Alessandro De Luca

A depth space approach to human-robot collision avoidance

In this paper a real-time collision avoidance approach is presented for safe human-robot coexistence. The main contribution is a fast method to evaluate distances between the robot and possibly moving obstacles (including humans), based on the concept of depth space. The distances are used to generate repulsive vectors that are used to control the robot while executing a generic motion task. The repulsive vectors can also take advantage of an estimation of the obstacle velocity. In order to preserve the execution of a Cartesian task with a redundant manipulator, a simple collision avoidance algorithm has been implemented where different reaction behaviors are set up for the end-effector and for other control points along the robot structure. The complete collision avoidance framework, from perception of the environment to joint-level robot control, is presented for a 7-dof KUKA Light-Weight-Robot IV using the Microsoft Kinect sensor. Experimental results are reported for dynamic environments with obstacles and a human.

Robots with Flexible Elements

Design issues, dynamic modeling, trajectory planning, and feedback control problems are presented for robot manipulators having components with mechanical flexibility, either concentrated at the joints or distributed along the links. The chapter is divided accordingly into two main parts. Similarities or differences between the two types of flexibility are pointed out wherever appropriate.

Motion control of redundant robots under joint constraints: Saturation in the Null Space

We present a novel efficient method addressing the inverse differential kinematics problem for redundant manipulators in the presence of different hard bounds (joint range, velocity, and acceleration limits) on the joint space motion. The proposed SNS (Saturation in the Null Space) iterative algorithm proceeds by successively discarding the use of joints that would exceed their motion bounds when using the minimum norm solution and reintroducing them at a saturated level by means of a projection in a suitable null space. The method is first defined at the velocity level and then moved to the acceleration level, so as to avoid joint velocity discontinuities due to the switching of saturated joints. Moreover, the algorithm includes an optimal task scaling in case the desired task trajectory is unfeasible under the given joint bounds. We also propose the integration of obstacle avoidance in the Cartesian space by properly modifying on line the joint bounds. Simulation and experimental results reported for the 7-dof lightweight KUKA LWR IV robot illustrate the properties and computational efficiency of the method.

Nonlinear decoupled motion-stiffness control and collision detection/reaction for the VSA-II variable stiffness device

Variable Stiffness Actuation (VSA) devices are being used to jointly address the issues of safety and performance in physical human-robot interaction. With reference to the VSA-II prototype, we present a feedback linearization approach that allows the simultaneous decoupling and accurate tracking of motion and stiffness reference profiles. The operative condition that avoids control singularities is characterized. Moreover, a momentum-based collision detection scheme is introduced, which does not require joint torque sensing nor information on the time-varying stiffness of the device. Based on the residual signal, a collision reaction strategy is presented that takes advantage of the proposed nonlinear control to rapidly let the arm bounce away after detecting the impact, while limiting contact forces through a sudden reduction of the stiffness. Simulations results are reported to illustrate the performance and robustness of the overall approach. Extensions to the multidof case of robot manipulators equipped with VSA-II devices are also considered.

Human-robot physical interaction and collaboration using an industrial robot with a closed control architecture

In physical Human-Robot Interaction, the basic problem of fast detection and safe robot reaction to unexpected collisions has been addressed successfully on advanced research robots that are torque controlled, possibly equipped with joint torque sensors, and for which an accurate dynamic model is available. In this paper, an end-user approach to collision detection and reaction is presented for an industrial manipulator having a closed control architecture and no additional sensors. The proposed detection and reaction schemes have minimal requirements: only the outer joint velocity reference to the robot manufacturers controller is used, together with the available measurements of motor currents and joint positions. No a priori information on the robot dynamic model and existing low-level joint controllers is strictly needed. A suitable on-line processing of the motor currents allows to distinguish between accidental collisions and intended human-robot contacts, so as to switch the robot to a collaboration mode when needed. Two examples of reaction schemes for collaboration are presented, with the user pushing/pulling the robot at any point of its structure (e.g., for manual guidance) or with a compliant-like robot behavior in response to forces applied by the human. The actual performance of the methods is illustrated through experiments on a KUKA KR5 manipulator.

