Topological representation and analysis method for multi-port and multi-orientation docking modular robots

For MSR Robots to successfully configure from one configuration into another, the control system must be able to visualize the current structure of the robot, which cannot be done without appropriate information about each module's docking status. Although the type of information required to visualize the structure of a MSR robot differs with the physical design of the modules, there are essential information that are commonly required, such as docking orientation and identity of neighboring modules. This paper presents a novel multi-port and multi-orientation modular robot, and a representation method that can uniquely represent the geometric structure of a group of connected modules and to analyze the number of "reconfigurable DOF" within the structure. The proposed method uses labeled planar graphs and incidence matrices to describe the docking status of the modules within the structure, which helps to effectively encode the data in computer understandable expressions. In addition to the work in configuration analysis, an innovative mechanism for detecting the orientation of each docking port is also presented.published_or_final_versio

Ground-Based 1U CubeSat Robotic Assembly Demonstration

Key gaps limiting in-space assembly of small satellites are (1) the lack of standardization of electromechanical CubeSat components for compatibility with commercial robotic assembly hardware, and (2) testing and modifying commercial robotic assembly hardware suitable for small satellite assembly for space operation. Working toward gap (1), the lack of standardization of CubeSat components for compatibility with commercial robotic assembly hardware, we have developed a ground-based robotic assembly of a 1U CubeSat using modular components and Commercial-Off-The-Shelf (COTS) robot arms without humans-in-the-loop. Two 16 in x 7 in x 7 in dexterous robot arms, weighing 2 kg each, are shown to work together to grasp and assemble CubeSat components into a 1U CubeSat. Addressing gap (2) in this work, solutions for adapting power-efficient COTS robot arms to assemble highly-capable CubeSats are examined. Lessons learned on thermal and power considerations for overheated motors and positioning errors were also encountered and resolved. We find that COTS robot arms with sustained throughput and processing efficiency have the potential to be cost-effective for future space missions. The two robot arms assembled a 1U CubeSat prototype in less than eight minutes

A decentralized control framework for modular robots

Distributed control paradigm offers robustness, scalability, and simplicity to the control and organization of module based systems. MSR (Modular Self-Reconfigurable) robot is a class of robot that best demonstrate the effectiveness of distributed systems as all modules in the robot are individuals that perform their own actuation and computation; the behavior of the complete robot is a collective behavior of all independent modules. In this paper, a general control framework, named General Suppression Framework, is proposed and a distributed control system based on the framework is presented. The control system is designed to control a set of MSR robots configured into a planar manipulator arm. All modules in the manipulator arm contain their own processing and actuation units, which allow them to evaluate and react to the environment independently. The modules can perform passive communication with their immediate neighbors and can exhibit aggressive or tolerant behavior based on the environment change to generate emergent group behaviors. A simulation program is developed to demonstrate the effectiveness of the distributed system in controlling the module based planar manipulator arm.published_or_final_versio

Addressing Tasks Through Robot Adaptation

Developing flexible, broadly capable systems is essential for robots to move out of factories and into our daily lives, functioning as responsive agents that can handle whatever the world throws at them. This dissertation focuses on two kinds of robot adaptation. Modular self-reconfigurable robots (MSRR) adapt to the requirements of their task and environments by transforming themselves. By rearranging the connective structure of their component robot modules, these systems can assume different morphologies: for example, a cluster of modules might configure themselves into a car to maneuver on flat ground, a snake to climb stairs, or an arm to pick and place objects. Conversely, environment augmentation is a strategy in which the robot transforms its environment to meet its own needs, adding physical structures that allow it to overcome obstacles. In both areas, the presented work includes elements of hardware design, algorithms, and integrated systems, with the common goal of establishing these methods of adaptation as viable strategies to address tasks. The research takes a systems-level view of robotics, placing particular emphasis on experimental validation in hardware

TOWARDS A NOVEL RESILIENT ROBOTIC SYSTEM

Resilient robotic systems are a kind of robotic system that is able to recover their original function after partial damage of the system. This is achieved by making changes on the partially damaged robot. In this dissertation study, a general robot, which makes sense by including active joints, passive joints, passive links, and passive adjustable links, was proposed in order to explore its resilience. Note that such a robot is also called an under-actuated robot. This dissertation presents the following studies. First, a novel architecture of robots was proposed, which is characterized as under-actuated robot. The architecture enables three types of recovery strategy, namely (1) change of the robot behavior, (2) change of the robot state, and (3) change of the robot configuration. Second, a novel docking system was developed, which allows for the realization of real-time assembly and disassembly and passive joint and adjustable passive link, and this thus enables the realization of the proposed architecture. Third, an example prototype system was built to experiment the effectiveness of the proposed architecture and to demonstrate the resilient behavior of the robot. Fourth, a novel method for robot configuration synthesis was developed, which is based on the genetic algorithm (GA), to determine the goal configuration of a partially damaged robot, at which the robot can still perform its original function. The novelty of the method lies in the integration of both discrete variables such as the number of modules, type of modules, and assembly patterns between modules and the continuous variables such as the length of modules and initial location of the robot. Fifth, a GA-based method for robot reconfiguration planning and scheduling was developed to actually change the robot from its initial configuration to the goal configuration with a minimum effort (time and energy). Two conclusions can be drawn from the above studies. First, the under-actuated robotic architecture can build a cost effective robot that can achieve the highest degree of resilience. Second, the design of the under-actuated resilient robot with the proposed docking system not only reduces the cost but also overcomes the two common actuator failures: (i) an active joint is unlocked (thus becoming a passive joint) and (ii) an active joint is locked (thus becoming an adjustable link). There are several contributions made by this dissertation to the field of robotics. The first is the finding that an under-actuated robot can be made more resilient. In the field of robotics, the concept of the under-actuated robot is available, but it has not been considered for reconfiguration (in literature, the reconfiguration is mostly about fully actuated robots). The second is the elaboration on the concept of reconfiguration planning, scheduling, and manipulation/control. In the literature of robotics, only the concept of reconfiguration planning is precisely given but not for reconfiguration scheduling. The third is the development of the model along with its algorithm for synthesis of the goal reconfiguration, reconfiguration planning, and scheduling. The application of the proposed under-actuated resilient robot lies in the operations in unknown or dangerous environments, for example, in rescue missions and space explorations. In these applications, replacement or repair of a damaged robot is impossible or cost-prohibited

