Tumours are subject to external environmental variability. However, in vitro tumour spheroid experiments, used to understand cancer progression and develop cancer therapies, have been routinely performed for the past fifty years in constant external environments. Furthermore, spheroids are typically grown in ambient atmospheric oxygen (normoxia), whereas most in vivo tumours exist in hypoxic environments. Therefore, there are clear discrepancies between in vitro and in vivo conditions. We explore these discrepancies by combining tools from experimental biology, mathematical modelling, and statistical uncertainty quantification. Focusing on oxygen variability to develop our framework, we reveal key biological mechanisms governing tumour spheroid growth. Growing spheroids in time-dependent conditions, we identify and quantify novel biological adaptation mechanisms, including unexpected necrotic core removal, and transient reversal of the tumour spheroid growth phases.

Tracking and controlling the shape of continuum dexterous manipulators (CDM) in constraint environments is a challenging task. The imposed constraints and interaction with unknown obstacles may conform the CDM's shape and therefore demands for shape sensing methods which do not rely on direct line of sight. To address these issues, we integrate a novel Fiber Bragg Grating (FBG) shape sensing unit into a CDM, reconstruct the shape in real-time, and develop an optimization-based control algorithm using FBG tip position feedback. The CDM is designed for less-invasive treatment of osteolysis (bone degradation). To evaluate the performance of the feedback control algorithm when the CDM interacts with obstacles, we perform a set of experiments similar to the real scenario of the CDM interaction with soft and hard lesions during the treatment of osteolysis. In addition, we propose methods for identification of the CDM collisions with soft or hard obstacles using the jacobian information. Results demonstrate successful control of the CDM tip based on the FBG feedback and indicate repeatability and robustness of the proposed method when interacting with unknown obstacles.

This paper focuses on the design and quantitative characterization of a debriding tool integrated with a robotic system to treat osteolysis (bone degradation). Osteolysis typically occurs due to wear of the polyethylene liner of the acetabular implant after total hip replacement surgery. In less invasive treatment of osteolysis, surgeons conventionally use rigid tools to debride the lesion, however with these inflexible instruments, complex lesion shapes are not completely treatable (about 50%). To address this issue, we have developed a debriding tool that passes through the lumen of a continuum dexterous manipulator (CDM). Integration of the CDM with a robotic arm assists the surgeon to reach the desired region behind the implant. Performance of the debriding tool integrated with this system was quantitatively evaluated during a simulated robot-assisted lesion debriding scenario. Rotational speed, aspiration pressure and irrigation flow of the debriding tool, as well as the sweeping velocity of the robotic system were identified as effective parameters in this procedure. Results indicate that maximum efficiency of the tool is achievable in a particular combination of these parameters.

Lesions of the lateral skull base in the petrous apex present unique surgical challenges because of the proximity of critical structures, including the inner ear, carotid artery, jugular bulb, facial nerve, lower cranial nerves, dura and brain. Currently, there are few appropriate surgical devices that can reach and remove these lesions, each with their own disadvantages. Here we investigate the feasibility of a dexterous continuum manipulator (DCM) capable of C-& S-shaped bends enabling dissection with remote center of motion (RCM) deep to the intact inner ear. A dedicated borescope channel provides the necessary visualization, while a flexible ring curette pre-shaped with a nitinol strip is designed to work through the instrument lumen for curettage of a cystic lesion. The kinematics of the DCM with the ring curette subject to an RCM constraint are investigated to explore the boundaries of a typical cyst cavity. Experiments in the planar phantom are carried out to validate feasibility, and results show that the proposed solution is practicable, accomplishing 80% and 83% removal of cysts for two kinds of boundaries.

This paper presents a nested marsupial robotic system and its execution of a notional disaster response task. Human supervised autonomy is facilitated by tightly-coupled, high-level user feedback enabling command and control of a bimanual mobile manipulator carrying a quadrotor unmanned aerial vehicle that carries a miniature ground robot. Each robot performs a portion of a mock hazardous chemical spill investigation and sampling task within a shipping container. This work offers an example application for a heterogeneous team of robots that could directly support first responder activities using complementary capabilities of autonomous dexterous manipulation and mobility, autonomous planning and control, and teleoperation. The task was successfully executed during multiple live trials at the DARPA Robotics Challenge Technology Expo in June 2015. A key contribution of the work is the application of a unified algorithmic approach to autonomous planning, control, and estimation supporting vision-based manipulation and non-GPS-based ground and aerial mobility, thus reducing algorithmic complexity across this capability set. The unified algorithmic approach is described along with the robot capabilities, hardware implementations, and human interface, followed by discussion of live demonstration execution and results.

