A novel kinematically redundant ($6+3$) -DoF parallel robot is presented in this paper. Three identical 3-DoF RU/2-RUS legs are attached to a configurable platform through spherical joints. With the selected leg mechanism, the motors are mounted at the base, reducing the reflected inertia. The robot is intended to be actuated with direct-drive motors in order to perform intuitive physical human-robot interaction. The design of the leg mechanism maximizes the workspace in which the end-effector of the leg can have a 2g acceleration in all directions. All singularities of the leg mechanism are identified under a simplifying assumption. A CAD model of the (6+3)-DoF robot is presented in order to illustrate the preliminary design of the robot.

Robots need to adapt their behaviour while physically interacting with an operator to guarantee safety and provide intuitiveness. Inferring the intentions of the operator is a challenging problem that can be addressed by introducing sensors, in addition to motor encoders. Also, kinematic redundancy can be used to avoid issues such as singularities or mechanical interference, and the redundant coordinates can be controlled freely. In this work, we propose to use the redundant degrees of freedom to infer the intentions of an operator interacting with a backdrivable kinematically redundant parallel robot, without introducing any additional sensors. The proposed approach is based on the fact that, in mechanically backdrivable robots, the operator can control the redundant degrees of freedom, and this can be sensed using solely motor encoders through the solution of the forward kinematics. This approach is implemented to switch between a position controller and a controller that allows the operator to guide the robot freely thanks to gravity compensation. Experiments are carried out to compare this approach with an existing one and show that it improves intuitiveness during interaction by reducing false mode change detections.

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.