A. James Clark School of Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/1654
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item Distributed Task Allocation Algorithms for Multi-Agent Systems with Very Low Communication(IEEE, 2022-11-23) Bapat, Akshay; Bora, Bharath Reddy; Herrmann, Jeffrey W.; Azarm, Shapour; Xu, Huan; Otte, Michael W.In this paper we explore the problem of task allocation when communication is very low, e.g., when the probability of a successful message between agents is ≪0.01 . Such situations may occur when agents choose not to communicate for reasons of stealth or when agent-to-agent communication is actively jammed by an adversary. In such cases, agents may need to divide tasks without knowing the locations of each other. Given the assumption that agents know the total number of agents in the workspace, we investigate solutions that ensure all tasks are eventually completed—even if some of the agents are destroyed. We present two task allocation algorithms that assume communication may not happen, but that benefit whenever communications are successful. (1) The Spatial Division Playbook Algorithm divides task among agents based on an area decomposition. (2) The Traveling Salesman Playbook Algorithm considers mission travel distance by leveraging Christofides’ 3/2 approximation algorithm. These algorithms have task completion runtime complexity of O(mlogm) and O(m3) , respectively, where m refers to the total number of tasks. We compare both algorithms to four state-of-the-art task allocation algorithms — ACBBA, DHBA, PIA and GA — across multiple communication levels and multiple numbers of targets, and using three different communication models. The new algorithms perform favorably, in terms of the time required to ensure all targets are visited, in the special case when communication is very low.Item DESIGN, DEVELOPMENT, AND EVALUATION OF A DISCRETELY ACTUATED STEERABLE CANNULA(2014) Ayvali, Elif; Desai, Jaydev P; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Needle-based procedures require the guidance of the needle to a target region to deliver therapy or to remove tissue samples for diagnosis. During needle insertion, needle deflection occurs due to needle-tissue interaction which deviates the needle from its insertion direction. Manipulating the needle at the base provides limited control over the needle trajectory after the insertion. Furthermore, some sites are inaccessible using straight-line trajectories due to delicate structures that need to be avoided. The goal of this research is to develop a discretely actuated steerable cannula to enable active trajectory corrections and achieve accurate targeting in needle-based procedures. The cannula is composed of straight segments connected by shape memory alloy (SMA) actuators and has multiple degrees-of-freedom. To control the motion of the cannula two approaches have been explored. One approach is to measure the cannula configuration directly from the imaging modality and to use this information as a feedback to control the joint motion. The second approach is a model-based controller where the strain of the SMA actuator is controlled by controlling the temperature of the SMA actuator. The constitutive model relates the stress, strain and the temperature of the SMA actuator. The uniaxial constitutive model of the SMA that describes the tensile behavior was extended to one-dimensional pure- bending case to model the phase transformation of the arc-shaped SMA wire. An experimental characterization procedure was devised to obtain the parameters of the SMA that are used in the constitutive model. Experimental results demonstrate that temperature feedback can be effectively used to control the strain of the SMA actuator and image feedback can be reliably used to control the joint motion. Using tools from differential geometry and the configuration control approach, motion planning algorithms were developed to create pre-operative plans that steer the cannula to a desired surgical site (nodule or suspicious tissue). Ultrasound-based tracking algorithms were developed to automate the needle insertion procedure using 2D ultrasound guidance. The effectiveness of the proposed in-plane and out-of-plane tracking methods were demonstrated through experiments inside tissue phantom made of gelatin and ex-vivo experiments. An optical coherence tomography probe was integrated into the cannula and in-situ microscale imaging was performed. The results demonstrate the use of the cannula as a delivery mechanism for diagnostic applications. The tools that were developed in this dissertation form the foundations of developing a complete steerable-cannula system. It is anticipated that the cannula could be used as a delivery mechanism in image-guided needle-based interventions to introduce therapeutic and diagnostic tools to a target region.