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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Anjan kumar ray research associate isrc

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

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 model of individual robot


Network services

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

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

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

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

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

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

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

Results: Simulation

Proposed method:

front members remain same

Same velocity profile:

Change of front members


Results simulation1

Results: Simulation

Resuming straight path

Continuous turning sequences


Results experimental two robots

Results: Experimental (two robots)

Continuous left turns

Continuous right turns


Results experimental 4 robots

Results: Experimental (4 robots)


Results contd

Results: contd.

Coordination along straight path

Linear velocities


Results

Results

Coordination during turning

Linear velocities


Results contd1

Results: contd.

Angular velocities

Resuming straight path after turning

Linear velocities


Results contd2

Results: contd.

Relative heading with respect to the leader


Addition of new members

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 members1

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.


Anjan kumar ray research associate isrc

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


Anjan kumar ray research associate isrc

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

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

Addition of new members: different phases

Two robots (blue)

One robot (blue)


Anjan kumar ray research associate isrc

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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Anjan kumar ray research associate isrc

Thank you


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