Showing papers in "IEEE Transactions on Robotics in 2015"

ORB-SLAM: A Versatile and Accurate Monocular SLAM System

Abstract: This paper presents ORB-SLAM, a feature-based monocular simultaneous localization and mapping (SLAM) system that operates in real time, in small and large indoor and outdoor environments. The system is robust to severe motion clutter, allows wide baseline loop closing and relocalization, and includes full automatic initialization. Building on excellent algorithms of recent years, we designed from scratch a novel system that uses the same features for all SLAM tasks: tracking, mapping, relocalization, and loop closing. A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation. We present an exhaustive evaluation in 27 sequences from the most popular datasets. ORB-SLAM achieves unprecedented performance with respect to other state-of-the-art monocular SLAM approaches. For the benefit of the community, we make the source code public.

Continuum Robots for Medical Applications: A Survey

Abstract: In this paper, we describe the state of the art in continuum robot manipulators and systems intended for application to interventional medicine. Inspired by biological trunks, tentacles, and snakes, continuum robot designs can traverse confined spaces, manipulate objects in complex environments, and conform to curvilinear paths in space. In addition, many designs offer inherent structural compliance and ease of miniaturization. After decades of pioneering research, a host of designs have now been investigated and have demonstrated capabilities beyond the scope of conventional rigid-link robots. Recently, we have seen increasing efforts aimed at leveraging these qualities to improve the frontiers of minimally invasive surgical interventions. Several concepts have now been commercialized, which are inspiring and enabling a current paradigm shift in surgical approaches toward flexible access routes, e.g., through natural orifices such as the nose. In this paper, we provide an overview of the current state of this field from the perspectives of both robotics science and medical applications. We discuss relevant research in design, modeling, control, and sensing for continuum manipulators, and we highlight how this work is being used to build robotic systems for specific surgical procedures. We provide perspective for the future by discussing current limitations, open questions, and challenges.

Modeling of Soft Fiber-Reinforced Bending Actuators

Abstract: Soft fluidic actuators consisting of elastomeric matrices with embedded flexible materials are of particular interest to the robotics community because they are affordable and can be easily customized to a given application. However, the significant potential of such actuators is currently limited as their design has typically been based on intuition. In this paper, the principle of operation of these actuators is comprehensively analyzed and described through experimentally validated quasi-static analytical and finite-element method models for bending in free space and force generation when in contact with an object. This study provides a set of systematic design rules to help the robotics community create soft actuators by understanding how these vary their outputs as a function of input pressure for a number of geometrical parameters. Additionally, the proposed analytical model is implemented in a controller demonstrating its ability to convert pressure information to bending angle in real time. Such an understanding of soft multimaterial actuators will allow future design concepts to be rapidly iterated and their performance predicted, thus enabling new and innovative applications that produce more complex motions to be explored.

Variable Impedance Control of Redundant Manipulators for Intuitive Human–Robot Physical Interaction

Abstract: This paper presents an experimental study on human–robot comanipulation in the presence of kinematic redundancy. The objective of the work is to enhance the performance during human–robot physical interaction by combining Cartesian impedance modulation and redundancy resolution. Cartesian impedance control is employed to achieve a compliant behavior of the robot's end effector in response to forces exerted by the human operator. Different impedance modulation strategies, which take into account the human's behavior during the interaction, are selected with the support of a simulation study and then experimentally tested on a 7-degree-of-freedom KUKA LWR4. A comparative study to establish the most effective redundancy resolution strategy has been made by evaluating different solutions compatible with the considered task. The experiments have shown that the redundancy, when used to ensure a decoupled apparent inertia at the end effector, allows enlarging the stability region in the impedance parameters space and improving the performance. On the other hand, the variable impedance with a suitable modulation strategy for parameters’ tuning outperforms the constant impedance, in the sense that it enhances the comfort perceived by humans during manual guidance and allows reaching a favorable compromise between accuracy and execution time.

