A Sliding Mode Control Architecture for Human-Manipulator Cooperative Surface Treatment Tasks

© 2018 IEEE. This paper presents a control architecture readily suitable for surface treatment tasks such as polishing, grinding, finishing or deburring as carried out by a human operator, with the added benefit of accuracy, recurrence and physical strength as administered by a robotic manipulator partner. The shared strategy effectively couples the human operator propioceptive abilities and fine skills through his interactions with the autonomous physical agent. The novel proposed control scheme is based on task prioritization and a non-conventional sliding mode control, which is considered to benefit from its inherent robustness and low computational cost. The system relies on two force sensors, one located between the last link of the robot and the surface treatment tool, and the other located in some place of the robot end-effector: the former is used to suitably accomplish the conditioning task, while the latter is used by the operator to manually guide the robotic tool. When the operator chooses to cease guiding the tool, the robot motion safely switches back to an automatic reference tracking. The paper presents the theories for the novel collaborative controller, whilst its effectiveness for robotic surface treatment is substantiated by experimental results using a redundant 7R manipulator and a mock-up conditioning tool

Human-robot cooperation for robust surface treatment using non-conventional sliding mode control

[EN] This work presents a human-robot closely collaborative solution to cooperatively perform surface treatment tasks such as polishing, grinding, deburring, etc. The method considers two force sensors attached to the manipulator end-effector and tool: one sensor is used to properly accomplish the surface treatment task, while the second one is used by the operator to guide the robot tool. The proposed scheme is based on task priority and adaptive non-conventional sliding mode control. The applicability of the proposed approach is substantiated by experimental results using a redundant 7R manipulator: the Sawyer cobot.This work was supported in part by the Spanish Government under the project DPI2017-87656-C2-1-R and the Generalitat Valenciana under Grants VALi + d APOSTD/2016/044 and APOSTD/2017/055.Solanes Galbis, JE.; Gracia Calandin, LI.; Muñoz-Benavent, P.; Valls Miro, J.; Girbés, V.; Tornero Montserrat, J. (2018). Human-robot cooperation for robust surface treatment using non-conventional sliding mode control. ISA Transactions. 80(1):528-541. https://doi.org/10.1016/j.isatra.2018.05.013S52854180

Human-robot cooperation for robust surface treatment using non-conventional sliding mode control

© 2018 ISA This work presents a human-robot closely collaborative solution to cooperatively perform surface treatment tasks such as polishing, grinding, deburring, etc. The method considers two force sensors attached to the manipulator end-effector and tool: one sensor is used to properly accomplish the surface treatment task, while the second one is used by the operator to guide the robot tool. The proposed scheme is based on task priority and adaptive non-conventional sliding mode control. The applicability of the proposed approach is substantiated by experimental results using a redundant 7R manipulator: the Sawyer cobot

Review of Intelligent Control Systems with Robotics

Interactive between human and robot assumes a significant job in improving the productivity of the instrument in mechanical technology. Numerous intricate undertakings are cultivated continuously via self-sufficient versatile robots. Current automated control frameworks have upset the creation business, making them very adaptable and simple to utilize. This paper examines current and up and coming sorts of control frameworks and their execution in mechanical technology, and the job of AI in apply autonomy. It additionally expects to reveal insight into the different issues around the control frameworks and the various approaches to fix them. It additionally proposes the basics of apply autonomy control frameworks and various kinds of mechanical technology control frameworks. Each kind of control framework has its upsides and downsides which are talked about in this paper. Another kind of robot control framework that upgrades and difficulties the pursuit stage is man-made brainpower. A portion of the speculations utilized in man-made reasoning, for example, Artificial Intelligence (AI) such as fuzzy logic, neural network and genetic algorithm, are itemized in this paper. At long last, a portion of the joint efforts between mechanical autonomy, people, and innovation were referenced. Human coordinated effort, for example, Kinect signal acknowledgment utilized in games and versatile upper-arm-based robots utilized in the clinical field for individuals with inabilities. Later on, it is normal that the significance of different sensors will build, accordingly expanding the knowledge and activity of the robot in a modern domai

