Safe Human Robot Research Articles

Development of a Safety- and Energy-Aware Impedance Controller for Collaborative Robots

In contexts where robots share their workspace with humans, safety is of utmost importance. Consequently, in recent years, a big impulse has been given to the design of human-friendly robots by involving both mechanical and control design aspects. Regarding controller design, this often involves introducing compliance and ensuring asymptotic stability using an interaction control scheme and passivity theory. Moreover, when human operators physically interact with the robot during work, strict safety measures become necessary with some of these including power and force limitations [1]. In this letter, a novel impedance control technique for collaborative robots is presented. The featured controller allows a safe human–robot interaction through energy and power limitations, assuring passivity through energy tanks. The proposed controller is evaluated with a KUKA LWR 4+ arm in a comanipulation environment.

Position-Force Domain Passivity of the Human Arm in Telerobotic Systems

In order to guarantee safe human–robot interaction in single-master/single-slave teleoperation systems, passivity-based controllers have traditionally been developed for communication delay compensation in the velocity-force domain (VD) with the assumption of passivity of the human arm. The same controllers can also make the delayed communication channel passive in the position-force domain (PD), which provides a convenient position-drift-free control strategy for more complicated scenarios such as multi-master/single-slave systems. This would, however, only work if the operator's arm also remains passive in the PD. Whether the arm remains passive in the PD is a critical question yet to be answered. In this paper, passivity of the human arm in the PD is investigated through mathematical analysis, experimentation, and statistical user studies involving 12 subjects and 48 trials. It is shown that unlike in the VD, the human operator will not remain passive in the PD for all frequency ranges. This implies the need for appropriate control strategies to make the human operator termination passive in the PD. For future design of suitable controllers, statistical analyses are performed to investigate correlations between the levels of PD passivity of the left and the right arms of the human participants, as well as the levels of passivity of the subjects’ arms and their physical characteristics, e.g., weight, height, and body mass index. Possible control strategies through which the passivity of the operator termination can be guaranteed are also discussed.

Multiobjective Optimization for Stiffness and Position Control in a Soft Robot Arm Module

The central concept of this letter is to develop an assistive manipulator that can automate the bathing task for elderly citizens. We propose to exploit principles of soft robotic technologies to design and control a compliant system to ensure safe human–robot interaction, a primary requirement for the task. The overall system is intended to be modular with a proximal segment that provides structural integrity to overcome gravitational challenges and a distal segment to perform the main bathing activities. The focus of this letter is on the design and control of the latter module. The design comprises of alternating tendons and pneumatics in a radial arrangement, which enables elongation, contraction, and omnidirectional bending. Additionally, a synergetic coactivation of cables and tendons in a given configuration allows for stiffness modulation, which is necessary to facilitate washing and scrubbing. The novelty of the work is twofold: 1) Three base cases of antagonistic actuation are identified that enable stiffness variation. Each category is then experimentally characterized by the application of an external force that imposes a linear displacement at the tip in both axial and lateral directions. 2) The development of a novel algorithm based on cooperative multiagent reinforcement learning that simultaneously optimizes stiffness and position. The results highlight the effectiveness of the design and control to contribute toward the development of the assistive device.

Anthropomorphic Low-Inertia High-Stiffness Manipulator for High-Speed Safe Interaction

In this paper, a manipulator is proposed for safe human–robot interaction at high speed. The manipulator has both low mass and inertia and high stiffness and strength. It is basically a cable-driven manipulator; nevertheless, by using a unique lightweight tension-amplification mechanism, the manipulator retains high stiffness and strength. The joint stiffness, which is strongly related to the motion control performance, is amplified by the quadratic order. Both 1-degree of freedom (DOF) and 3-DOF joint mechanisms using the tension-amplification mechanism are presented and combined to develop a 7-DOF anthropomorphic manipulator named LIMS. The mass and inertia beyond the shoulder were 2.24 kg and 0.599 kg·m2, respectively, which are lower than those of a human. The stiffness of the developed elbow joint was 1410 N·m/rad, which is approximately seven times higher than that of a human. Considering the ratio of stiffness to inertia, the manipulator is expected to show a control performance that is comparable to those of conventional industrial manipulators. Comprehensive experiments, including joint stiffness tests and high-speed interaction tests, were conducted to verify the feasibility of the developed manipulator.

