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ICRA 2006

Towards Robust Multi-robot Formations

Conference Paper Robotic Formations Artificial Intelligence · Robotics

Abstract

Robots in formations move while maintaining a predefined geometric shape. Previous work has examined formation-maintenance algorithms that would ensure the stability of the formation. However, for each geometric formation, an exponential number of stable controllers exists. Thus a key question is how to select (construct) a formation controller that optimizes desired properties, such as sensor usage for robustness. This paper presents a monitoring multi-graph framework for formation controller selection, based on sensor-morphology considerations. We instantiate the framework, and present two contributions. First, we show that graph-theoretic techniques can then be used to compute sensing policies that maintain a given formation. In particular, sensor-based control laws for separation-bearing (distance-angle) formation control can be automatically constructed. Second, we present a protocol allowing controllers to be switched on-line, to allow robots to adjust to sensory failures. We report on results from comprehensive experiments with physical robots. The results show that the use of the dynamic protocol allows formations of physical robots to move significantly faster and with greater precision, while reducing the number of formation failures

Authors

Keywords

  • Robustness
  • Robot sensing systems
  • Automatic control
  • Robotics and automation
  • Communication system control
  • Stability
  • Protocols
  • Condition monitoring
  • Shape control
  • Robot control
  • Optimal Control
  • Geometric Shapes
  • Formation Control
  • Physical Robot
  • Field Of View
  • Use Of Techniques
  • Shortest Path
  • Edge Weights
  • Distance Range
  • First Set Of Experiments
  • Single Sensor
  • Multiple Edges
  • Switching Dynamics
  • Monitoring Costs
  • Position Of The Robot
  • Single Edge
  • Dijkstra’s Algorithm
  • Static Control
  • Monitoring Capabilities
  • Static Graph
  • Robot Capabilities
  • Center Of The Field Of View
  • Distance Sensor
  • Set Of Robots

Context

Venue
IEEE International Conference on Robotics and Automation
Archive span
1984-2025
Indexed papers
30179
Paper id
67079854796116780
v2026.09.13