Three-Dimensional Bipedal Walking Control Based on Divergent Component of Motion

Abstract: In this paper, the concept of divergent component of motion (DCM, also called “Capture Point”) is extended to 3-D. We introduce the “Enhanced Centroidal Moment Pivot point” (eCMP) and the “Virtual Repellent Point” (VRP), which allow for the encoding of both direction and magnitude of the external forces and the total force (i.e., external plus gravitational forces) acting on the robot. Based on eCMP, VRP, and DCM, we present methods for real-time planning and tracking control of DCM trajectories in 3-D. The basic DCM trajectory generator is extended to produce continuous leg force profiles and to facilitate the use of toe-off motion during double support. The robustness of the proposed control framework is thoroughly examined, and its capabilities are verified both in simulations and experiments.

A Computationally Efficient Motion Primitive for Quadrocopter Trajectory Generation

Abstract: A method is presented for the rapid generation and feasibility verification of motion primitives for quadrocopters and similar multirotor vehicles. The motion primitives are defined by the quadrocopter's initial state, the desired motion duration, and any combination of components of the quadrocopter's position, velocity, and acceleration at the motion's end. Closed-form solutions for the primitives are given, which minimize a cost function related to input aggressiveness. Computationally efficient tests are presented to allow for rapid feasibility verification. Conditions are given under which the existence of feasible primitives can be guaranteed a priori . The algorithm may be incorporated in a high-level trajectory generator, which can then rapidly search over a large number of motion primitives which would achieve some given high-level goal. It is shown that a million motion primitives may be evaluated and compared per second on a standard laptop computer. The motion primitive generation algorithm is experimentally demonstrated by tasking a quadrocopter with an attached net to catch a thrown ball, evaluating thousands of different possible motions to catch the ball.

Human–Robot Interaction Control of Rehabilitation Robots With Series Elastic Actuators

Abstract: Rehabilitation robots, by necessity, have direct physical interaction with humans. Physical interaction affects the controlled variables and may even cause system instability. Thus, human–robot interaction control design is critical in rehabilitation robotics research. This paper presents an interaction control strategy for a gait rehabilitation robot. The robot is driven by a novel compact series elastic actuator, which provides intrinsic compliance and backdrivablility for safe human–robot interaction. The control design is based on the actuator model with consideration of interaction dynamics. It consists mainly of human interaction compensation, friction compensation, and is enhanced with a disturbance observer. Such a control scheme enables the robot to achieve low output impedance when operating in human-in-charge mode and achieve accurate force tracking when operating in force control mode. Due to the direct physical interaction with humans, the controller design must also meet the stability requirement. A theoretical proof is provided to show the guaranteed stability of the closed-loop system under the proposed controller. The proposed design is verified with an ankle robot in walking experiments. The results can be readily extended to other rehabilitation and assistive robots driven with compliant actuators without much difficulty.

Force Sensor Integrated Surgical Forceps for Minimally Invasive Robotic Surgery

Abstract: This paper presents a novel surgical instrument integrated with a four-degree-of-freedom (DOF) force sensor. By adopting the capacitive transduction principle, the sensor enables the direct sensing of normal and shear forces at surgical instrument tips. Thus, three-DOF pulling forces and a single-DOF grasping force can be measured for haptic feedback control of robotic minimally invasive surgery systems. The sensor consists of four capacitive transducers, and all the transducers including analog signal processing units are embedded in small surgical instrument tips. The four-DOF force sensing is enabled thanks to the four capacitive transducers by using the force transformation method. In this study, the instrument is designed and manufactured to be adaptable to the open-source surgical robot platform, called Raven-II. In addition, the sensing system is experimentally validated through its application to the Raven-II by using a reference force sensor.

Neural Network and Jacobian Method for Solving the Inverse Statics of a Cable-Driven Soft Arm With Nonconstant Curvature

Abstract: The solution of the inverse kinematics problem of soft manipulators is essential to generate paths in the task space. The inverse kinematics problem of constant curvature or piecewise constant curvature manipulators has already been solved by using different methods, which include closed-form analytical approaches and iterative methods based on the Jacobian method. On the other hand, the inverse kinematics problem of nonconstant curvature manipulators remains unsolved. This study represents one of the first attempts in this direction. It presents both a model-based method and a supervised learning method to solve the inverse statics of nonconstant curvature soft manipulators. In particular, a Jacobian-based method and a feedforward neural network are chosen and tested experimentally. A comparative analysis has been conducted in terms of accuracy and computational time.