Invariance Control for Safe Human–Robot Interaction in Dynamic Environments

In human–robot interaction, it is essential to ensure that the robot poses no threat to the human. Especially in applications that require close or physical interaction, e.g., collaborative manufacturing or rehabilitation, the danger emanating from the robot has to be minimized. Control schemes introducing virtual constraints have proven valuable in this context since they allow us to define a safe zone to move in without endangering the human. Combining the different requirements on the control scheme, such as real-time capability, stability, and reliability, in the presence of external disturbances and dynamic limits, however, turns out to be challenging. In this paper, we present a novel control scheme for human–robot interaction, which enforces dynamic constraints even in the presence of external forces. Based on an analytic constraint description and a feedback linearization of the system dynamics, a safe set of states is determined, which is then rendered controlled positively invariant, thus keeping the system in a safe configuration. The controlled system is analyzed with respect to invariance and boundedness with the results being illustrated in a full-scale experiment.

Safe Human–Robot Interaction in Medical Robotics: A case study on Robotic Fracture Surgery System

This paper presents a safety analysis of a Robotic Fracture Surgery System using the Systems-Theoretic Process Analysis (STPA). It focuses particularly on hazards caused by the human in the loop. The robotic system and operating staff are modeled including information flow between different components of the system. The analysis has generated a set of requirements for the system design that can ultimately mitigate the identified hazards, as well as a preliminary set of human factors that can improve safety.

Towards the development of a soft manipulator as an assistive robot for personal care of elderly people

Manipulators based on soft robotic technologies exhibit compliance and dexterity which ensures safe human–robot interaction. This article is a novel attempt at exploiting these desirable properties to develop a manipulator for an assistive application, in particular, a shower arm to assist the elderly in the bathing task. The overall vision for the soft manipulator is to concatenate three modules in a serial manner such that (i) the proximal segment is made up of cable-based actuation to compensate for gravitational effects and (ii) the central and distal segments are made up of hybrid actuation to autonomously reach delicate body parts to perform the main tasks related to bathing. The role of the latter modules is crucial to the application of the system in the bathing task; however, it is a nontrivial challenge to develop a robust and controllable hybrid actuated system with advanced manipulation capabilities and hence, the focus of this article. We first introduce our design and experimentally characterize its functionalities, which include elongation, shortening, omnidirectional bending. Next, we propose a control concept capable of solving the inverse kinetics problem using multiagent reinforcement learning to exploit these functionalities despite high dimensionality and redundancy. We demonstrate the effectiveness of the design and control of this module by demonstrating an open-loop task space control where it successfully moves through an asymmetric 3-D trajectory sampled at 12 points with an average reaching accuracy of 0.79 cm ± 0.18 cm. Our quantitative experimental results present a promising step toward the development of the soft manipulator eventually contributing to the advancement of soft robotics.

Minimum Distance Calculation for Safe Human Robot Interaction

The ability of efficient and fast calculation of the minimum distance between humans and robots is vitally important for realizing a safe human robot interaction (HRI), where robots and human co-workers share the same workspace. The minimum distance is the main input for most of collision avoidance methods, HRI, robot decision making, as well as robot navigation. In this study it is presented a novel methodology to analytically compute of the minimum distance between cylindrical primitives with spherical ends. Such primitives are very important since that there geometrical shape is suitable for representing the co-worker and the robots structures. The computational cost of the minimum distance between n cylinders is of order O(n2). In this study QR factorization is proposed to achieve the computational efficiency in calculating the minimum distance mutually between each pair of cylinders. Experimental tests demonstrated the effectiveness of the proposed approach.

Working Together: A Review on Safe Human-Robot Collaboration in Industrial Environments

After many years of rigid conventional procedures of production, industrial manufacturing is going through a process of change toward flexible and intelligent manufacturing, the so-called Industry 4.0. In this paper, human–robot collaboration has an important role in smart factories since it contributes to the achievement of higher productivity and greater efficiency. However, this evolution means breaking with the established safety procedures as the separation of workspaces between robot and human is removed. These changes are reflected in safety standards related to industrial robotics since the last decade, and have led to the development of a wide field of research focusing on the prevention of human–robot impacts and/or the minimization of related risks or their consequences. This paper presents a review of the main safety systems that have been proposed and applied in industrial robotic environments that contribute to the achievement of safe collaborative human–robot work. Additionally, a review is provided of the current regulations along with new concepts that have been introduced in them. The discussion presented in this paper includes multi-disciplinary approaches, such as techniques for estimation and the evaluation of injuries in human–robot collisions, mechanical and software devices designed to minimize the consequences of human–robot impact, impact detection systems, and strategies to prevent collisions or minimize their consequences when they occur.