An Adaptive Tool-Based Telerobot Control System

Modern telerobotics concepts seek to improve the work efficiency and quality of remote operations. The unstructured nature of typical remote operational environments makes autonomous operation of telerobotic systems difficult to achieve. Thus, human operators must always remain in the control loop for safety reasons. Remote operations involve tooling interactions with task environment. These interactions can be strong enough to promote unstable operation sometimes leading to system failures. Interestingly, manipulator/tooling dynamic interactions have not been studied in detail. This dissertation introduces a human-machine cooperative telerobotic (HMCTR) system architecture that has the ability to incorporate tooling interaction control and other computer assistance functions into the overall control system. A universal tooling interaction force prediction model has been created and implemented using grey system theory. Finally, a grey prediction force/position parallel fuzzy controller has been developed that compensates for the tooling interaction forces. Detailed experiments using a full-scale telerobotics testbed indicate: (i) the feasibility of the developed methodologies, and (ii) dramatic improvements in the stability of manipulator – based on band saw cutting operations. These results are foundational toward the further enhancement and development of telerobot

Performance of modified jatropha oil in combination with hexagonal boron nitride particles as a bio-based lubricant for green machining

This study evaluates the machining performance of newly developed modified jatropha oils (MJO1, MJO3 and MJO5), both with and without hexagonal boron nitride (hBN) particles (ranging between 0.05 and 0.5 wt%) during turning of AISI 1045 using minimum quantity lubrication (MQL). The experimental results indicated that, viscosity improved with the increase in MJOs molar ratio and hBN concentration. Excellent tribological behaviours is found to correlated with a better machining performance were achieved by MJO5a with 0.05 wt%. The MJO5a sample showed the lowest values of cutting force, cutting temperature and surface roughness, with a prolonged tool life and less tool wear, qualifying itself to be a potential alternative to the synthetic ester, with regard to the environmental concern

Human-robot interaction using a behavioural control strategy

PhD ThesisA topical and important aspect of robotics research is in the area of human-robot interaction (HRI), which addresses the issue of cooperation between a human and a robot to allow tasks to be shared in a safe and reliable manner. This thesis focuses on the design and development of an appropriate set of behaviour strategies for human-robot interactive control by first understanding how an equivalent human-human interaction (HHI) can be used to establish a framework for a robotic behaviour-based approach. To achieve the above goal, two preliminary HHI experimental investigations were initiated in this study. The first of which was designed to evaluate the human dynamic response using a one degree-of-freedom (DOF) HHI rectilinear test where the handler passes a compliant object to the receiver along a constrained horizontal path. The human dynamic response while executing the HHI rectilinear task has been investigated using a Box-Behnken design of experiments [Box and Hunter, 1957] and was based on the McRuer crossover model [McRuer et al. 1995]. To mimic a real-world human-human object handover task where the handler is able to pass an object to the receiver in a 3D workspace, a second more substantive one DOF HHI baton handover task has been developed. The HHI object handover tests were designed to understand the dynamic behavioural characteristics of the human participants, in which the handler was required to dexterously pass an object to the receiver in a timely and natural manner. The profiles of interactive forces between the handler and receiver were measured as a function of time, and how they are modulated whilst performing the tasks, was evaluated. Three key parameters were used to identify the physical characteristics of the human participants, including: peak interactive force (fmax), transfer time (Ttrf), and work done (W). These variables were subsequently used to design and develop an appropriate set of force and velocity control strategies for a six DOF Stäubli robot manipulator arm (TX60) working in a human-robot interactive environment. The optimal design of the software and hardware controller implementation for the robot system has been successfully established in keeping with a behaviour-based approach. External force control based on proportional plus integral (PI) and fuzzy logic control (FLC) algorithms were adopted to control the robot end effector velocity and interactive force in real-time. ii The results of interactive experiments with human-to-robot and robot-to-human handover tasks allowed a comparison of the PI and FLC control strategies. It can be concluded that the quantitative measurement of the performance of robot velocity and force control can be considered acceptable for human-robot interaction. These can provide effective performance during the robot-human object handover tasks, where the robot was able to successfully pass the object from/to the human in a safe, reliable and timely manner. However, after careful analysis with regard to human-robot handover test results, the FLC scheme was shown to be superior to PI control by actively compensating for the dynamics in the non-linear system and demonstrated better overall performance and stability. The FLC also shows superior performance in terms of improved sensitivity to small error changes compared to PI control, which is an advantage in establishing effective robot force control. The results of survey responses from the participants were in agreement with the parallel test outcomes, demonstrating significant satisfaction with the overall performance of the human-robot interactive system, as measured by an average rating of 4.06 on a five point scale. In brief, this research has contributed the foundations for long-term research, particularly in the development of an interactive real-time robot-force control system, which enables the robot manipulator arm to cooperate with a human to facilitate the dextrous transfer of objects in a safe and speedy manner.Thai government and Prince of Songkla University (PSU