Transformation Design Principles as Enablers for Designing Reconfigurable Robots

The design of cleaning and maintenance (CaM) robots are generally limited by their fixed morphologies. Contrary to the fixed robotic systems, design for reconfiguration in robots presents unique challenges. Reconfigurable robots pose the challenge of designing their subsystems and functionalities such that a robot meets its system, performance, and other fixed requirements, while providing reconfiguration capabilities to increase functionality and to provide innovative operational scenarios. Established transformation or reconfiguration principles, namely, expand/collapse, expose/cover, and fuse/divide, observed in several products-services-systems, can be adopted to design subsystems and system for reconfiguration in robots. Essentially these principles in many robots may be governed and implemented. The heuristic approach to design the reconfigurable robotic systems using three layers namely input, formulation and output layer is proposed. This paper used the design principles and associated facilitators and abstracts them to build a reconfigurable pavement cleaning robot named Panthera. Moreover, need, challenges, and design strategies for system and subsystem levels are presented. The system-level reconfiguration is to expand/collapse, whereas the subsystems, namely, i) Varying footprint, ii) Transmission, iii) Storage bin, iv) Cleaning brushes, v) Vacuum/Suction and blowing, and vi) Outer skin or cover are explained. The step-by-step illustration for reconfiguring the system and subsystem of Panthera is done by referring to the transformation principles, precedence, and mechanism adopted to achieve reconfiguration requirements.

Modelling and Control of a Reconfigurable Robot for Achieving Reconfiguration and Locomotion with Different Shapes

Area coverage is a crucial factor for a robot intended for applications such as floor cleaning, disinfection, and inspection. Robots with fixed shapes could not realize an adequate level of area coverage performance. Reconfigurable robots have been introduced to overcome the limitations of fixed-shape robots, such as accessing narrow spaces and cover obstacles. Although state-of-the-art reconfigurable robots used for coverage applications are capable of shape-changing for improving the area coverage, the reconfiguration is limited to a few predefined shapes. It has been proven that the ability of reconfiguration beyond a few shapes can significantly improve the area coverage performance of a reconfigurable robot. In this regard, this paper proposes a novel robot model and a low-level controller that can facilitate the reconfiguration beyond a small set of predefined shapes and locomotion per instructions while firmly maintaining the shape. A prototype of a robot that facilitates the aim mentioned above has been designed and developed. The proposed robot model and controller have been integrated into the prototype, and experiments have been conducted considering various reconfiguration and locomotion scenarios. Experimental results confirm the validity of the proposed model and controller during reconfiguration and locomotion of the robot. Moreover, the applicability of the proposed model and controller for achieving high-level autonomous capabilities has been proven.

Robust and fault tolerant control of modular and reconfigurable robots

Modular and reconfigurable robot has been one of the main areas of robotics research in recent years due to its wide range of applications, especially in aerospace sector. Dynamic control of manipulators can be performed using joint torque sensing with little information of the link dynamics. From the modular robot perspective, this advantage offered by the torque sensor can be taken to enhance the modularity of the control system. Known modular robots though boast novel and diverse mechanical design on joint modules in one way or another, they still require the whole robot dynamic model for motion control, and modularity offered in the mechanical side does not offer any advantage in the control design. In this work, a modular distributed control technique is formulated for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under this control methodology, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed without the need of re-tuning the controller. Model uncertainties associated with load and links are compensated by the use of joint torque sensors. Other model uncertainties at each joint module are compensated by a decomposition based robust controller for each module. The proposed distributed control technique offers a ‘modular’ approach, featuring a unique joint-by-joint control synthesis of the joint modules. Fault tolerance and fault detection are formulated as a decentralized control problem for modular and reconfigurable robots in this thesis work. The modularity of the system is exploited to derive a strategy dependent only on a single joint module, while eliminating the need for the motion states of other joint modules. While the traditional fault tolerant and detection schemes are suitable for robots with the whole dynamic model, this proposed technique is ideal for modular and reconfigurable robots because of its modular nature. The proposed methods have been investigated with simulations and experimentally tested using a 3-DOF modular and reconfigurable robot.

