Kinematic-model-free online learning for robot motion control
File(s)
Author(s)
AlAttar, Ahmad
Type
Thesis
Abstract
Controlling robots has been a thriving field of research since their emergence. Traditionally,
robots are controlled using joint space to task space transformations based on kinematic and
dynamic models. However, unconventional robots like soft, morphing, malleable, transforming,
and evolving ones pose challenges for accurate modeling and control. Controllers in literature
typically fall into two categories: model-based and model-free.
Kinematic-model-free control offers a promising solution to overcome challenges faced by
conventional controllers. This method doesn’t require prior knowledge of the robot’s kinematic
or dynamic models. Instead, it gathers data through exploratory actuations, building a volatile
local linear model to approximate the robot’s behavior and estimate actuation signals for target
movement. This thesis extends the state-of-the-art kinematic-model-free controller to tackle
various problems such as tip orientation and pose control, robot configuration control, obstacle
avoidance, gravity compensation, and continuous control.
Initially applied to planar rigid robots, the controller was adapted for soft continuum
robots, demonstrating its effectiveness through both simulation and physical experimentation.
Quaternion and dual-quaternion mathematics were employed for position, orientation, and pose
control. A dual-quaternionic kinematic-model-free multi-point controller was introduced to
resolve redundancy in hyper-redundant manipulators, validated through simulation tests.
Integration with model-predictive control enabled path planning and obstacle avoidance,
validated through physical experimentation on a planar rigid robot manipulator with virtual
obstacles. Modifications allowed the controller to run continuously at higher speeds, outperforming
conventional methods in the face of kinematic or dynamic changes.
The kinematic-model-free controller showcased versatility across different robot types, both
in simulation and physical experiments. This research pushed the boundaries of the kinematicmodel-
free controller and validated its effectiveness through rigorous testing.
robots are controlled using joint space to task space transformations based on kinematic and
dynamic models. However, unconventional robots like soft, morphing, malleable, transforming,
and evolving ones pose challenges for accurate modeling and control. Controllers in literature
typically fall into two categories: model-based and model-free.
Kinematic-model-free control offers a promising solution to overcome challenges faced by
conventional controllers. This method doesn’t require prior knowledge of the robot’s kinematic
or dynamic models. Instead, it gathers data through exploratory actuations, building a volatile
local linear model to approximate the robot’s behavior and estimate actuation signals for target
movement. This thesis extends the state-of-the-art kinematic-model-free controller to tackle
various problems such as tip orientation and pose control, robot configuration control, obstacle
avoidance, gravity compensation, and continuous control.
Initially applied to planar rigid robots, the controller was adapted for soft continuum
robots, demonstrating its effectiveness through both simulation and physical experimentation.
Quaternion and dual-quaternion mathematics were employed for position, orientation, and pose
control. A dual-quaternionic kinematic-model-free multi-point controller was introduced to
resolve redundancy in hyper-redundant manipulators, validated through simulation tests.
Integration with model-predictive control enabled path planning and obstacle avoidance,
validated through physical experimentation on a planar rigid robot manipulator with virtual
obstacles. Modifications allowed the controller to run continuously at higher speeds, outperforming
conventional methods in the face of kinematic or dynamic changes.
The kinematic-model-free controller showcased versatility across different robot types, both
in simulation and physical experiments. This research pushed the boundaries of the kinematicmodel-
free controller and validated its effectiveness through rigorous testing.
Version
Open Access
Date Issued
2024-01
Date Awarded
2024-04
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Kormushev, Petar
Sponsor
United Arab Emirates. Ministry of Education
Publisher Department
Dyson School of Design Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)