Human-Robot Collaboration in Automotive Industry

Human–Robot Collaboration is a new trend in the field of industrial and service. Application of human-robot-collaboration techniques in automotive industries has many advantages on productivity, production quality and workers’ ergonomic; however, workers’ safety aspects play the vital role during this collaboration. Previously, the machine is allowed to be at automatic work only if operators are out of its workspace but today collaborative robots provide the opportunity to establish the human robot cooperation. In this thesis, efforts have been made to present innovative solutions for using human-robot collaboration to develop a manufacturing cell. These solutions are not only used to facilitate the operator working with collaborative robots but also consider the worker safety and ergonomic. After proposing different solutions for improving the safety of operations during the collaboration with industrial robots, the efficiency of the solutions is tested in both laboratory and virtual environments. In this research, firstly, Analytic Hierarchy Process (AHP) has been used as a potential decision maker to prove the efficiency of human-robot collaboration system over the manual one. In the second step, detailed task decomposition has been done using Hierarchical Task Analysis (HTA) to allocate operational tasks to human and robot reducing the chance of duty interference. In the International Organization of Standardization's technical specification 15066 on collaborative robot safety four methodologies have been proposed to reduce the risk of injury in the work area. The four methods implied in ISO/TS 15066 are safety-rated monitored stop (SMS), hand-guided (HG), speed and separation monitoring (SSM) and power force limiting (PFL). SMS method reduces the risk of operator’s injury by stopping the robot motion whenever the operator is in the collaborative workspace. HG method reduces the chance of operator’s injury by providing the possibility of having control over the robot motion at all times in the workstation using emergency system or enabling device. The SSM method determines the minimum protective distance between a robot and an operator in the collaborative workspace, below which the robot will stop any kind of motion and PFL method reduces the momentum of a robot in a way that contact between an operator and the robot will not cause any injury. After determining the requirements and specifications of hybrid assembly cell, few of the above-mentioned methods for evaluating the safety of human-robot-collaboration procedure have been tasted in the laboratory environment. Due to the lack of safety camera (sensors) in the laboratory workstation, the ISO methods such as SSM, that needs sensors in the workstation, have been modeled in virtual environment to evaluate different scenario of human-robot-interaction and feasibility of the assembly process. Implementing different scenarios of ISO methods in hybrid assembly workstation not only improves the operator safety who is in interaction with the collaborative robot but also improves the worker ergonomic during the performing of repetitive heavy tasks

Impact Force Reduction Strategies To Achieve Safer Human-Robot Collisions

The increasing use of robots operating close to people has made human-robot collisions more likely. In this paper, strategies intended to reduce the impact force to a safe level, without sacrificing the robot’s performance, are investigated. The strategies can be applied to a robot arm without modifying its internal hardware. They include the existing strategies: lowering the actuator controller’s stiffness; actuator switched off upon impact detection; withdrawing the arm upon impact detection; and adding a compliant cover. We also propose the novel strategy of limiting the controller’s feedback term. The collision scenario studied is a robot arm colliding with a person’s constrained head. An improved lumped parameter model of the constrained impact is proposed. Simulation results are included for a UR5 collaborative robot. Sixteen combinations of the impact force reduction strategies are compared. The results show that using a high stiffness controller with a feedback limit and compliant cover reduces the impact force to a safe level, and achieves precise trajectory tracking

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 multidisciplinary 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

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

Motion-tracking skill assist and power assist for sinusoidal motions with a semi-active assist mechanism using energy control

This paper describes a skill assist method for sinusoidal motions using a semi-active assist mechanism through an energy control method. In a previous study, we had developed and verified the effectiveness of a power assist device with a semi-active assist mechanism and a control method for reducing loads during periodic motion. Here, we have developed a skill assist method as an extension of our power assist device for periodic motion. The skill of performing sinusoidal motions is defined in this study as an operator’s ability to track such motions. Therefore, our skill assist method attempts to improve the operator’s tracking ability. The proposed skill assist method is implemented using our previous power assist device; therefore, the device provides not only a power assist effect but also a skill assist effect to correct the motion. Hence, an operator obtains both the power and the skill assist effects simultaneously