Modular Robots Morphology Transformation And Task Execution

Self-reconfigurable modular robots are composed of a small set of modules with uniform docking interfaces. Different from conventional robots that are custom-built and optimized for specific tasks, modular robots are able to adapt to many different activities and handle hardware and software failures by rearranging their components. This reconfiguration capability allows these systems to exist in a variety of morphologies, and the introduced flexibility enables self-reconfigurable modular robots to handle a much wider range of tasks, but also complicates the design, control, and planning. This thesis considers a hierarchy framework to deploy modular robots in the real world: the robot first identifies its current morphology, then reconfigures itself into a new morphology if needed, and finally executes either manipulation or locomotion tasks. A reliable system architecture is necessary to handle a large number of modules. The number of possible morphologies constructed by modules increases exponentially as the number of modules grows, and these morphologies usually have many degrees of freedom with complex constraints. In this thesis, hardware platforms and several control methods and planning algorithms are developed to build this hierarchy framework leading to the system-level deployment of modular robots, including a hybrid modular robot (SMORES-EP) and a modular truss robot (VTT). Graph representations of modular robots are introduced as well as several algorithms for morphology identification. Efficient mobile-stylereconfiguration strategies are explored for hybrid modular robots, and a real-time planner based on optimal control is developed to perform dexterous manipulation tasks. For modular truss robots, configuration space is studied and a hybrid planning framework (sampling-based and search-based) is presented to handle reconfiguration activities. A non-impact rolling locomotion planner is then developed to drive an arbitrary truss robot in an environment

A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

Autonomous robot systems and competitions: proceedings of the 12th International Conference

This is the 2012’s edition of the scientific meeting of the Portuguese Robotics Open (ROBOTICA’ 2012). It aims to disseminate scientific contributions and to promote discussion of theories, methods and experiences in areas of relevance to Autonomous Robotics and Robotic Competitions. All accepted contributions are included in this proceedings book. The conference program has also included an invited talk by Dr.ir. Raymond H. Cuijpers, from the Department of Human Technology Interaction of Eindhoven University of Technology, Netherlands.The conference is kindly sponsored by the IEEE Portugal Section / IEEE RAS ChapterSPR-Sociedade Portuguesa de Robótic

Smart Camera Robotic Assistant for Laparoscopic Surgery

The cognitive architecture also includes learning mechanisms to adapt the behavior of the robot to the different ways of working of surgeons, and to improve the robot behavior through experience, in a similar way as a human assistant would do. The theoretical concepts of this dissertation have been validated both through in-vitro experimentation in the labs of medical robotics of the University of Malaga and through in-vivo experimentation with pigs in the IACE Center (Instituto Andaluz de Cirugía Experimental), performed by expert surgeons.In the last decades, laparoscopic surgery has become a daily practice in operating rooms worldwide, which evolution is tending towards less invasive techniques. In this scenario, robotics has found a wide field of application, from slave robotic systems that replicate the movements of the surgeon to autonomous robots able to assist the surgeon in certain maneuvers or to perform autonomous surgical tasks. However, these systems require the direct supervision of the surgeon, and its capacity of making decisions and adapting to dynamic environments is very limited. This PhD dissertation presents the design and implementation of a smart camera robotic assistant to collaborate with the surgeon in a real surgical environment. First, it presents the design of a novel camera robotic assistant able to augment the capacities of current vision systems. This robotic assistant is based on an intra-abdominal camera robot, which is completely inserted into the patient’s abdomen and it can be freely moved along the abdominal cavity by means of magnetic interaction with an external magnet. To provide the camera with the autonomy of motion, the external magnet is coupled to the end effector of a robotic arm, which controls the shift of the camera robot along the abdominal wall. This way, the robotic assistant proposed in this dissertation has six degrees of freedom, which allow providing a wider field of view compared to the traditional vision systems, and also to have different perspectives of the operating area. On the other hand, the intelligence of the system is based on a cognitive architecture specially designed for autonomous collaboration with the surgeon in real surgical environments. The proposed architecture simulates the behavior of a human assistant, with a natural and intuitive human-robot interface for the communication between the robot and the surgeon