Safe physical human-robot interaction with industrial dual-arm robots

In the immediate future, metrics related to safety and dependability have to be found in order to successfully introduce robots in everyday environments. The crucial issues needed to tackle the problem of a safe and dependable physical human-robot interaction (pHRI) were addressed in the EURON Perspective Research Project PHRIDOM (Physical Human-Robot Interaction in Anthropic Domains), aimed at charting the new "territory" of pHRI. While there are certainly also "cognitive" issues involved, due to the human perception of the robot (and vice versa), and other objective metrics related to fault detection and isolation, the discussion in this paper will focus on the peculiar aspects of "physical" interaction with robots. In particular, safety and dependability will be the underlying evaluation criteria for mechanical design, actuation, and control architectures. Mechanical and control issues will be discussed with emphasis on techniques that provide safety in an intrinsic way or by means of control components. Attention will be devoted to dependability, mainly related to sensors, control architectures, and fault handling and tolerance. After PHRIDOM, a novel research project has been launched under the Information Society Technologies Sixth Framework Programme of the European Commission. This "Specific Targeted Research or Innovation" project is dedicated to "Physical Human-Robot Interaction: depENDability and Safety" (PHRIENDS). PHRIENDS is about developing key components of the next generation of robots, including industrial robots and assist devices, designed to share the environment and to physically interact with people. The philosophy of the project proposes an integrated approach to the co-design of robots for safe physical interaction with humans, which revolutionizes the classical approach for designing industrial robots - rigid design for accuracy, active control for safety - by creating a new paradigm: design robots that are intrinsically safe, and control them to deliver performance. This paper presents the state of the art in the field as surveyed by the PHRIDOM project, as well as it enlightens a number of challenges that will be undertaken within the PHRIENDS project.

The presented research work introduces the safe limitation of contact forces between an industrial robot and its human operator during physical collaboration. While estimating these contact forces with a physics algorithm in the robot control software, they can be easily limited before getting harmful. The developed algorithms allow the user to stop and move the robot arm with moderate effort and therefore he feels safe during interaction. Through bypassing and redesigning the position feed-back controllers of the robot, the drive output torques can be held under the critical threshold calculated via Newton-Euler dynamics.Keywordshuman-robot interactionrobot safetycontrol algorithms

Over the last decade, safe physical Human-Robot Interaction (pHRI) has been made possible due to significant advances in mechatronics, control, and planning. One result of these developments were fully integrated safer lightweight robots that are equipped with sophisticated interaction control capabilities. These new robots have even opened up novel and unforeseen application domains, in which human and robot are sought to work and interact with each other. For this, safe physical interaction is prime. This chapter gives a brief overview on two of its central aspects: human safety from an injury and standards standpoint, and control for physical interaction with focus on interaction control and collision handling.

With the advancement of the motion control of industrial robots in recent years, a method that can easily measure the accuracy of the synchronous control of a two-axis dual-arm robot is desired. Therefore, in this study, we propose a new measurement method that creates a ball rolling motion in a circular orbit on a work plate and uses the rolling motion error with respect to the reference circle. In addition, industrial robots in the field are always forced to operate continuously for a long period of time, and they work with all kinds of loads overlapping and applying non-uniform loads. In this study, we propose a new measurement method that creates a rolling motion of a ball on a circular track on a work plate and uses the error of the rolling motion relative to a reference circle. In particular, in order to elucidate the motion error during long-time continuous operation under high load, we approached the problem from the viewpoint of joint temperature and power consumption. As a result, we found that the ball trajectory error was caused by an increase in the temperature of the elbow and wrist motors, which increased the joint load and caused an angular error in the plate. Even when non-uniform loads were applied, the circular trajectory could be corrected by making corrections according to the temperature at each arm. The tendency of the angle error due to the temperature rise and the increase in joint load of each joint was found, and it was found that it was possible to correct the angle error by FF control.