An Energy Tank-Based Interactive Control Architecture for Autonomous and Teleoperated Robotic Surgery

Abstract: Introducing some form of autonomy in robotic surgery is being considered by the medical community to better exploit the potential of robots in the operating room. However, significant technological steps have to occur before even the smallest autonomous task is ready to be presented to the regulatory authorities. In this paper, we address the initial steps of this process, in particular the development of control concepts satisfying the basic safety requirements of robotic surgery, i.e., providing the robot with the necessary dexterity and a stable and smooth behavior of the surgical tool. Two specific situations are considered: the automatic adaptation to changing tissue stiffness and the transition from autonomous to teleoperated mode. These situations replicate real-life cases when the surgeon adapts the stiffness of her/his arm to penetrate tissues of different consistency and when, due to an unexpected event, the surgeon has to take over the control of the surgical robot. To address the first case, we propose a passivity-based interactive control architecture that allows us to implement stable time-varying interactive behaviors. For the second case, we present a two-layered bilateral control architecture that ensures a stable behavior during the transition between autonomy and teleoperation and, after the switch, limits the effect of initial mismatch between master and slave poses. The proposed solutions are validated in the realistic surgical scenario developed within the EU-funded I-SUR project, using a surgical robot prototype specifically designed for the autonomous execution of surgical tasks like the insertion of needles into the human body.

Multirobot Control Using Time-Varying Density Functions

Abstract: An approach is presented for influencing teams of robots by means of time-varying density functions, representing rough references for where the robots should be located A continuous-time coverage algorithm is proposed and distributed approximations are given whereby the robots only need to access information from adjacent robots Robotic experiments show that the proposed algorithms work in practice, as well as in theory

Multirobot Rendezvous Planning for Recharging in Persistent Tasks

Abstract: This paper addresses a multirobot scheduling problem in which autonomous unmanned aerial vehicles (UAVs) must be recharged during a long-term mission. The proposal is to introduce a separate team of dedicated charging robots that the UAVs can dock with in order to recharge. The goal is to schedule and plan minimum cost paths for charging robots such that they rendezvous with and replenish the UAVs, as needed, during the mission. The approach is to discretize the 3-D UAV flight trajectories into sets of projected charging points on the ground, thus allowing the problem to be abstracted onto a partitioned graph. Solutions consist of charging robot paths that collectively charge each of the UAVs. The problem is solved by first formulating the rendezvous planning problem to recharge each UAV once using both an integer linear program and a transformation to the Travelling Salesman Problem. The methods are then leveraged to plan recurring rendezvous’ over longer horizons using fixed horizon and receding horizon strategies. Simulation results using realistic vehicle and battery models demonstrate the feasibility and robustness of the proposed approach.

Control of Redundant Robots Under Hard Joint Constraints: Saturation in the Null Space

Abstract: We present an efficient method for addressing online the inversion of differential task kinematics for redundant manipulators, in the presence of hard limits on joint space motion that can never be violated. The proposed Saturation in the Null Space (SNS) algorithm proceeds by successively discarding the use of joints that would exceed their motion bounds when using the minimum norm solution. When processing multiple tasks with priority, the SNS method realizes a preemptive strategy by preserving the correct order of priority in spite of the presence of saturations. In the single- and multitask case, the algorithm automatically integrates a least possible task-scaling procedure, when an original task is found to be unfeasible. The optimality properties of the SNS algorithm are analyzed by considering an associated quadratic programming problem. Its solution leads to a variant of the algorithm, which guarantees optimality even when the basic SNS algorithm does not. Numerically efficient versions of these algorithms are proposed. Their performance allows real-time control of robots executing many prioritized tasks with a large number of hard bounds. Experimental results are reported.

