Bilateral Teleoperation of Multiple Mobile Agents: Coordinated Motion and Collision Avoidance

By Erick J. Rodríguez-Seda, James J. Troy, Charles A. Erignac, P. Murray, Dusan M. Stipanovic, Mark W. Spong. 2010

156 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Mechanical Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Wenwu Yu
2. Guanrong Chen
3. Wei Ren
4. Yongcan Cao
5. Frank L. Lewis
6. Jinde Cao
7. Z. Duan
8. Guanghui Wen

In Control and Systems Engineering

1. Guanrong Chen
2. Wenwu Yu
3. Yongcan Cao
4. Wei Ren
5. Michael Lewis
6. Nilanjan Chakraborty
7. Andreas Kolling
8. Phillip M. Walker

In Mechanical Engineering

1. Michael Lewis
2. Guanrong Chen
3. Nilanjan Chakraborty
4. Wei Ren
5. Andreas Kolling
6. Phillip M. Walker
7. Wenwu Yu
8. Yongcan Cao

Citations in the corpus

• An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination (2012, background): “2, where d ij denotes the desired distance between agents i and j. Briefly, the nonlinear systems studied in this case include nonholonomic mobile robots (see (6)) [221]– [225], rigid bodies (see (7)) [226], [227], and linear systems 11 with nonlinear terms [219], [220]. Compared with the flocking pro”
• Human Interaction With Robot Swarms: A Survey (2016, background): “Control complexity is reduced by controlling leaders that influence the swarm; key questions are the selection of leaders and propagation of influence; a comparison between strong or weak influence is found in [118]; algorithmic dynamic selection of leaders improves control over the swarm [120], [11”