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Robots are typically classified based on specific morphological features, like their kinematic structure. However, a complex interplay between morphology and intelligence shapes how well a robot performs processes. Just as delicate surgical procedures demand high dexterity and tactile precision, manual warehouse or construction work requires strength and endurance. These process requirements necessitate robot systems that provide a level of performance fitting the process. In this work, we… Mehr anzeigen

Robots are typically classified based on specific morphological features, like their kinematic structure. However, a complex interplay between morphology and intelligence shapes how well a robot performs processes. Just as delicate surgical procedures demand high dexterity and tactile precision, manual warehouse or construction work requires strength and endurance. These process requirements necessitate robot systems that provide a level of performance fitting the process. In this work, we introduce the tree of robots as a taxonomy to bridge the gap between morphological classification and process-based performance. It classifies robots based on their fitness to perform, for example, physical interaction processes. Using 11 industrial manipulators, we constructed the first part of the tree of robots based on a carefully deduced set of metrics reflecting fundamental robot capabilities for various industrial physical interaction processes. Through significance analysis, we identified substantial differences between the systems, grouping them via an expectation-maximization algorithm to create a fitness-based robot classification that is open for contributions and accessible. Weniger anzeigen

This paper presents a teleoperation framework designed for online learning and adaptation of tactile skills, which provides an intuitive interface without the need for physical access to an execution robot. The proposed tele-teaching approach utilizes periodical Dynamical Movement Primitives (DMP) and Recursive Least Square (RLS) to generate tactile skills. An autonomy allocation strategy, guided by learning confidence and operator intention, ensures a smooth transition from human demonstration… Mehr anzeigen

This paper presents a teleoperation framework designed for online learning and adaptation of tactile skills, which provides an intuitive interface without the need for physical access to an execution robot. The proposed tele-teaching approach utilizes periodical Dynamical Movement Primitives (DMP) and Recursive Least Square (RLS) to generate tactile skills. An autonomy allocation strategy, guided by learning confidence and operator intention, ensures a smooth transition from human demonstration to autonomous robot operation. Our experimental results with two 7 Degree of Freedom (DoF) Franka Panda robots demonstrate that the tele-teaching framework facilitates online motion and force learning and adaptation within a few iterations. Weniger anzeigen

Mobile manipulators (MM) have proven valuable in assisting humans in industrial settings. However, their strict separation from humans in controlled environments limits their effectiveness. Efforts have been made to bridge this gap for physical human-robot interaction (pHRI), leading to the development of collaborative mobile manipulators (CMM). Nonetheless, unpredictable environments continue to present challenges. This paper introduces an innovative suspension design for mobile bases (MBs) to… Mehr anzeigen

Mobile manipulators (MM) have proven valuable in assisting humans in industrial settings. However, their strict separation from humans in controlled environments limits their effectiveness. Efforts have been made to bridge this gap for physical human-robot interaction (pHRI), leading to the development of collaborative mobile manipulators (CMM). Nonetheless, unpredictable environments continue to present challenges. This paper introduces an innovative suspension design for mobile bases (MBs) to enhance the safety and autonomy of CMMs. We propose an electromechanical approach leveraging variable stiffness and combining passive springs with adaptive transmission mechanisms. Through simulation, physical prototype development, and experimental validation, we demonstrate the effectiveness of our approach in stabilizing the MB against external disturbances. Our findings provide valuable insights for the development of CMMs in dynamic environments. Weniger anzeigen

Despite recent advancements in torque-controlled tactile robots, integrating them into manufacturing settings remains challenging, particularly in complex environments. Simplifying robotic skill programming for non-experts is crucial for increasing robot deployment in manufacturing. This work proposes an innovative approach, Vision-Augmented Unified Force-Impedance Control (VA-UFIC), aimed at intuitive visuo-tactile exploration of unknown 3D curvatures. VA-UFIC stands out by seamlessly… Mehr anzeigen