The ability of robotic systems to effectively address disaster scenarios that are potentially dangerous for human operators is continuing to grow as a research and development field. This leverages research from areas such as bimanual manipulation, dexterous grasping, bipedal locomotion, computer vision, sensing, object segmentation, varying degrees of autonomy, and operator control/feedback. This paper describes the development of a semi-autonomous bimanual dexterous robotic system that comes to the aid of a mannequin simulating an injured victim by operating a fire extinguisher, affixing a cervical collar, cooperatively placing the victim on a spineboard with another bimanual robot, and relocating the victim. This system accomplishes these tasks through a series of control modalities that range from supervised autonomy to full teleoperation and allows the control model to be chosen and optimized for a specific subtask. We present a description of the hardware platform, the software control architecture, a human-in-the-loop computer vision algorithm, and an infrastructure to use a variety of user input devices in combination with autonomous control to compete several dexterous tasks. The effectiveness of the system was demonstrated in both laboratory and live outdoor demonstrations.

We have recently developed a snake-like manipulator for use in orthopaedic environments. One example application is the treatment of osteolysis (bone degradation) due to total hip arthroplasty. Recent literature suggest constant curvature models to define manipulator configuration from string (or actuator cable) length; however, our manipulator does not conform to constant curvature bending. In this paper, we present a two-step model to predict the kinematic configuration directly from string length with no assumptions regarding constant curvature bending. We experimentally identify the model parameters and validate the model on an additional experimental data set. The results indicate our model achieved an average maximum error of 1.0 ± 0.90mm in predicting manipulator configuration compared to the ground truth over the test data set.

Osteolysis is a debilitating condition that can occur behind the acetabular component of total hip replacements due to wear of the polyethylene liner. Conventional treatment techniques suggest replacing the component, while less-invasive approaches attempt to access and clean the lesion through the screw holes in the component. However, current rigid tools have been shown to access at most 50% of the lesion. Using a recently developed dexterous manipulator, we have adapted a group-theoretic convolution framework to define the manipulator's workspace and its ability to fully explore a lesion. We compared this with the experimental exploration of a printed model of the lesion. This convolution approach successfully contains the experimental results and shows over 98.8% volumetric coverage of a complex lesion. The results suggest this manipulator as a possible solution to accessing much of the area unreachable to the conventional less-invasive technique.

This paper presents a method for estimating drive cable length in an underactuated, hyper-redundant, snake-like manipulator. The continuum manipulator was designed for the surgical removal of osteolysis behind total hip arthroplasties. Two independently actuated cables in a pull-pull configuration control the compliant manipulator in a single plane. Using a previously developed kinematic model, we present a method for estimating drive cable displacement for a given manipulator configuration. This calibrated function is then inverted to explore the ability to achieve local manipulator configurations from prescribed drive cable displacements without the use of continuous visual feedback. Results demonstrate an effectiveness in predicting drive cable lengths from manipulator configurations. Preliminary results also show an ability to achieve manipulator configurations from prescribed cable lengths with reasonable accuracy without continuous visual feedback.

We address the problem of image formation in transmission tomography when metal objects of known composition and shape, but unknown pose, are present in the scan subject. Using an alternating minimization (AM) algorithm, derived from a model in which the detected data are viewed as Poisson-distributed photon counts, we seek to eliminate the streaking artifacts commonly seen in filtered back projection images containing high-contrast objects. We show that this algorithm, which minimizes the I-divergence (or equivalently, maximizes the log-likelihood) between the measured data and model-based estimates of the means of the data, converges much faster when knowledge of the high-density materials (such as brachytherapy applicators or prosthetic implants) is exploited. The algorithm incorporates a steepest descent-based method to find the position and orientation (collectively called the pose) of the known objects. This pose is then used to constrain the image pixels to their known attenuation values, or, for example, to form a mask on the "missing" projection data in the shadow of the objects. Results from two-dimensional simulations are shown in this paper. The extension of the model and methods used to three dimensions is outlined.

The reconstruction of tomographic images is often treated as a linear deblurring problem. When a high-density, man-made metal object is present somewhere in the image field, it is a deblurring problem in which the unknown function has a component that is known except for some location and orientation parameters. We first address general linear deblurring problems in which a known function having unknown parameters is present. We then show how the resulting iterative solution can be applied to tomographic imaging in the presence of man-made foreign objects, and we apply the result, in particular, to X-ray computed tomography imaging used in support of brachytherapy treatment of advanced cervical cancer.