Robot Control for Task Performance and Enhanced Safety under Impact

A control law combining motion performance quality and low stiffness reaction to unintended contacts is proposed in this work. It achieves prescribed performance evolution of the position error under disturbances up to a level related to model uncertainties and responds compliantly and with low stiffness to significant disturbances arising from impact forces. The controller employs a velocity reference signal in a model-based control law utilizing a non-linear time-dependent term, which embeds prescribed performance specifications and vanishes in case of significant disturbances. Simulation results with a three degrees of freedom (DOF) robot illustrate the motion performance and self-regulation of the output stiffness achieved by this controller under an external force, and highlights its advantages with respect to constant and switched impedance schemes. Experiments with a KUKA LWR4+ demonstrate its performance under impact with a human while following a desired trajectory

Human-robot coexistence and interaction in open industrial cells

Recent research results on human\u2013robot interaction and collaborative robotics are leaving behind the traditional paradigm of robots living in a separated space inside safety cages, allowing humans and robot to work together for completing an increasing number of complex industrial tasks. In this context, safety of the human operator is a main concern. In this paper, we present a framework for ensuring human safety in a robotic cell that allows human\u2013robot coexistence and dependable interaction. The framework is based on a layered control architecture that exploits an effective algorithm for online monitoring of relative human\u2013robot distance using depth sensors. This method allows to modify in real time the robot behavior depending on the user position, without limiting the operative robot workspace in a too conservative way. In order to guarantee redundancy and diversity at the safety level, additional certified laser scanners monitor human\u2013robot proximity in the cell and safe communication protocols and logical units are used for the smooth integration with an industrial software for safe low-level robot control. The implemented concept includes a smart human-machine interface to support in-process collaborative activities and for a contactless interaction with gesture recognition of operator commands. Coexistence and interaction are illustrated and tested in an industrial cell, in which a robot moves a tool that measures the quality of a polished metallic part while the operator performs a close evaluation of the same workpiece

Riistvarapaindlik ROSi tarkvarapakett tööstuslike robotite mööndlikuks juhtimiseks

Industrial robotics today is moving towards using lightweight collaborative robots to make it possible for small and medium sized enterprises to integrate robots in their manufacturing environment. However, there is still very few collaborative robots seen in the industry and the main reason is that programming of the robot is still too expensive and time-consuming, since there are too few ready solutions available today for controlling co-robots. The solution would be more available open source, maintainable, extendable and usable high-quality code for controlling co-robots. This thesis concentrates on developing such complete software bundle on ROS for compliant control for industrial collaborative manipulators

Social Robotics and Societies of Robots

The sustainability of social robotics, like other ambitious research programs, depends on the identification of lines of inquiry that are coherent with its visionary goals while satisfying more stringent constraints of feasibility and near-term payoffs. Within these constraints, this article outlines one line of inquiry that seems especially viable: development of a society of robots operating within the physical environments of everyday human life, developing rich robot–robot social exchanges, and yet, refraining from any physical contact with human beings. To pursue this line of inquiry effectively, sustained interactions between specialized research communities in robotics are needed. Notably, suitable robotic hand design and control principles must be adopted to achieve proper robotic manipulation of objects designed for human hands that one finds in human habitats. The Pisa-IIT SoftHand project promises to meet these manipulation needs by a principled combination of sensorimotor synergies and soft robotics actuation, which aims at capturing how the biomechanical structure and neural control strategies of the human hand interact so as to simplify and solve both control and sensing problems

Control of redundant robot arms with null-space compliance and singularity-free orientation representation

This paper tackles the problem of controlling the position and orientation, expressed in a singularity-free representation form, of the end-effector of a redundant robot, while addressing an active compliant behaviour within the null-space. The manuscript extends the work in [1] by explicitly addressing the orientation part. In order to successfully accomplish the task, a dynamic controller is designed without need of any exteroceptive sensors information. A rigorous stability analysis is provided to confirm the developed theory. Experiments are finally carried out to bolster the performance of the proposed approach

Autonomous Collision Avoidance Tradespace Analysis for High-Speed Vessels

In this work, a tradespace was introduced allowing a weighted combination of a course change and speed change when deviating from the preferred velocity vector in protocol - constrained autonomous collision avoidance algorithms. A novel iterative geometry testing technique was introduced and key evaluation metrics were studied including the introduction of a protocol - compliance metric for collision avoidance scenario s. The performance metric results differ ed for high - speed vessels indicating a need for parameter tuning specific to high - speed vessels before applying collision avoidance algorithms tested on slower vessels

On Blocking Collisions between People, Objects and other Robots

Intentional or unintentional contacts are bound to occur increasingly more often due to the deployment of autonomous systems in human environments. In this paper, we devise methods to computationally predict imminent collisions between objects, robots and people, and use an upper-body humanoid robot to block them if they are likely to happen. We employ statistical methods for effective collision prediction followed by sensor-based trajectory generation and real-time control to attempt to stop the likely collisions using the most favorable part of the blocking robot. We thoroughly investigate collisions in various types of experimental setups involving objects, robots, and people. Overall, the main contribution of this paper is to devise sensor-based prediction, trajectory generation and control processes for highly articulated robots to prevent collisions against people, and conduct numerous experiments to validate this approach

The Opportunities and Challenges of SME Manufacturing Automation: Safety and Ergonomics in Human–Robot Collaboration

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Shared control for natural motion and safety in hands-on robotic surgery

Hands-on robotic surgery is where the surgeon controls the tool's motion by applying forces and torques to the robot holding the tool, allowing the robot-environment interaction to be felt though the tool itself. To further improve results, shared control strategies are used to combine the strengths of the surgeon with those of the robot. One such strategy is active constraints, which prevent motion into regions deemed unsafe or unnecessary. While research in active constraints on rigid anatomy has been well-established, limited work on dynamic active constraints (DACs) for deformable soft tissue has been performed, particularly on strategies which handle multiple sensing modalities. In addition, attaching the tool to the robot imposes the end effector dynamics onto the surgeon, reducing dexterity and increasing fatigue. Current control policies on these systems only compensate for gravity, ignoring other dynamic effects. This thesis presents several research contributions to shared control in hands-on robotic surgery, which create a more natural motion for the surgeon and expand the usage of DACs to point clouds. A novel null-space based optimization technique has been developed which minimizes the end effector friction, mass, and inertia of redundant robots, creating a more natural motion, one which is closer to the feeling of the tool unattached to the robot. By operating in the null-space, the surgeon is left in full control of the procedure. A novel DACs approach has also been developed, which operates on point clouds. This allows its application to various sensing technologies, such as 3D cameras or CT scans and, therefore, various surgeries. Experimental validation in point-to-point motion trials and a virtual reality ultrasound scenario demonstrate a reduction in work when maneuvering the tool and improvements in accuracy and speed when performing virtual ultrasound scans. Overall, the results suggest that these techniques could increase the ease of use for the surgeon and improve patient safety.Open Acces