Despite recent advancements in torque-controlled tactile robots, integrating them into manufacturing settings remains challenging, particularly in complex environments. Simplifying robotic skill programming for non-experts is crucial for increasing robot deployment in manufacturing. This work proposes an innovative approach, Vision-Augmented Unified Force-Impedance Control (VA-UFIC), aimed at intuitive visuo-tactile exploration of unknown 3D curvatures. VA-UFIC stands out by seamlessly integrating vision and tactile data, enabling the exploration of diverse contact shapes in three dimensions, including point contacts, flat contacts with concave and convex curvatures, and scenarios involving contact loss. A pivotal component of our method is a robust online contact alignment monitoring system that considers tactile error, local surface curvature, and orientation, facilitating adaptive adjustments of robot stiffness and force regulation during exploration. We introduce virtual energy tanks within the control framework to ensure safety and stability, effectively addressing inherent safety concerns in visuo-tactile exploration. Evaluation using a Franka Emika research robot demonstrates the efficacy of VA-UFIC in exploring unknown 3D curvatures while adhering to arbitrarily defined force-motion policies. By seamlessly integrating vision and tactile sensing, VA-UFIC offers a promising avenue for intuitive exploration of complex environments, with potential applications spanning manufacturing, inspection, and beyond. Weniger anzeigen

Flexible manufacturing lines are required to meet the demand for customized and small batch-size products. Even though state-of-the-art tactile robots may provide the versatility for increased adaptability and flexibility, their potential is yet to be fully exploited. To support robotics deployment in manufacturing, we propose a task-based tactile robot programming paradigm that uses an object-centric tactile skill definition that directly links identified object constraints of the task to the… Mehr anzeigen

Flexible manufacturing lines are required to meet the demand for customized and small batch-size products. Even though state-of-the-art tactile robots may provide the versatility for increased adaptability and flexibility, their potential is yet to be fully exploited. To support robotics deployment in manufacturing, we propose a task-based tactile robot programming paradigm that uses an object-centric tactile skill definition that directly links identified object constraints of the task to the definition of constraint-based unified force-impedance control. In this study, we first explain the basic concept of abstracting the task constraints experienced by the object and transferring them to the robot's operational space frame. Second, using the object-centric tactile skill definition, we synthesize unified force-impedance control and formalized holonomic constraints to enable flexible task execution. Later, we propose the quantified analysis metrics for the process by analyzing them as a typical example of flexible manipulation disassembly skills, e.g., levering and unscrew-driving regarding their object requirements. Supported by realistic experimental evaluation using a Franka Emika robot, our tactile robot programming approach for the direct translation between task-level constraints and robot control parameter design is shown to be a viable solution for increased robotic deployment in flexible manufacturing lines. Weniger anzeigen

Different robotic manipulation tasks require different execution and planning strategies. Nevertheless, the versatility of tasks in assembly and disassembly demands flexible control strategies. Fundamental to achieving such adaptive control methods is understanding and generalizing the interactions between tools, the manipulated object, and the environment required to perform a manipulation. This paper addresses the problem of generating adaptive manipulation by introducing the force-velocity… Mehr anzeigen

Different robotic manipulation tasks require different execution and planning strategies. Nevertheless, the versatility of tasks in assembly and disassembly demands flexible control strategies. Fundamental to achieving such adaptive control methods is understanding and generalizing the interactions between tools, the manipulated object, and the environment required to perform a manipulation. This paper addresses the problem of generating adaptive manipulation by introducing the force-velocity task phase plot that represents the inherent nature of tactile manipulation skills. This representation enables us to identify the primary phases of the interaction in the force-velocity domain. Using unified force-impedance control, we establish a tactile manipulation strategy to robustly conduct versatile manipulation tasks even in case of disturbances or imprecise task information. The proposed control scheme features a dynamic process for impedance shaping based on the external force applied to the robot and the skill motion error for collision response, as well as a force-shaping function that enables both a smooth transition from free motion to contact and force regulation. We implement and compare the control strategy to previously proposed strategies using peg-in-hole reference experiments that include force disturbance and positioning inaccuracies and show the respective task phase plots. As a result, we observe high controller robustness and conclude that using the task phase plot as the inherent representation of tactile manipulation via unified force-impedance control enables successful adaptive controller design and creates a quantifiable basis for robotic skill solution comparison. Weniger anzeigen

Tactile robots can perform complex interaction skills, e.g., polishing. Such robots should therefore be designed to be adaptive to environmental uncertainties such as changing geometry and contact-loss. To address this, we propose a tactile exploration technique to observe the local curvatures of the physical constraints such as corners, edges, etc. for updating predefined tactile skill policies accordingly. First, we develop a unified force-impedance control approach in which the force… Mehr anzeigen

Tactile robots can perform complex interaction skills, e.g., polishing. Such robots should therefore be designed to be adaptive to environmental uncertainties such as changing geometry and contact-loss. To address this, we propose a tactile exploration technique to observe the local curvatures of the physical constraints such as corners, edges, etc. for updating predefined tactile skill policies accordingly. First, we develop a unified force-impedance control approach in which the force controller significantly improves the geometry following performance due to the ensured contact. Second, we use the proposed controller to autonomously investigate the unknown environment via the local curvature observer, designed to be a dynamic process. Finally, the exploration performance of the proposed controller is demonstrated by using a polishing skill on an unknown 3D surface, where the robot is observed to autonomously investigate the unknown surface from top to bottom along the edges and corners. Weniger anzeigen

