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Independent Study: Bryce

Optimal chassis control for autonomous robotic road vehicles.

Background

The research aims to find the steering type that best suit for the vehicle. During the transportation of a bike, there would undoubtedly be rough and uneasy terrains for the vehicle to traverse.

On top of that, the towing of the bike in addition with the physical dimensions and weight would cause the vehicle have unstable controllability.

Therefore, it is of utmost importance to identify some of the potential problems that would affect the on-road performances of the KanGo

Research Objective

The research will be conducted in three phases: defining parameters, researching of steering mechanisms, and lastly simulations and identifying the optimal control system of the KanGo vehicle.

Parameters of consideration

  • turning angle

  • steering response; controllability of vehicle and the bike when turning

  • complexity; easiness to be implemented, as compact mechanisms tends to backfire

  • cover area: the area that the vehicle would cover when turning

  • dimensions and weight distribution of vehicle.

Research details

There are mainly 2 steering mechanisms of interest.

simple simulation of steering path of vehicle

Ackerman steering

  • control non driving wheels

  • wide-range of usage

  • tight turning angle

  • requires differential gears for rear wheels

  • difficulty of implementation of small scale prototypes

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Differential drive

  • requires non-intersecting axis

  • swivel offset calculations; balance between control and load

  • passively driven; might be hard to control for longer wheelbases

  • a self pivoting castor wheel with intersecting axis

  • allow better control of chassis, as the direction of the wheels can be controlled instead of passively driven

  • allows self locking. If rotated with wheels axis pointed to the direction of drive, front wheels would be restricted from rotation (photo below), and locking of the chassis can be achieved.

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  • simulation of differential drive using robotics toolkit in MATLAB

  • trackwidth would affect the cover area of the turning, making the vehicle more bulky

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  • the below shows a simulation between a low trackwidth and wide trackwidth vehicle

  • the cover area; overall width and bulkiness would affect the vehicle maneuverability overall

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lower trackwidth vehicle

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higher trackwidth vehicle

Significance of Research

During the testing phase, we have encountered difficulties with vehicle steering. When steering the vehicle, there are complication with the bike as it would restrict. This would make transporting the bike troublesome, and in some case might cause failure in towing the bike to its destination.

The results utterly defeats the purpose of creating KanGo, and moreover would induce more complications in developments as redesigning must be done if such errors would occur.

Therefore, it is best to address the issue, and to research with caution in order to thoroughly plan the designing of the vehicle. This would lower the chance of catastrophic designing error to occur.

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