ROBOTIC INTERACTION AND COOPERATION. Industrial and rehabilitative applications

The main goal of the thesis is the development of human-robotic interaction control strategies, which enable close collaboration between human and robot. In this framework we studied two di erent aspects, with applications respectively in industrial and rehabilitation domains. In the rst part safety issues are examined on a scenario in which a robot manipulator and a human perform the same task and in the same workspace. During the task execution the human should be able to get into contact with the robot and in this case an estimation algorithm of both interaction forces and contact point is proposed in order to guarantee safety conditions. At the same time, all the unintended contacts have to be avoided, and a suitable post collision strategy has been studied to move away the robot from the collision area or to reduce the impact e orts. However, the second part of the thesis focus on the cooperation between an orthesis and a patient. Indeed, in order to support a rehabilitation process, gait parameters, such as hip and knee angles or the beginning of a gait phase, have been estimated. For this purpose a sensor system, consisting of accelerometers and gyroscopes, and algorithms, developed in order to avoid the error accumulation due to the gyroscopes drift and the vibrations related to the beginning of the stance phase due to the accelerometers, have been proposed.The main goal of the thesis is the development of human-robotic interaction control strategies, which enable close collaboration between human and robot. In this framework we studied two di erent aspects, with applications respectively in industrial and rehabilitation domains. In the rst part safety issues are examined on a scenario in which a robot manipulator and a human perform the same task and in the same workspace. During the task execution the human should be able to get into contact with the robot and in this case an estimation algorithm of both interaction forces and contact point is proposed in order to guarantee safety conditions. At the same time, all the unintended contacts have to be avoided, and a suitable post collision strategy has been studied to move away the robot from the collision area or to reduce the impact e orts. However, the second part of the thesis focus on the cooperation between an orthesis and a patient. Indeed, in order to support a rehabilitation process, gait parameters, such as hip and knee angles or the beginning of a gait phase, have been estimated. For this purpose a sensor system, consisting of accelerometers and gyroscopes, and algorithms, developed in order to avoid the error accumulation due to the gyroscopes drift and the vibrations related to the beginning of the stance phase due to the accelerometers, have been proposed

On Sensorless Collision Detection and Measurement of External Forces in Presence of Modeling Inaccuracies

The field of human-robot interaction has garnered significant interest in the last decade. Every form of human-robot coexistence must guarantee the safety of the user. Safety in human-robot interaction is being vigorously studied, in areas such as collision avoidance, soft actuators, light-weight robots, computer vision techniques, soft tissue modeling, collision detection, etc. Despite the safety provisions, unwanted collisions can occur in case of system faults. In such cases, before post-collision strategies are triggered, it is imperative to effectively detect the collisions. Implementation of tactile sensors, vision systems, sonar and Lidar sensors, etc., allows for detection of collisions. However, due to the cost of such methods, more practical approaches are being investigated. A general goal remains to develop methods for fast detection of external contacts using minimal sensory information. Availability of position data and command torques in manipulators permits development of observer-based techniques to measure external forces/torques. The presence of disturbances and inaccuracies in the model of the robot presents challenges in the efficacy of observers in the context of collision detection. The purpose of this thesis is to develop methods that reduce the effects of modeling inaccuracies in external force/torque estimation and increase the efficacy of collision detection. It is comprised of the following four parts: 1. The KUKA Light-Weight Robot IV+ is commonly employed for research purposes. The regressor matrix, minimal inertial parameters and the friction model of this robot are identified and presented in detail. To develop the model, relative weight analysis is employed for identification. 2. Modeling inaccuracies and robot state approximation errors are considered simultaneously to develop model-based time-varying thresholds for collision detection. A metric is formulated to compare trajectories realizing the same task in terms of their collision detection and external force/torque estimation capabilities. A method for determining optimal trajectories with regards to accurate external force/torque estimation is also developed. 3. The effects of velocity on external force/torque estimation errors are studied with and without the use of joint force/torque sensors. Velocity-based thresholds are developed and implemented to improve collision detection. The results are compared with the collision detection module integrated in the KUKA Light-Weight Robot IV+. 4. An alternative joint-by-joint heuristic method is proposed to identify the effects of modeling inaccuracies on external force/torque estimation. Time-varying collision detection thresholds associated with the heuristic method are developed and compared with constant thresholds. In this work, the KUKA Light-Weight Robot IV+ is used for obtaining the experimental results. This robot is controlled via the Fast Research Interface and Visual C++ 2008. The experimental results confirm the efficacy of the proposed methodologies