2,659 research outputs found
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
Seven properties of self-organization in the human brain
The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) functional resiliency, 5) functional plasticity, 6) from-local-to-global functional organization, and 7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward
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An extendible reconfigurable robot based on hot melt adhesives
The ability to physically enlarge one’s own body structures plays an important role in robustness and adaptability of biological systems. It is, however, a significant challenge for robotic systems to autonomously extend their bodies. To address this challenge, this paper presents an approach using Hot Melt Adhesives (HMAs) to assemble and integrate extensions into the robotic body. HMAs are thermoplastics with temperature dependent adhesiveness and bonding strength. We exploit this property of HMAs to connect passive external objects to the robot’s own body structures, and investigate the characteristics of the approach. In a set of elementary configurations, we analyze to which extent a robot can self-reconfigure using the proposed method. We found that the extension limit depends on the mechanical properties of the extension, and the reconfiguration algorithm. A five-axis robot manipulator equipped with specialized HMA handling devices is employed to demonstrate these findings in four experiments. It is shown that the robot can construct and integrate extensions into its own body, which allow it to solve tasks that it could not achieve in its initial configuration.This work was supported by the Swiss National Science Foundation Professorship Grant No. PP00P2123387/1, and the ETH Zurich Research Grant ETH-23-10-3.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s10514-015-9428-
Design and Experiments with a Low-Cost Single-Motor Modular Aquatic Robot
We present a novel design for a low-cost robotic boat powered by a single
actuator, useful for both modular and swarming applications. The boat uses the
conservation of angular momentum and passive flippers to convert the motion of
a single motor into an adjustable paddling motion for propulsion and steering.
We develop design criteria for modularity and swarming and present a prototype
implementing these criteria. We identify significant mechanical sensitivities
with the presented design, theorize about the cause of the sensitivities, and
present an improved design for future work.Comment: Accepted to the International Conference on Ubiquitous Robots (UR
2020). 8 page
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