In this article, a macro–mini aerial manipulator with elastic suspension is introduced. The mini is an omnidirectional aerial manipulator suspended from the macro by a spring. The macro is a Cartesian robot that moves the anchoring point of the spring. This design combines the advantages of the large workspace of the macrorobot with the high dynamics of aerial vehicles, while reducing energy consumption thanks to gravity compensation. A partitioned control scheme is first implemented to regulate the aerial manipulator and its carrier separately. The redundancy resolution strategy positions the macrorobot to minimize the energy consumption of the aerial manipulator at steady state. Then, a nonlinear model predictive controller replaces the partitioned controller to improve further the efficiency of the combined system, notably by anticipating the slow dynamics of the macrorobot. A sufficient condition for offset-free tracking has been investigated theoretically. Experiments with a cable-driven parallel robot as macro are carried out to assess the added value of the carrier. Both controllers are validated and compared experimentally.

Aerial Manipulators with Elastic Suspension (AMES) may be seen as a hybrid robot mixing properties of classical Aerial Manipulators (AMs) and Cable-Driven Parallel Robots (CDPRs). The optimal design and control of an AMES using unidirectional thrusters are considered in this paper. To maximize the workspace, an optimization algorithm is proposed. The position and orientation of the thrusters are optimized by adapting methods borrowed from both the AM and CDPR communities. The resulting design is used to build a prototype. Preliminary experimentations are carried out to validate the theoretical workspace and assess the trajectory tracking performance of this AMES. Experiments highlight the significant improvements with respect to a previous suboptimal prototype.

Aerial manipulation increases significantly the workspace size of robotic manipulators. However, aerial manipulation suffers from a lack of autonomy due to limited embedded energy. The Aerial Manipulator with Elastic Suspension (AMES) is designed to cope with this issue. It is an omnidirectional aerial vehicle equipped with a gripper and suspended under a robotic carrier by a spring for gravity compensation. In this paper, the AMES is controlled with a nonlinear model predictive controller (NMPC). To eliminate the steady-state errors, an observer based on a model of the AMES augmented with constant disturbances is implemented in conjunction with the NMPC controller. Experiments illustrate the efficiency of the NMPC by comparing it to a computed torque controller.

Since omnidirectional aerial vehicles can generate a six degrees of freedom wrench, they could be used for dexterous manipulation tasks without the need for an additional robotic arm. However, they suffer from a reduced efficiency and dynamics range due to the huge amount of energy lost in gravity compensation.In this work, we introduce an omnidirectional aerial manipulator suspended from a cable-driven parallel robot (CDPR) by a spring, combining the advantages of the CDPR large workspace with the high dynamics of aerial vehicles, while reducing energy consumption thanks to gravity compensation.A partitioned control scheme is implemented to regulate both systems separately. A preliminary control strategy is proposed for the CDPR motion that minimizes the total energy consumption. Experiments are carried out to assess the added value of the CDPR carrier.

This paper presents a preliminary study of an Aerial Manipulator suspended by a spring to a robotic carrier. The suspended aerial manipulator is actuated by six pairs of contra-rotating propellers generating a 6-DoF wrench. Simulations show path following results using a computed torque (feedback linearization) control strategy. Active vibration canceling is validated experimentally on a first prototype.

This work studies redundant actuation for both trajectory tracking and disturbance rejection on flexible cable-driven parallel robots (CDPR). High dynamics/bandwidth unidirectional force generators, like air propellers, are used in combination with conventional but slower cable winding winches. To optimally balance the action of the two types of actuation within their saturation constraints, a model predictive controller is used. Experiments show the added value of on-board propulsion units with respect to winch-only control in order to improve the overall CDPR dynamic behavior.

This work is a preliminary study assessing the feasibility of using cold-gas thrusters for active damping of flexible cable-driven parallel robots. The concept is validated experimentally on a planar robot embedding custom-built supersonic air thrusters operating at an industry-standard pressure level.