Continuous Role Adaptation for Human–Robot Shared Control

Abstract: In this paper, we propose a role adaptation method for human–robot shared control. Game theory is employed for fundamental analysis of this two-agent system. An adaptation law is developed such that the robot is able to adjust its own role according to the human's intention to lead or follow, which is inferred through the measured interaction force. In the absence of human interaction forces, the adaptive scheme allows the robot to take the lead and complete the task by itself. On the other hand, when the human persistently exerts strong forces that signal an unambiguous intent to lead, the robot yields and becomes the follower. Additionally, the full spectrum of mixed roles between these extreme scenarios is afforded by continuous online update of the control that is shared between both agents. Theoretical analysis shows that the resulting shared control is optimal with respect to a two-agent coordination game. Experimental results illustrate better overall performance, in terms of both error and effort, compared with fixed-role interactions.

Building a 3-D Line-Based Map Using Stereo SLAM

Abstract: This paper presents a graph-based visual simultaneous localization and mapping (SLAM) system using straight lines as features. Compared with point features, lines provide far richer information about the structure of the environment and make it possible to infer spatial semantics from the map. Using a stereo rig as the sole sensor, our proposed system utilizes many advanced techniques, such as motion estimation, pose optimization, and bundle adjustment. We use two different representations to parameterize 3-D lines in this paper: Plucker line coordinates for efficient initialization of newly observed line features and projection of 3-D lines, and orthonormal representation for graph optimization. The proposed system is tested with indoor and outdoor sequences, and it exhibits better reconstruction performance against a point-based SLAM system in line-rich environments.

Design and Modeling of Generalized Fiber-Reinforced Pneumatic Soft Actuators

Abstract: Soft actuators comprised of fluidic structures with fiber-reinforced elastomeric enclosures are seen throughout nature, exhibiting strength, power density, resilience, and diverse motions and forces. However, these structures are rarely used by engineers, in part due to the absence of a generalized understanding of their kinematics and forces. A small subset of soft actuators generating only extension or compression, popularly known as McKibben actuators, has been thoroughly investigated. This paper introduces the entire design space of actuators built with two families of fibers, of which McKibben actuators occupy a subset. The helix angle of the actuator's translation and rotation deformation is determined from the kinematics of the fiber deformation for all fiber angles as the actuator is pressurized. The volumetric transduction of the actuators, relating the output motion to change in contained volume, is analytically determined. The results are discretized to provide a designer with an easy to use design selection chart. The kinematics, force, and moment of the actuators are experimentally validated for all fiber angles.

Knee Joint Misalignment in Exoskeletons for the Lower Extremities: Effects on User's Gait

Abstract: Due to the complexity of the human musculoskeletal system and intra/intersubjects variability, powered exoskeletons are prone to human–robot misalignments. These induce undesired interaction forces that may jeopardize safe operation. Uncompensated inertia of the robotic links also generates spurious interaction forces. Current design approaches to compensate for misalignments rely on the use of auxiliary passive degrees of freedom that unavoidably increase robot inertia, which potentially affects their effectiveness in reducing undesired interaction forces. Assessing the relative impact of misalignment and robot inertia on the wearer can, therefore, provide useful insights on how to improve the effectiveness of such approaches, especially in those situations where the dynamics of the movement are quasi-periodic and, therefore, predictable such as in gait. In this paper, we studied the effects of knee joint misalignments on the wearer's gait, by using a treadmill-based exoskeleton developed by our group, the ALEX II. Knee joint misalignments were purposely introduced by adjusting the mismatch between the length of the robot thigh and that of the human thigh. The amount of robot inertia reflected to the user was adjusted through control. Results evidenced that knee misalignment significantly changes human–robot interaction forces, especially at the thigh interface, and this effect can be attenuated by actively compensating for robot inertia. Misalignments caused by an excessively long robot thigh are less critical than misalignments of equal magnitude deriving from an excessively short robot thigh.