A modified newton-euler method for dynamic computations in robot fault detection and control

We present a modified recursive Newton-Euler method for computing some dynamic expressions that arise in two problems of fault detection and control of serial robot manipulators, and which cannot be evaluated numerically using the standard method. The two motivating problems are: i) the computation of the residual vector that allows accurate detection of actuator faults or unexpected collisions using only robot proprioceptive measurements, and ii) the evaluation of a passivity-based trajectory tracking control law. The modified Newton-Euler algorithm generates factorization matrices of the Coriolis and centrifugal terms that satisfy the skew-symmetric property. The computational advantages with respect to numerical evaluation of symbolically obtained dynamic expressions is illustrated on a 7R DLR lightweight manipulato

Control of generalized contact motion and force in physical human-robot interaction

During human-robot interaction tasks, a human may physically touch a robot and engage in a collaboration phase with exchange of contact forces and/or requiring coordinated motion of a common contact point. Under the premise of keeping the interaction safe, the robot controller should impose a desired motion/force behavior at the contact or explicitly regulate the contact forces. Since intentional contacts may occur anywhere along the robot structure, the ability of controlling generalized contact motion and force becomes an essential robot feature. In our recent work, we have shown how to estimate contact forces without an explicit force sensing device, relying on residual signals to detect contact and on the use of an external (depth) sensor to localize the contact point. Based on this result, we introduce two control schemes that generalize the impedance and direct force control paradigms to a generic contact location on the robot, making use of the estimated contact forces. The issue of human-robot task compatibility is pointed out in case of control of generalized contact forces. Experimental results are presented for a KUKA LWR robot using a Kinect sensor.

Estimation of contact forces using a virtual force sensor

Physical human-robot collaboration is characterized by a suitable exchange of contact forces between human and robot, which can occur in general at any point along the robot structure. If the contact location and the exchanged forces were known in real time, a safe and controlled collaboration could be established. We present a novel approach that allows localizing the contact between a robot and human parts with a depth camera, while determining in parallel the joint torques generated by the physical interaction using the so-called residual method. The combination of such exteroceptive sensing and model-based techniques is sufficient, under suitable conditions, for a reliable estimation of the actual exchanged force at the contact, realizing thus a virtual force sensor. Multiple contacts can be handled as well. We validate quantitatively the proposed estimation method with a number of static experiments on a KUKA LWR. An illustration of the use of estimated contact forces in the realization of collaborative behaviors is given, reporting preliminary experiments on a generalized admittance control scheme at the contact point.

On-line estimation of variable stiffness in flexible robot joints

Variable stiffness actuators (VSAs) are currently explored as a new actuation approach to increase safety in physical human–robot interaction (pHRI) and improve dynamic performance of robots. For control purposes, accurate knowledge is needed of the varying stiffness at the robot joints, which is not directly measurable, nonlinearly depending on transmission deformation, and uncertain to be modeled. We address the online estimation of transmission stiffness in robots driven by VSAs in antagonistic or serial configuration, without the need for joint torque sensing. The two-stage approach combines (i) a residual-based estimator of the torque at the flexible transmission, and (ii) a recursive least squares stiffness estimator based on a parametric model. Further design refinements guarantee a robust behavior in the lack of velocity measures and in poor excitation conditions. The proposed stiffness estimation can be easily extended to multi-degree-of-freedom (multi-DOF) robots in a decentralized way, using only local motor and link position measurements. The method is tested through extensive simulations on the VSA-II device of the University of Pisa and on the Actuator with Adjustable Stiffness (AwAS) of IIT. Experiments on the AwAS platform validate the approach.

A PD-type regulator with exact gravity cancellation for robots with flexible joints

We present a new control approach to regulation tasks for robots with elastic joints in the presence of gravity. The control law combines a term that cancels the gravity effects on the robot link dynamics with a PD-type error feedback on the motor variables. The first control component follows from the feedback equivalence principle when imposing to the link variables the same dynamic behavior as if gravity were absent. The PD component can then be designed in a rather straightforward way. Global asymptotic stability is shown via Lyapunov analysis, without the need of strictly positive lower bounds neither on the proportional control gain nor on the structural joint stiffness. The control approach is also extended to the case of robot joints with nonlinear stiffness.