An alternative approach to standard computed torque with feedback linearization is proposed in this paper to control cable-driven parallel robots (CDPRs) with highly flexible cables. Exteroceptive feedback is used to measure the end-effector Cartesian position at a high sampling rate. Stability is demonstrated using singular perturbation theory. The proposed control scheme is experimentally validated on a planar 3-degree-of-freedom CDPR and its efficiency is assessed by comparison with a simple kinematic control law.

Cable-Driven Parallel Robots (CDPRs) can execute fast motions across a large workspace. However, these performances are reached at the cost of a relatively low stiffness which often yields parasitic vibrations at the CDPR mobile platform. In this paper, vibration damping of CDPRs is addressed by means of an original active stabilizer consisting of actuated rotating arms installed on-board the CDPR mobile platform. A control strategy for the whole system, which consists of the CDPR and the stabilizer, and with one purpose for each-position control for the platform and vibration damping for the stabilizer-is designed. The system being controlled at two different time scales, the singular perturbation theory can be used to prove the stability of the corresponding closed-loop system. The efficiency of the proposed device and control strategy is tested in simulations in the case of a planar 3-DOF CDPR equipped with a three-arm stabilizer.

Compared to other parallel robots, cable-driven parallel robots can achieve bigger workspace, higher dynamics with lighter parts and fewer energy while being economically competitive. However, such robots with big workspaces are affected either by cable sagging or by a very low end-effector stiffness, both causing positioning errors. With lightweight cables, the very low stiffness yields disturbing vibrations. In this paper, we address the problem of decoupled active canceling of those vibrations in the modal space. In modal space, vibrations are decomposed in orthogonal signals which allows to use simple SISO control methods to build an active vibration canceling algorithm for the end-effector. As the modal space depends on the end-effector position, better performances are achieved if the controller is tuned for the current robot position. The proposed method is tested both on a realistic simulation and on a 8-cables and 6-degrees of freedom robot.

Cable-driven parallel robots allow for fast motions and huge workspaces, using relatively lightweight moving masses and low-power actuation. This kind of structure yields usually very cost-effective solutions. However, the wider the workspace, the lower the equivalent stiffness of the end-effector yielding inaccuracies due mainly to unwanted vibrations. In this paper, we propose a new approach to compensate for these vibrations. Reaction wheels are used to cancel rotational oscillations of the platform. A planar cable-driven robot built with cheap and lightweight Lego Mindstorms parts is used to validate the concept.

When using a camera as a position sensor, the measurement is limited in bandwidth, mainly due to the blur effects. The knowledge of an accurate model of the camera is then necessary to reconstruct the trajectory from the measurements given by the camera. This paper deals with the reconstruction of the continuous-time trajectory from the discrete-time measurements provided by the camera and shows the improvement obtained by using an accurate camera model. In the proposed methodology, a Kalman filter is used for the data fusion between the model and the measurement. The tuning and implementation of the filter are discussed in the specific context of the camera measurement. The system is evaluated in the context of a biomedical application: the reconstruction of the movement of a beating-heart.

Visual servoing refers to the closed-loop position control of the robot end-effector (Hutchinson et al., 1996) using visual feedback and should be distinguished from vision-based expert systems (Corke and Good, 1996). In this work, we focus our interest on high performance visual servoing. Our goal is to maximize the bandwidth of the visual loop. This means usually, considering the average dynamics of robots, that the use of a high speed camera is necessary. To achieve this goal, the model of the visual loop must be known with a good accuracy. This includes the dynamics of the robot and the dynamics of the vision system. The main objective of this work is to propose a new dynamic model for the vision sensor. The proposed model is validated by experiments. Ultrasonic motors are used in the experiments since they exhibit a very short response time and can be modeled by a simple transfer function, thus simplifying the decoupling between vision and actuation.

In this paper is considered fast visual servoing of a two-links arm including flexibilities for compensation of heart movements in surgery. The flexibilities are globally identified with no additional sensor than the external-500 Hz camera used in the visual servoing loop. The obtained model is valid around the working position of the arm and can be easily modified for new positions of the camera. Two control strategies to handle flexibilities and achieve high bandwidth are implemented: Generalized Predictive Control (GPC) and H∞ control. Simulation and experimental results are given allowing to compare their efficiencies.