Providing contact sensing on the whole body of a robot is a key feature to increase the safety level of physical human-robot interaction. In this paper, a new robot skin capable of sensing multiple contact locations is presented. The motivation behind the proposed design is to produce a relatively inexpensive skin having the capability to provide the spatial location of collisions and also to add compliance to the robot's external cover. The resulting device is a thin flexible sensor sheet made of polyimide films with electrically conductive ink and a pressure sensitive conductive rubber sheet. The problem of internal wire routing is circumvented by the use of conductive ink and a circuit is proposed to minimize the number of output wires. To provide collision absorption and mechanical robustness, the sensor is embedded in different layers of polyurethane using shape deposition manufacturing (SDM). The paper presents the design and the fabrication process of the skin but also some experimental results on the determination of the mechanical properties of the resulting sensor as well as its potential for increasing human safety during human robot interaction.

A safe physical human-robot interaction (pHRI) in rehabilitation requires reliable perception and low-latency decision making under heterogeneous and unreliable sensor inputs. This paper presents a multimodal sensor-fusion-based safety framework that integrates physical state estimation, semantic information fusion, and an edge-deployed large language model (LLM) for real-time pHRI safety control. A dynamics-based virtual sensing method is introduced to estimate internal joint torques from external force-torque measurements, achieving a normalized mean absolute error of 18.5% in real-world experiments. An asynchronous semantic state pool with a time-to-live mechanism is designed to fuse visual, force, posture, and human semantic cues while maintaining robustness to sensor delays and dropouts. Based on structured multimodal tokens, an instruction-tuned edge LLM outputs discrete safety decisions that are further mapped to continuous compliant control parameters. The framework is trained using a hybrid dataset consisting of limited real-world samples and LLM-augmented synthetic data, and evaluated on unseen real and mixed-condition scenarios. Experimental results show reliable detection of safety-critical events with a low emergency misdetection rate, while maintaining an end-to-end decision latency of approximately 223 ms on edge hardware. Real-world experiments on a rehabilitation robot demonstrate effective responses to impacts, user instability, and visual occlusions, indicating the practical applicability of the proposed approach for real-time pHRI safety monitoring.

We review our research results on safe control of physical Human-Robot Interaction to handle collision detection/classification, co- existence in the workspace, and collaboration with intentional contacts or by visual coordination, using model-based techniques and real-time monitoring by sensors.

Recently, new needs have emerged to control not only linear motion but also rotational motion in high-accuracy manufacturing fields. Many five axiscontrolled machining centers are therefore in use. However, one problem has been that it may be difficult to achieve flexible manufacturing systems by methods based on the use of these machine tools. On the other hand, industrial dual-arm robots have gained attention as new tools to control both linear motion and rotational motion accurately, in the attempt to control a working plate like a machine tool table. In the present report, cooperative dual-arm motion is demonstrated to make it feasible to perform stable operation control, such as controlling the working plate to keep a ball rolling in a circular path on it. As a result, we investigated the influence of each axis motion error on a ball-rolling path.

Operating in the proximity of humans has been a long-term challenge in robotics research. To achieve this objective, one of the main issues is to ensure safe and comfortable physical human-robot interaction (pHRI). In this paper, we tackle the safety problem at the control level. To ensure operation is within perceived safe zone, we use model predictive control, which finds the optimal control signal online, while imposing predefined safety constraints on the robotic system. The strength of this method lies in allowing the system to perform close to, or at the edge of the constraints' boundaries. In contrast to other works we consider here perceived safety; the constraints for perceived safety are derived in a competitive pHRI experiment. The perceived safety and comfort of the proposed approach is then evaluated with a second, game-like pHRI experiment.

Safe physical human-robot interaction: A quasi whole-body sensing method based on novel laser-ranging sensor ring pairs