Occlusion-Based Cooperative Transport with a Swarm of Miniature Mobile Robots

Abstract: This paper proposes a strategy for transporting a large object to a goal using a large number of mobile robots that are significantly smaller than the object. The robots only push the object at positions where the direct line of sight to the goal is occluded by the object. This strategy is fully decentralized and requires neither explicit communication nor specific manipulation mechanisms. We prove that it can transport any convex object in a planar environment. We implement this strategy on the e-puck robotic platform and present systematic experiments with a group of 20 e-pucks transporting three objects of different shapes. The objects were successfully transported to the goal in 43 out of 45 trials. When using a mobile goal, teleoperated by a human, the object could be navigated through an environment with obstacles. We also tested the strategy in a 3-D environment using physics-based computer simulation. Due to its simplicity, the transport strategy is particularly suited for implementation on microscale robotic systems.

A Versatile Tension Distribution Algorithm for $n$ -DOF Parallel Robots Driven by $n+2$ Cables

Abstract: Redundancy resolution of redundantly actuated cable-driven parallel robots (CDPRs) requires the computation of feasible and continuous cable tension distributions along a trajectory. This paper focuses on n -DOF CDPRs driven by n + 2 cables, since, for n = 6, these redundantly actuated CDPRs are relevant in many applications. The set of feasible cable tensions of n -DOF ( n + 2)-cable CDPRs is a 2-D convex polygon. An algorithm that determines the vertices of this polygon in a clockwise or counterclockwise order is first introduced. This algorithm is efficient and can deal with infeasibility. It is then pointed out that straightforward modifications of this algorithm allow the determination of various (optimal) cable tension distributions. A self-contained and versatile tension distribution algorithm is thereby obtained. Moreover, the worst-case maximum number of iterations of this algorithm is established. Based on this result, its computational cost is analyzed in detail, showing that the algorithm is efficient and real-time compatible even in the worst case. Finally, experiments on two six-degree-of-freedom eight-cable CDPR prototypes are reported.

Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints

Abstract: Evolutionary algorithm-based unmanned aerial vehicle (UAV) path planners have been extensively studied for their effectiveness and flexibility. However, they still suffer from a drawback that the high-quality waypoints in previous candidate paths can hardly be exploited for further evolution, since they regard all the waypoints of a path as an integrated individual. Due to this drawback, the previous planners usually fail when encountering lots of obstacles. In this paper, a new idea of separately evaluating and evolving waypoints is presented to solve this problem. Concretely, the original objective and constraint functions of UAVs path planning are decomposed into a set of new evaluation functions, with which waypoints on a path can be evaluated separately. The new evaluation functions allow waypoints on a path to be evolved separately and, thus, high-quality waypoints can be better exploited. On this basis, the waypoints are encoded in a rotated coordinate system with an external restriction and evolved with JADE, a state-of-the-art variant of the differential evolution algorithm. To test the capabilities of the new planner on planning obstacle-free paths, five scenarios with increasing numbers of obstacles are constructed. Three existing planners and four variants of the proposed planner are compared to assess the effectiveness and efficiency of the proposed planner. The results demonstrate the superiority of the proposed planner and the idea of separate evolution.

Dynamic Modeling of Bellows-Actuated Continuum Robots Using the Euler–Lagrange Formalism

Abstract: In the previous decade, multiple useful approaches for kinematic models of continuum manipulators were successfully developed. However, dynamic modeling approaches needed for fast simulations and the development of model-based controller design are not powerful enough yet—especially for spatial manipulators with multiple sections. Therefore, a practicable lumped mass model similar to common dynamic models of rigid-link manipulators is needed, which can be used for simulations and model-based control design. The model incorporates mechanical interconnections of parallel and serially connected bellows and uses constant curvature kinematics and its analytical derivatives to balance forces and energies in a global reference frame. The parameters of the resulting model are identified with measurements before the simulation results are experimentally validated. The obtained dynamic model can be used to both simulate the manipulator dynamics and calculate the inverse dynamics needed for model-based controller design or path planning.