Active collision avoidance for human–robot collaboration driven by vision sensors

Establishing safe human–robot collaboration is an essential factor for improving efficiency and flexibility in today’s manufacturing environment. Targeting safety in human–robot collaboration, this paper reports a novel approach for effective online collision avoidance in an augmented environment, where virtual three-dimensional (3D) models of robots and real images of human operators from depth cameras are used for monitoring and collision detection. A prototype system is developed and linked to industrial robot controllers for adaptive robot control, without the need of programming by the operators. The result of collision detection reveals four safety strategies: the system can alert an operator, stop a robot, move away the robot, or modify the robot’s trajectory away from an approaching operator. These strategies can be activated based on the operator’s existence and location with respect to the robot. The case study of the research further discusses the possibility of implementing the developed method in realistic applications, for example, collaboration between robots and humans in an assembly line.

A computationally efficient safety assessment for collaborative robotics applications

Safety during interaction with unstructured and dynamic environments is now a well established requirement for complex robotic systems. A wide variety of approaches focus on the introduction of safety evaluation methods in order to shape a consequent safety-oriented control strategy, able to reactively prevent collisions between the robot and potential obstacles, including a human being. This paper presents a new safety assessment, named kinetostatic safety field, that captures the risk in the vicinity of an arbitrary rigid body “source of danger” (e.g. an obstacle, a human body part or a robot link) moving in R3. The safety field depends on the position and velocity of the body but it is also influenced by its real shape and size, exploiting its triangular mesh. The introduction of a body-fixed reference frame in the definition of the field provides closed form computability and an effective computation time reduction, that allows for real-time applications. In particular, intensive computations, connected to the specific body geometry, can be performed only once and off-line, ensuring a fast and constant on-line computation time, independently of the number of mesh elements. Furthermore, we combine the safety field concept with a safety-oriented reactive control strategy for redundant manipulators. Our approach allows to enhance safety in several real-time collision avoidance scenarios, including collision avoidance with potential obstacles, self-collision avoidance and safe human–robot coexistence. The proposed control strategy is validated through experiments performed on an ABB FRIDA dual arm robot.

Joint configuration for physically safe human–robot interaction of serial-chain manipulators

Manipulators with a series of revolute joints usually have more than 6-DoFs from the shoulder to the wrist to conduct miscellaneous tasks for humans. To add physical interaction or safety to manipulators, functions of compliance or safety components are implemented to joints or links of manipulators. However, a physical interaction by a collision may occur anywhere from the base to the end-effector of the manipulators. If a collision occurs at upper link, which has relatively fewer-DoFs joints, an external force may not be transmitted to the respective joints and links properly. Therefore, a study of the overall joint configurations for manipulators is necessary. This paper suggests a simplified methodology for joint configurations of manipulators using two types of revolute joints, rotational (type R) or twist (type T) joints. When an external force is applied to the link attached to these joints, the characteristics of torque transmission are described. Then, optimal joint configurations at the shoulder joint of 2- or 3-DoFs are described for physical interaction to manipulators. Experimental results followed by the scenario from pre-collision to collision show that joint configurations affect the safety performance of the manipulator.

Sociological and Biological Insights on How to Prevent the Reduction in Cognitive Activity that Stems from Robots Assuming Workloads in Human–Robot Cooperation

The reduction of cognitive tasks brought about by new developments in service-robots’ collaboration with humans in working environments has given rise to new challenges as to how to address safety issues. This paper presents insights from biology, cognitive/neural sciences and sociology that can conquer these new challenges. The main focus lies in sociological variables that ensure safe human–robot interaction in working environments rather than addressing biological ones (avoiding bodily harm) or purely cognitive ones (avoiding any signals that are outside the human’s sensory comfort zones). We will present an approach on how to integrate behavioral patterns into the robotic system in order to prevent the problem of reduced cognition in relation to essential features, which are necessary for carrying out this pattern in the context of a human–robot interaction with non-humanoid robots (which is the most typical design of robots used in work environments).