Intra-cardiac catheterization is an effective procedure for diagnosis and treatment of many cardiac disorders such as arrhythmia. The objective of the catheter manipulation is to accurately position the catheter tip at the target tissue on the endocardium and provide a stable contact force for a specific duration to the region of interest. However, this is a challenging task due to the high flexibility of the catheter, ineffective visualization and dynamic environment of the heart. Additionally, the catheter-tissue interaction force, that the procedure outcome highly depends on, is not known to the interventionalist during the catheterization. This thesis deals with improving the safety and effectiveness of the catheterization by making contributions to two main areas; catheter contact force estimation and automatic force/position control of a robotic catheter system. First, a quasi-static model of the planar catheter that predicts the catheter pose for the given actuation variables and external forces in the plane of catheter motion, is proposed. In the next step, the computational efficiency of the proposed model is utilized to develop an online approach for the estimation of the external force at the tip of a catheter based on the pose measurement. The proposed force estimation approach is also extended to 3D by developing an efficient model of the catheter that is derived by coupling the classical Cosserat rod model with a new model of the pull-wire actuation. Experiments performed using electromagnetic sensors verify the feasibility of the proposed schemes in medical applications. In the control area, a position control scheme for a robotic assisted manipulation system is proposed, using the experimentally obtained inverse kinematics that compensates for the non-smooth dynamics of the distal shaft bending mechanism. Compensation of the backlash behavior of the catheter due to its interaction with the surrounding veins is also incorporated in the control scheme. The proposed position controller is then adopted as the internal loop of a hybrid position/force controller that positions the catheter tip to the target tissue and simultaneously, regulates the contact force to a desired value. The viability of the proposed controllers is then verified through simulations and experiments.

Estimation of human impedance and motion intention for constrained human–robot interaction

Compliant robots with constant joint stiffness (Serial Elastic Actuators - SEA), on the contrary to ones with variable joint stiffness (Variable Stiffness Actuators – VSA), have limited capabilities for modulating robot mechanical impedance in the interaction task. However, in the case of kinematic redundancy in specific tasks, robots can exploit the null space to adjust End-Effector (EE) Cartesian stiffness. Thus, prior knowledge of the task path or the operational workspace can be used to pre-compute joint stiffness that can enable maximal ratio between maximal and minimal stiffness of the robot’s EE during the task execution, and therefore shape achievable EE stiffness to best fit the task execution. In that light, this paper elaborates on the preselection of joint stiffnesses which influences the achievable robot’s Cartesian stiffness in a specific task. Besides optimizing the available operational EE stiffness, by pre-computed joint stiffness values, the robot will be able to adapt better to specific tasks and provide a better framework for safe and efficient physical human-robot interaction. The paper presents an approach to the selection of predefined joint stiffness values of the 7-DOFs KUKA LWR, where joint stiffness is achieved/emulated with torque feedback. In the simulation experiments, the approach is depicted in the preselection of two joint stiffness values within the prescribed range, while other joint stiffness is set constant.

In the factories and distribution centers of the future, humans and robots shall work together in close proximity and even physically interact. This shift to joint human–robot teams raises the question of how to ensure worker safety. In this manuscript, we present a novel episodic memory system for safety-aware robots. Using this system, the robots can answer questions about their actions at the level of safety concepts. We built this system as an extension of the KnowRob framework and its notion of episodic memories. We evaluated the system in a safe physical human–robot interaction (pHRI) experiment, in which a robot had to sort surgical instruments while also ensuring the safety of its human co-workers. Our experimental results show the efficacy of the system to act as a robot’s belief state for online reasoning, as well as its ability to support offline safety analysis through its fast and flexible query interface. To this end, we demonstrate the system’s ability to reconstruct its geometric environment, course of action, and motion parameters from descriptions of safety-relevant events. We also show-case the system’s capability to conduct statistical analysis.

ABSTRACTDual-arm redundant robot systems are usually required to handle primary tasks, repetitively and synchronously in practical applications. In this paper, a jerk-level synchronous repetitive motion scheme is proposed to remedy the joint-angle drift phenomenon and achieve the synchronous control of a dual-arm redundant robot system. The proposed scheme is novelly resolved at jerk level, which makes the joint variables, i.e. joint angles, joint velocities and joint accelerations, smooth and bounded. In addition, two types of dynamics algorithms, i.e. gradient-type (G-type) and zeroing-type (Z-type) dynamics algorithms, for the design of repetitive motion variable vectors, are presented in detail with the corresponding circuit schematics. Subsequently, the proposed scheme is reformulated as two dynamical quadratic programs (DQPs) and further integrated into a unified DQP (UDQP) for the synchronous control of a dual-arm robot system. The optimal solution of the UDQP is found by the piecewise-linear projection equation neural network. Moreover, simulations and comparisons based on a six-degrees-of-freedom planar dual-arm redundant robot system substantiate the operation effectiveness and tracking accuracy of the robot system with the proposed scheme for repetitive motion and synchronous control.