Stable Coordinated Platooning by a Group of Mobile Robots
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Stable Coordinated Platooning by a Group of Mobile Robots Anjan Kumar Ray , Martin McGinnity , Laxmidhar Behera, Sonya Coleman. Anjan Kumar Ray Research Associate, ISRC UKIERI Workshop on the Fusion of BCI and Assistive Robotics, 7-8 July, 2011. Presentation Outline.

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Stable Coordinated Platooning by a Group of Mobile RobotsAnjan Kumar Ray , Martin McGinnity , Laxmidhar Behera, Sonya Coleman

Anjan Kumar Ray

Research Associate, ISRC

UKIERI Workshop on the Fusion of BCI and Assistive Robotics, 7-8 July, 2011


Presentation Outline

  • Background developments for collaboration

    • Network model and services of individual robot

    • Understanding environment

    • Platoon formation

  • Stable platoon coordination

  • Results

  • Addition of new members

  • Results

  • Conclusion


Network model of individual robot


Network Services

Each robot acts as a server of different information for other robots.

Each robot can request information from other robots.

A robot can be connected by an individual robot or a group of robots.

A robot can connect to an individual robot or a group of robots.

A robot can switch among server robots depending on requirements.


Experiment on network services

(b) A group of robots turn

(a) Linear velocity control

The objective : Robots can share information in a decentralized way


Understanding environment: an example

  • A robot understands its environment using different sensors.

  • An example shows a laser based human tracking by a robot.

  • Objective: A robot can decide its motion as per environmental situation and application.


Scenario : Column formation and Platoon

  • If a robot decides its motion, it can pass this information to other robots.

  • Subsequently, other robots can follow the leader.

  • They should maintain safe separation distances among each others.

  • A column formation is generated in this way.

  • Similarly, multiple columns generate a platoon of robots.

  • So, any front member can be the leader.

  • Assumption: The leader knows its motion initiative.

Figure 1: Column of robots

Figure 2: Platoon of robots


Stable platoon coordination: Model

  • A robot is given an ID Acr where ‘c’ and ‘r’ refer to the corresponding column and row.

  • The position and orientation at thek-th time instance are denoted by

  • where,

  • Linear and angular velocities of each robot are represented by V cr and ωcr.


Stable platoon coordination: Constraints

  • General constraints

  • for front members:

  • General constraint for column members:

  • Relative positional constraints:

    • Front members may be at the left, right or both sides of the leader.

  • Navigational constrains imposed by the leader:

    • The leader may move straight, turn right or left or move with any combinations.

    • Further constraints imposed on column members:

    • They should not imitate velocity profile of the leader rather decide their own velocities as per the impending situation.


Stable platoon coordination: Velocity Control

Velocities of the front members satisfying all constraints are defined by

Similarly, the velocities of the column members are defined by

Where,


Results: Simulation

Proposed method:

front members remain same

Same velocity profile:

Change of front members


Results: Simulation

Resuming straight path

Continuous turning sequences


Results: Experimental (two robots)

Continuous left turns

Continuous right turns


Results: Experimental (4 robots)


Results: contd.

Coordination along straight path

Linear velocities


Results

Coordination during turning

Linear velocities


Results: contd.

Angular velocities

Resuming straight path after turning

Linear velocities


Results: contd.

Relative heading with respect to the leader


Addition of new members

  • Previous method ensures cohesion of an existing formation.

  • Next, we studied the possibility of expanding an existing formation.

  • In this method, external robots can join the existing formation.

  • These robots gradually adapt to the existing formation.

  • They are able to decide their velocities as per the changes in the leader.

  • This method enhances scalability of an existing formation.


Addition of new members

  • An external robotis assigned with an ID Acr+1 within the formation.

  • A reference trajectory is initialized at the k-thtime which puts the reference trajectory at the desired separation distance.

  • The reference trajectory for each external robot is defined as per the kinematic constraints of an existing formation.


Addition of new members:

  • We proposed a model predictive control method to define the velocities of these

  • external robots.

  • It minimizes reference trajectory tracking errors.

  • The cost function is given by

  • where,

  • Ueis error input vector

  • is error state matrix

  • is error input matrix

  • and are weighting matrices


The control law is obtained by minimizing the cost function as

Finally, velocity inputs to the external robot are given by


Results: Adaptation to an existing formation

Angular velocities

Paths of an existing formation

along with an external robot

Linear velocities


Addition of new members: different phases

Two robots (blue)

One robot (blue)


Conclusion

  • Experimental verifications of a multi-robot platoon coordination is presented.

  • Members follow motion patterns of the leader while maintaining safe separation distances among each other.

  • Furthermore, the front members keep their relative heading with respect to the

  • leader.

  • We tested the proposed method in different navigational situations.

  • We included the facility of adding additional members to the formation.

  • Results are shown to validate the method.

  • This method can be explored in different application areas including distributed

  • sensing of the environment, satellite formation, UAV formation for wide area

  • surveillance and UGV formation.

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Thank you


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