Mechanical design and evaluation of a compact portable knee–ankle–foot robot for gait rehabilitation

This paper presents the mechanical design and evaluation of a knee–ankle–foot robot, which is compact, modular and portable for stroke patients to carry out overground gait training at outpatient and home settings. A novel compact series elastic actuator (SEA) is developed for safe human–robot interactions. As a solution to the limitation of conventional SEA designs, one low-stiffness translational spring and a high-stiffness torsion spring are placed in series for force transmission. The springs are selected based on gait biomechanics to maintain a high intrinsic compliance for most period of a gait cycle, while retaining the capacity to provide the peak force. To achieve portability, the robotic joint mechanism is optimized based on gait biomechanics, and the mechanical structure is built with lightweight materials. This robot demonstrates stable and accurate force control in experiments conducted on healthy subjects with overground walking. The activation level of the major leg muscles of subjects is reduced as indicated by the EMG signals and the normal gait pattern is maintained during the test, which demonstrates that the robot can provide effective assistive force to the subjects during overground walking.

Practical relevance of faults, diagnosis methods, and tolerance measures in elastically actuated robots

Elastically actuated robots promise safe human–robot interaction and energy-efficient motions. Yet, increased complexity and critical operation states might increase the practical fault risk. This paper explores faults in such robots using expert data from the field and identifies components that show increased fault occurrence: the highest fault sensitivity occurs in kinematics, electronics, sensors, and software. Since elastic actuators are an active field of research, few cases of industrial application exist and thus most experts in this study have academic background. Beyond assessing fault sensitivity, countermeasures such as redundant design are compiled. A brief literature review discusses fault diagnosis and fault-tolerant design with respect to these insights. Despite the availability of a few promising methods in robotics, neither diagnosis nor tolerance do receive sufficient recognition leaving potential for practical application.

Time-of-flight-assisted Kinect camera-based people detection for intuitive human robot cooperation in the surgical operating room.

Scene supervision is a major tool to make medical robots safer and more intuitive. The paper shows an approach to efficiently use 3D cameras within the surgical operating room to enable for safe human robot interaction and action perception. Additionally the presented approach aims to make 3D camera-based scene supervision more reliable and accurate. A camera system composed of multiple Kinect and time-of-flight cameras has been designed, implemented and calibrated. Calibration and object detection as well as people tracking methods have been designed and evaluated. The camera system shows a good registration accuracy of 0.05m. The tracking of humans is reliable and accurate and has been evaluated in an experimental setup using operating clothing. The robot detection shows an error of around 0.04m. The robustness and accuracy of the approach allow for an integration into modern operating room. The data output can be used directly for situation and workflow detection as well as collision avoidance.

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

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.

Full-body collision detection and reaction with omnidirectional mobile platforms: a step towards safe human–robot interaction

In this paper, we develop estimation and control methods for quickly reacting to collisions between omnidirectional mobile platforms and their environment. To enable the full-body detection of external forces, we use torque sensors located in the robot’s drivetrain. Using model based techniques we estimate, with good precision, the location, direction, and magnitude of collision forces, and we develop an admittance controller that achieves a low effective mass in reaction to them. For experimental testing, we use a facility containing a calibrated collision dummy and our holonomic mobile platform. We subsequently explore collisions with the dummy colliding against a stationary base and the base colliding against a stationary dummy. Overall, we accomplish fast reaction times and a reduction of impact forces. A proof of concept experiment presents various parts of the mobile platform, including the wheels, colliding safely with humans.

A Proactive Strategy for Safe Human-Robot Collaboration based on a Simplified Risk Analysis

In an increasing demand for human-robot collaboration systems, the need for safe robots is crucial. This paper presents a proactive strategy to enable an awareness of the current risk for the robot. The awareness is based upon a map of historically occupied space by the operator. The map is built based on a risk evaluation of each pose presented by the operator. The risk evaluation results in a risk eld that can be used to evaluate the risk of a collaborative task. Based on this risk eld, a control algorithm that constantly reduces the current risk within its task constraints was developed. Kinematic redundancy was exploited for simultaneous task performance within task constraints, and risk minimization. Sphere-based geometric models were used both for the human and robot. The strategy was tested in simulation, and implemented and experimentally tested on a NACHI MR20 7-axes industrial robot.

A Novel 3D Camera Based Supervision System for Safe Human-Robot Interaction in the Operating Room

A Novel 3D Camera Based Supervision System for Safe Human-Robot Interaction in the Operating Room