Persistent Homology for Path Planning in Uncertain Environments

Abstract: We address the fundamental problem of goal-directed path planning in an uncertain environment represented as a probability (of occupancy) map. Most methods generally use a threshold to reduce the grayscale map to a binary map before applying off-the-shelf techniques to find the best path. This raises the somewhat ill-posed question, what is the right (optimal) value to threshold the map? We instead suggest a persistent homology approach to the problem—a topological approach in which we seek the homology class of trajectories that is most persistent for the given probability map. In other words, we want the class of trajectories that is free of obstacles over the largest range of threshold values. In order to make this problem tractable, we use homology in $\mathbb {Z}_2$ coefficients (instead of the standard $\mathbb {Z}$ coefficients), and describe how graph search-based algorithms can be used to find trajectories in different homology classes. Our simulation results demonstrate the efficiency and practical applicability of the algorithm proposed in this paper.

Real-Time Trajectory Generation for Quadrocopters

Abstract: This paper presents a trajectory generation algorithm that efficiently computes high-performance flight trajectories that are capable of moving a quadrocopter from a large class of initial states to a given target point that will be reached at rest. The approach consists of planning separate trajectories in each of the three translational degrees of freedom, and ensuring feasibility by deriving decoupled constraints for each degree of freedom through approximations that preserve feasibility. The presented algorithm can compute a feasible trajectory within tens of microseconds on a laptop computer; remaining computation time can be used to iteratively improve the trajectory. By replanning the trajectory at a high rate, the trajectory generator can be used as an implicit feedback law similar to model predictive control. The solutions generated by the algorithm are analyzed by comparing them with time-optimal motions, and experimental results validate the approach.

Stability-Guaranteed Force-Sensorless Contact Force/Motion Control of Heavy-Duty Hydraulic Manipulators

Abstract: In this paper, a force-sensorless high-performance contact force/motion control approach is proposed for multiple-degree-of-freedom hydraulic manipulators A rigorous stability proof for an entire hydraulic manipulator performing contact tasks is provided for the first time The controller design for the manipulator is based on the recently introduced virtual decomposition control approach As a significant novelty, the end-effector contact force is directly estimated from the manipulator's cylinder pressure data, which provides a practical solution for heavy-duty contact force control without engaging fragile force/torque sensors In the experiments, the proposed controller achieved a force control accuracy of 41% at a desired contact force of 8000 N while in motion This can be considered a significant result due to the hydraulic actuators’ highly nonlinear behaviors, the coupled mechanical linkage dynamics, and the complex interaction dynamics between the manipulator and the environment

Minimum Bounds on the Number of Electromagnets Required for Remote Magnetic Manipulation

Abstract: Numerous magnetic-manipulation systems have been developed to control objects in relatively large workspaces. These systems vary in their number of electromagnets, their configuration, and their limitations. To date, no attempt has been made to rigorously quantify how many electromagnets are required to perform a given magnetic manipulation task. For some tasks, such as controlling the field at a point, the answer is clear: the same number as dimension of control. For tasks that apply magnetic forces on an object, the answer is less clear, and some systems, which have more control magnets than kinematic degrees of freedom (DOFs), have demonstrated unexpected singularities that only arise at specific object orientations. This paper provides a general analysis for static electromagnetic systems rooted in the governing magnetic equations and proves an unintuitive result. That is, if only magnetic fields and forces are used to control an unconstrained magnetic object, four magnetic sources are required for 3-DOF force control and eight magnetic sources are required for orientation-independent 5-DOF force and heading control.

Disturbance-Observer-Based PD Control of Flexible Joint Robots for Asymptotic Convergence

Abstract: This paper proposes a robust PD control scheme for flexible-joint robots based on a disturbance observer (DOB). In this paper, the DOB is applied only to the motor-side dynamics of the robot, and the uncertainties on the motor-side are successfully eliminated. It is shown that the proposed DOB-based approach guarantees global asymptotic stability. To this end, two special treatments are required. First, unlike the typical configuration of the DOB, nominal states of the motor-side are fed back to the PD controller. Second, a control input that makes the nominal states stable is additionally introduced. The proposed approach was verified using multi-degree-of-freedom experiments.

