This article contributes a novel method to assess robot dexterity. Existing Jacobian-based dexterity metrics, such as the manipulability index or the condition number, do not allow for comparisons between robot architectures, are local in nature, and are affected by robot dimensions (robot size). On the contrary, the introduced metric is global and allows for quantitative comparisons of robot architectures as it explicitly incorporates the orientational and positional coverage of a robot's end-effector. Experiments presented show that the proposed dexterity metric can improve the computational and precision performance of numerical inverse kinematics and showcase its suitability for use in computational dexterous robot design and, in particular, for designing concentric tube robots with high orientational and positional dexterity.

Continuum surgical robots can navigate anatomical pathways to reach pathological locations deep inside the human body. Their flexibility, however, generally comes with reduced dexterity at their tip and limited workspace. Building on recent work on eccentric tube robots, this paper proposes a new continuum robot architecture and theoretical framework that combines the flexibility of push/pull actuated snake robots and the dexterity offered by concentric tube robotic end-effectors. We designed and present a prototype system as a proof-of-concept, and developed a tailored quasistatic mechanics-based model that describes the shape and end-effector's pose for this new type robotic architecture. The model can accommodate an arbitrary number of arms placed eccentrically with respect to the backbone's neutral axis. Our experiments show that the error between model and experiment is on average 3.56% of the manipulator's overall length. This is in agreement with state of the art models of single type continuum architecture.

This article presents a unified mathematical approach for modeling, identifying, and solving the friction-inclusive dynamics of robotic mechanisms driven by sliding contact transmission systems. This approach is applied to the most common industrial screw-based drives: 1) the worm drive, 2) the simple lead screw drive, and 3) the antibacklash lead screw drive. The resulting dynamics, handily transferable to single and multiple degree of freedom (DoF) manipulators, are complemented with an algorithm for the solution of the forward dynamics problem as well as a framework for friction identification based on nonlinear optimization. The presented theory is experimentally tested on single-DoF screw-based drives for a variety of payloads and at different operation speeds. Simulation and parameter identification results using the classical Coulomb model, the Coulomb model with Stribeck friction, and the Armstrong model with Stribeck friction, rising static friction, and frictional memory are compared with experimental data, showcasing the effectiveness of the presented approach toward framing the concepts of friction and motion transmission into a robotics setting.

This article presents a model predictive controller (MPC) developed for the autonomous steering of concentric tube robots (CTRs). State-of-the-art CTR control relies on differential kinematics developed by local linearization of the CTRs mechanics model and cannot explicitly handle constraints on robot's joint limits or unstable configurations commonly known as snapping points. The proposed nonlinear MPC explicitly considers constraints on the robot configuration space (i.e., joint limits) and the robot's workspace (i.e., mixed boundary conditions on robot curvature). Additionally, the MPC calculates control decisions by optimizing the model-based predictions of future robot configurations. This way, it avoids configurations it cannot recover from, i.e., joint limits, singular configurations, and snapping. The proposed controller is evaluated via simulations and experimental studies with a variety of trajectories of increasing complexity. Simulation results demonstrate the capability of MPC to avoid singularities while satisfying robot mechanical constraints. Experimental results demonstrate that our solution enables following of trajectories unattainable by state-of-the-art controllers with mean error corresponding to 1% of robot arclength.

Concentric tube robots (CTR) can traverse tightly curved paths and offer dexterity in constrained environments, making them advantageous for minimally invasive surgical scenarios that experience strict anatomical and surgical constraints. Their shape is controlled via rotation and translation of several concentrically arranged super-elastic precurved tubes that form the robot backbone. As the elastic energy accumulated in the backbone due to bending and twist of the tubes increases, robots can exhibit sudden snapping motions, which can damage the surrounding tissues. In this paper, we proposed an approach for closed-loop steering of a redundant CTR that allows for snap-free motion and enhances its force/velocity manipulability, increasing the capacity of the robot to move and/or exercise forces along any direction. First, a controller stabilizes the CTR end-effector on a desired time-variant trajectory. Next, an online optimizer uses the robot's redundant Degrees of Freedom (DoF) to reshape its manipulability in real-time and steer it away from potentially snapping configurations or increase its capacity in delivering force payloads. Simulations and experiments demonstrate the performance of the proposed control strategy. The controller can steer a generally unstable CTR along trajectories while avoiding instabilities with a mean error of 850 μm, corresponding to 0.6% of arclength, and improves robot ability to exercise forces by 55%.

Despite several robots having been proposed for vitreoretinal surgery, there is limited information on their dynamic modeling. This gap leads to sub-optimal motor selection and hinders the application of advanced control schemes that would fulfill the goal of micro-precise surgery. This paper presents the design process and a dynamics study of a multi-Degree of Freedom (DoF) robotic system, which is inspired by established co-manipulation architectures. A rigorous kinematics and dynamics analysis of the robot's part that is responsible for manipulating the surgical tool during the retinal surgery phase is provided. In particular, the Euler-Lagrange equations of motion, which describe the dynamics of the 3-link surgical manipulator, are combined with novel analytical models of each link's corresponding transmission mechanism, including an anti-backlash lead screw assembly and a worm drive. The resulting models, transferable to existing manipulators, provide a meticulous analysis of the robot's performance that can be used both for mechanical design and control purposes.

The enhanced dexterity and manipulability offered by continuum manipulators makes them the robots of choice for complex procedures inside the human body. However, without tailored analytical tools to evaluate their manipulability, many capabilities of continuum robots such as safe and effective manipulation will remain largely inaccessible. This paper presents a quantifiable measure for analysing force/velocity manipulability of continuum robots. We expand classical measures of manipulability for rigid robots to introduce three types of manipulability indices to continuum robots, namely, velocity, compliance, and unified force-velocity manipulability. We provide a specific case study using the proposed method to analyse the force/velocity manipulability for a concentric-tube robot. We investigate the application of the manipulability measures to compare performance of continuum robots in terms of compliance and force-velocity manipulability. The proposed manipulability measures enable future research on design and optimal path planning for continuum robots.