Improving robot systems via newly-developed sensing devices, control algorithms, or state estimators in order to obtain safe and efficient human-robot interaction as well as tactile manipulation skills requires standardized performance measurement protocols for objective comparison. Common protocols to evaluate robot motion performance are currently defined in EN ISO 9283:1998. For tactile and safety performance, however, no common metrics were agreed on nor standardized yet. In this paper, we… Mehr anzeigen

Improving robot systems via newly-developed sensing devices, control algorithms, or state estimators in order to obtain safe and efficient human-robot interaction as well as tactile manipulation skills requires standardized performance measurement protocols for objective comparison. Common protocols to evaluate robot motion performance are currently defined in EN ISO 9283:1998. For tactile and safety performance, however, no common metrics were agreed on nor standardized yet. In this paper, we propose a set of quantifiable performance criteria for robot performance analysis, objectifying robot force sensing, force control, and collision detection/reaction performance. We introduce the corresponding measurement setups and protocols, demonstrate and experimentally validate each with a Universal Robot UR10e and UR5e as well as a Franka Emika Panda robot arm.
The proposed performance criteria, metrics, and experimental setups constitute the basis of a fully tactile performance and safety benchmarking framework that allows to objectively evaluate tactile robot performance via reproducible reference tests. Weniger anzeigen

The daily use of advanced wearable robotic devices for the assistance of people with locomotor disabilities is still facing clear limitations in usability and acceptance (e.g. cost, complexity, and inability to maintain balance). In most devices, the correct selection and initiation of pre-defined functions and activities (e.g. walking and stair ascent-descent) rely on the user's input and constant interpretation of the environment, which results in a substantial cognitive workload. In this… Mehr anzeigen

The daily use of advanced wearable robotic devices for the assistance of people with locomotor disabilities is still facing clear limitations in usability and acceptance (e.g. cost, complexity, and inability to maintain balance). In most devices, the correct selection and initiation of pre-defined functions and activities (e.g. walking and stair ascent-descent) rely on the user's input and constant interpretation of the environment, which results in a substantial cognitive workload. In this study, a novel environment recognition and parameterization system that uses depth camera images is proposed as a potential assistant in the control of powered lower-limb exoskeletons. The feasibility of an online shared-control approach between the user and the system was assessed in two specific use-cases of lower-limb exoskeletons: Mode selection assistance and dynamic step adaptation. In a sequence of realistic daily life tasks, the assistance provided by the proposed system achieved an error below 10% with a loop frequency up to 400 Hz in terms of parameterizing the environment, and reduced the mean overall workload, measured with the Raw Task Load Index, by 19% in a group of seven neurologically intact subjects. In conclusion, an assistive environment recognition and parameterization system shows potential to reduce the cognitive workload on the user, and thereby positively influence device usability. Weniger anzeigen

Tactile robots shall be deployed for dynamic task execution in production lines with small batch sizes. Therefore, these robots should have the ability to respond to changing conditions and be easy to (re-)program. Operating under uncertain environments requires unifying subsystems such as robot motion and force policy into one framework, referred to as tactile skills. In this paper, we propose the enhancement of these skills for passivity-based skill motion learning in stiffness-adaptive… Mehr anzeigen

Tactile robots shall be deployed for dynamic task execution in production lines with small batch sizes. Therefore, these robots should have the ability to respond to changing conditions and be easy to (re-)program. Operating under uncertain environments requires unifying subsystems such as robot motion and force policy into one framework, referred to as tactile skills. In this paper, we propose the enhancement of these skills for passivity-based skill motion learning in stiffness-adaptive unified force-impedance control. To achieve the increased level of adaptability, we represent all tactile skills by three basic primitives: contact initiation, manipulation, and contact termination. To ensure passivity and stability, we develop an energy-based approach for unified force-impedance control that allows humans to teach the robot motion through physical interaction during the execution of a tactile task. We incorporate our proposed framework into a tactile robot to experimentally validate the motion adaptation by interaction performance and stability of the control. While the polishing task is presented as our use case through the paper, the experiments can also be carried out with various tactile skills. Finally, the results show the novel controller's stability and passivity to contact-loss and stiffness adaptation, leading to successful programming by interaction. Weniger anzeigen