Internal Force Analysis and Load Distribution for Cooperative Multi-Robot Manipulation

Abstract: The load distribution strategy in cooperative manipulation tasks allocates suitable force and torque setpoints to an ensemble of manipulators in order to implement a desired action on the manipulated object. Due to the manipulator redundancy, the load distribution computed by means of a generalized inverse of the grasp matrix is not uniquely determined. Controversial results on the nonsqueezing property of specific load distributions exist in the literature. In this paper, we propose a new paradigm for the analysis of internal wrenches based on the kinematic constraints imposed to the manipulator ensemble. We unify previous results by showing that there exists no unique nonsqueezing load distribution and illustrate the consequences of our findings by means of several examples. In particular, the presented results provide a new perspective on the decomposition of interaction forces into internal and external components as required for cooperative multimanipulator control schemes.

Planar Path Following of 3-D Steering Scaled-Up Helical Microswimmers

Abstract: Helical microswimmers that are capable of propulsion at low Reynolds numbers have great potential for numerous applications. Several kinds of artificial magnetic-actuated helical microswimmers have been designed by researchers. However, they are primarily open-loop controlled. This paper aims to investigate methods of closed-loop control of a magnetic-actuated helical swimmer at low Reynolds number by using visual feedback. For many in-vitro applications, helical swimmers should pass through a defined path, for example along channels with no prerequisite on the velocity profile along the path. Therefore, the main objective of this paper is to achieve a velocity-independent planar path following task. Since the planar path following is based on 3-D steering control of the helical swimmer, a 3-D pose estimation of a helical swimmer is introduced based on the real-time visual tracking with a stereo vision system. The contribution of this paper is in two parts: The 3-D steering of a helical swimmer is demonstrated by visual servo control; and the path following of a straight line with visual servo control is achieved, then compared with open-loop control. We further expect that with this visual servo control method, the helical swimmers will be able to follow reference paths at the microscale.

Geometry Selection of a Redundantly Actuated Cable-Suspended Parallel Robot

Abstract: This paper is dedicated to the geometry selection of a redundantly actuated cable-suspended parallel robot intended to manipulate heavy payloads over a wide workspace. Cable-suspended refers here to cable-driven parallel robots in a crane-like setting, where all the cable drawing points are located on top of the base frame, gravity being used to keep the cables taut. Geometry selection consists of determining the relative positions of the cable drawing points on the base frame and of the cable attachment points on the mobile platform together with the cable arrangement between these two sets of points. An original performance index is introduced. It is defined as the maximum acceptable distance between the mobile platform geometric center and the center of mass of the set consisting of the platform and a payload. This performance index is of particular interest in heavy payload handling applications. Used within a two-phase geometry selection strategy, it yields a new cable-suspended robot geometry having a very large workspace to footprint ratio and able to handle heavy payloads. A large-dimension redundantly actuated cable-suspended robot was built in order to demonstrate these capabilities.

The Triangular Quadrotor: A More Efficient Quadrotor Configuration

Abstract: We describe a new configuration of fixed-pitch miniature robot rotorcraft that combines the energetic efficiency of a helicopter and the mechanical simplicity of a quadrotor. The large power required to hover is proportional to the inverse of the rotor radius; thus, for a given diameter footprint, a single large rotor will energetically outperform several smaller rotors within the same boundary. However, smaller rotors are able to respond more quickly than large rotors, which require complex actuation to provide control. Our “triangular quadrotor” configuration uses a single large rotor for lift and three small rotors for control, gaining the benefits of both. The small rotors are canted slightly to also provide the same service as a conventional helicopter's tail rotor. Momentum theory analysis shows that a triangular quadrotor may provide a 20% reduction in required hover power, compared with a quadrotor of the same mass and footprint. This is particularly valuable for flying robots working indoors where maximum rotor size is constrained. Using conventional quadrotor and a triangular quadrotors constructed to be a similar as possible, we demonstrate that the triangular quadrotor uses 15% less power, without optimization. A power efficiency budget is provided, and the influence of drive system efficiency is explored. We present a dynamic model and demonstrate experimentally that the aircraft can be stabilized in flight with simple PID control.