Multi-vehicle Cooperative Control Raffaello D

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Multi-vehicle Cooperative ControlRaffaello
DAndreaMechanical Aerospace Engineering
Cornell University
OUTLINE

• Hierarchical Decomposition
• Example RoboCup
• Concluding Remarks

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Hierarchical Decomposition
Objective Develop hierarchy-based tools for
designing complex, multi-asset systems in
uncertain and adversarial environments
MAIN IDEAS

• System level decomposition
• Bottom up design
• Simplification of models via relaxations and
  reduction
• Propagation of uncertainty to higher levels
• Adoption of heuristics, coupled with verification

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Example RoboCup

• International competition cooperation,
  adversaries, uncertainty
• 1997 Nagoya Carnegie Mellon
• 1998 Paris Carnegie Mellon
• 1999 Stockholm Cornell
• 2000 Melbourne Cornell
• 2001 Seattle
• Involvement
• Universities, Research Labs, Companies

Cornell
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Example
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Competition Highlights (1999)
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System Level Decomposition
Wheel velocity
INTELLIGENCE AND CONTROL
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Bottom Up Design
Relaxation and Simplified Dynamics
RobustControl Design
Restrict possible motions, design low level
systemto behave like simplified dynamical model
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Mid-Level Control
Trajectory Primitives
minimum time, minimum energy
minimum time
minimum time
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Intelligence and Control
DESIRED FINAL POSITIONS ANDVELOCITIES, TIME TO
TARGET
DESIRED VELOCITIES
STRATEGY
TRAJECTORYGENERATION
LOCALCONTROL
FEASIBILITY OF REQUESTS

• Current design
• finite state machine
• Obstacle avoidance Frazzoli, Feron, Dahleh
• no adaptation
• no formal methods

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BACK-PASS
PASS-PLAY
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Example Goalie
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Formation Flight Testbed
Use upwash created by neighbouring craft to
provide extra lift
MOTIVATION

• satellite type of applications (Wolfe,
  Chichka and Speyer 96)
• MAVs and UAVs, extend range

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Formation Flight test bed

• 5 wings in low speed wind tunnel
• roll and translation along y axis

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Concluding Remarks
Relaxation, Restriction
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PERFORMANCE
COMPLEXITY
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Robust Control Design
Hierarchical Design
...
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Current Activities

• Propagation of uncertainy/mismatch
• Randomized Algorithms for planning (MIT)
• Game Theoretic tools (delayed information)
• Verification
• Human in the loop
• New test-beds