 75080 USA
[3] Univ Texas Dallas, Dept Mech Engn, Richardson, TX 75080 USA
[4] Univ Texas Arlington, UT Arlington Res Inst, Arlington, TX 76118 USA
关键词
Collision avoidance; Convergence; Robustness; Robot sensing systems; Robot kinematics; Automobiles; Distributed collision avoidance; distributed robotic platform; formation control; multiagent systems; RIGID FORMATIONS; MOBILE AGENTS; STABILIZATION;
D O I
10.1109/TRO.2020.3014022
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In this article, we present a distributed formation control strategy for agents with a variety of dynamics to achieve a desired planar formation. Our approach is based on the barycentric-coordinate-based (BCB) control, which is fully distributed, does not require interagent communication or a common sense of orientation, and can be implemented using relative position measurements acquired by agents in their local coordinate frames. This removes the need for global positioning or alignment of local coordinate frames, which are required across several existing strategies. We show how the BCB control for agents with the simplest dynamical model, i.e., the single-integrator dynamics, can be extended to agents with higher order dynamics such as quadrotors, and nonholonomic agents such as unicycles and cars. Specifically, our extension preserves the desired convergence and robustness guarantees of the BCB approach and is provably robust to saturations in the input and unmodeled linear actuator dynamics for unicycle and car agents. We further show that under our proposed BCB control design, the agents can move along a rotated and scaled control direction without affecting the convergence to the desired formation. This observation is used to design a fully distributed collision avoidance strategy, which is often not considered in the formation control literature. We demonstrate the proposed approach in simulations and further present a distributed robotic platform to test the strategy experimentally. Our experimental platform consists of off-the-shelf equipment that can be used to test and validate other multiagent algorithms. The code and implementation instructions for this platform are available online.
引用
收藏
页码:185 / 205
页数:21
相关论文
共 57 条
[1]  
Bähnemann R, 2017, 2017 IEEE INTERNATIONAL SYMPOSIUM ON SAFETY, SECURITY AND RESCUE ROBOTICS (SSRR), P123, DOI 10.1109/SSRR.2017.8088150
[2]   Swarm robotics reviewed [J].
Barca, Jan Carlo ;
Sekercioglu, Y. Ahmet .
ROBOTICA, 2013, 31 :345-359
[3]   Distributed control of triangular formations with angle-only constraints [J].
Basiri, Meysam ;
Bishop, Adrian N. ;
Jensfelt, Patric .
SYSTEMS & CONTROL LETTERS, 2010, 59 (02) :147-154
[4]   Distributed formation control with relaxed motion requirements [J].
Bishop, Adrian N. ;
Deghat, Mohammad ;
Anderson, Brian D. O. ;
Hong, Yiguang .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2015, 25 (17) :3210-3230
[5]  
Bishop AN, 2013, IEEE INTL CONF CONTR, P1194, DOI 10.1109/CCA.2013.6662914
[6]   Distributed optimization and statistical learning via the alternating direction method of multipliers [J].
Boyd S. ;
Parikh N. ;
Chu E. ;
Peleato B. ;
Eckstein J. .
Foundations and Trends in Machine Learning, 2010, 3 (01) :1-122
[7]  
Boyd S., 2006, Proc. International Congress of Mathematicians, V3, P1311
[8]  
Corke P., 2017, Robotics, Vision and Control, V118
[9]  
De Luca A., 1998, Robot motion planning and control, P171, DOI 10.1007/BFb0036073
[10]   Distributed algorithm for controlling scale-free polygonal formations. [J].
de Marina, Hector Garcia ;
Jayawardhana, Bayu ;
Cao, Ming .
IFAC PAPERSONLINE, 2017, 50 (01) :1760-1765