Robot calibration based on nonlinear formulation for modular reconfigurable robots (MRRs).

Developed in this thesis is a full pose kinematic calibration method for modular reconfigurable robots (MRRs). This method is based on a nonlinear formulation as opposed to the conventional linear method that has a number of critical limitations. By avoiding linearization of the nonlinear robot forward kinematic equations, these nonlinear equations are directly used to identify the robot calibration parameters. A hybrid search method is developed to solve the nonlinear error equations by combining genetic algorithms with Monte Carlo simulations to ensure a global search over the robot workspace with good accuracy. A number of comparisons are made between the proposed method and the conventional linear method, indicating the advantages of the former over the latter by eliminating two critical limitations. The first one is the orthogonality sacrifice that leads to ill-conditioning of the Jacobian used in the linear method. The second one is quadrant sensitivity during the determination of the (Tait) Bryan angles from inverting the rotation matrix.

Robust and fault tolerant control of modular and reconfigurable robots

Modular and reconfigurable robot has been one of the main areas of robotics research in recent years due to its wide range of applications, especially in aerospace sector. Dynamic control of manipulators can be performed using joint torque sensing with little information of the link dynamics. From the modular robot perspective, this advantage offered by the torque sensor can be taken to enhance the modularity of the control system. Known modular robots though boast novel and diverse mechanical design on joint modules in one way or another, they still require the whole robot dynamic model for motion control, and modularity offered in the mechanical side does not offer any advantage in the control design. In this work, a modular distributed control technique is formulated for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under this control methodology, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed without the need of re-tuning the controller. Model uncertainties associated with load and links are compensated by the use of joint torque sensors. Other model uncertainties at each joint module are compensated by a decomposition based robust controller for each module. The proposed distributed control technique offers a ‘modular’ approach, featuring a unique joint-by-joint control synthesis of the joint modules. Fault tolerance and fault detection are formulated as a decentralized control problem for modular and reconfigurable robots in this thesis work. The modularity of the system is exploited to derive a strategy dependent only on a single joint module, while eliminating the need for the motion states of other joint modules. While the traditional fault tolerant and detection schemes are suitable for robots with the whole dynamic model, this proposed technique is ideal for modular and reconfigurable robots because of its modular nature. The proposed methods have been investigated with simulations and experimentally tested using a 3-DOF modular and reconfigurable robot.

Robot calibration based on nonlinear formulation for modular reconfigurable robots (MRRs).

Developed in this thesis is a full pose kinematic calibration method for modular reconfigurable robots (MRRs). This method is based on a nonlinear formulation as opposed to the conventional linear method that has a number of critical limitations. By avoiding linearization of the nonlinear robot forward kinematic equations, these nonlinear equations are directly used to identify the robot calibration parameters. A hybrid search method is developed to solve the nonlinear error equations by combining genetic algorithms with Monte Carlo simulations to ensure a global search over the robot workspace with good accuracy. A number of comparisons are made between the proposed method and the conventional linear method, indicating the advantages of the former over the latter by eliminating two critical limitations. The first one is the orthogonality sacrifice that leads to ill-conditioning of the Jacobian used in the linear method. The second one is quadrant sensitivity during the determination of the (Tait) Bryan angles from inverting the rotation matrix.

Multi-modal reconfigurable robotic platform with 3d-immersive telepresence system

The concept of reconfigurability and its applications in robotics have become prominent in the past few years as they provide versatility, adaptability and scalability to the systems. The reconfigurable robots can perform tasks in outer space, under the sea and in hazardous environments by rearranging their physical configurations to alter the system’s behavior and geometry. However, the concept of reconfigurable robots is not just constrained by the mechanical reconfiguration of the components, for the system should also demonstrate a modular reconfigurable behavior to newly imposed conditions. The objective of this work was to design and implement a multi-modal reconfigurable platform based on the concept of “form follows function” to be integrated with 3D-Immersive telepresence systems. The developed system was analyzed to verify the feasibility and functionality of the proposed architecture, and suggestions were made for future improvements.