Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8793993
P. Triantafyllou, H. Mnyusiwalla, P. Sotiropoulos, M. Roa, Duncan Russell, G. Deacon
Robotic manipulation is a very active field of research nowadays; however, pick-and-place operations constitute the majority of today’s industrial robotic applications. In order to adopt a robotic solution for an industrial setting, proper evaluation processes should be defined to assess the system’s performance. A number of benchmarks have been proposed in the literature focusing mainly on individual components needed to perform the task, like grasping, perception and motion planning; thus, they do not provide enough information on the performance of the entire robotic system. To address this, we propose a benchmarking framework for a pick-and-place task inspired by a use case for picking fruits and vegetables in an industrial setting. To foster reproducible research and comparison of different robotic systems, the benchmarking framework uses surrogate objects with instructions on how to build them, an easy-to-reproduce environment, and guidelines for object placement. The proposed benchmark is applied to evaluate the performance of two variants of a robotic system with different end-effectors.
{"title":"A Benchmarking Framework for Systematic Evaluation of Robotic Pick-and-Place Systems in an Industrial Grocery Setting","authors":"P. Triantafyllou, H. Mnyusiwalla, P. Sotiropoulos, M. Roa, Duncan Russell, G. Deacon","doi":"10.1109/ICRA.2019.8793993","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793993","url":null,"abstract":"Robotic manipulation is a very active field of research nowadays; however, pick-and-place operations constitute the majority of today’s industrial robotic applications. In order to adopt a robotic solution for an industrial setting, proper evaluation processes should be defined to assess the system’s performance. A number of benchmarks have been proposed in the literature focusing mainly on individual components needed to perform the task, like grasping, perception and motion planning; thus, they do not provide enough information on the performance of the entire robotic system. To address this, we propose a benchmarking framework for a pick-and-place task inspired by a use case for picking fruits and vegetables in an industrial setting. To foster reproducible research and comparison of different robotic systems, the benchmarking framework uses surrogate objects with instructions on how to build them, an easy-to-reproduce environment, and guidelines for object placement. The proposed benchmark is applied to evaluate the performance of two variants of a robotic system with different end-effectors.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"35 1","pages":"6692-6698"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91003724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8793935
Emil Madsen, Oluf Skov Rosenlund, David Brandt, Xuping Zhang
Flexibility commonly exists in the joints of many industrial robots due to the elasticity of the lightweight strain-wave type transmissions being used. This leads to a dynamic time-varying displacement between the position of the drive actuator and that of the driven link. Furthermore, the joint flexibility changes with time due to the material slowly being worn off at the gear meshing. Knowing the stiffness of the robot joints is of great value, e.g. in the design of new model-based feedforward and feedback controllers, and for predictive maintenance in the case of gearing unit failure. In this paper, we address on-line estimation of robot joint stiffness using a recursive least squares strategy based on a parametric model taking into account the elastic torques’ nonlinear dependency on transmission deformation. Robustness is achieved in the presence of measurement noise and in poor excitation conditions. The method can be easily extended to general classes of serial-link multi-degree-of-freedom robots. The estimation technique uses only feedback signals that are readily available on Universal Robots’ e-Series manipulators. Experiments on the new UR5e manipulator demonstrate the effectiveness of the proposed method.
{"title":"Model-Based On-line Estimation of Time-Varying Nonlinear Joint Stiffness on an e-Series Universal Robots Manipulator","authors":"Emil Madsen, Oluf Skov Rosenlund, David Brandt, Xuping Zhang","doi":"10.1109/ICRA.2019.8793935","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793935","url":null,"abstract":"Flexibility commonly exists in the joints of many industrial robots due to the elasticity of the lightweight strain-wave type transmissions being used. This leads to a dynamic time-varying displacement between the position of the drive actuator and that of the driven link. Furthermore, the joint flexibility changes with time due to the material slowly being worn off at the gear meshing. Knowing the stiffness of the robot joints is of great value, e.g. in the design of new model-based feedforward and feedback controllers, and for predictive maintenance in the case of gearing unit failure. In this paper, we address on-line estimation of robot joint stiffness using a recursive least squares strategy based on a parametric model taking into account the elastic torques’ nonlinear dependency on transmission deformation. Robustness is achieved in the presence of measurement noise and in poor excitation conditions. The method can be easily extended to general classes of serial-link multi-degree-of-freedom robots. The estimation technique uses only feedback signals that are readily available on Universal Robots’ e-Series manipulators. Experiments on the new UR5e manipulator demonstrate the effectiveness of the proposed method.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"20 1","pages":"8408-8414"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76974593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8793544
Benjamin A. Richardson, K. J. Kuchenbecker
Humans can form an impression of how a new object feels simply by touching its surfaces with the densely innervated skin of the fingertips. Many haptics researchers have recently been working to endow robots with similar levels of haptic intelligence, but these efforts almost always employ hand-crafted features, which are brittle, and concrete tasks, such as object recognition. We applied unsupervised feature learning methods, specifically K-SVD and Spatio-Temporal Hierarchical Matching Pursuit (ST-HMP), to rich multi-modal haptic data from a diverse dataset. We then tested the learned features on 19 more abstract binary classification tasks that center on haptic adjectives such as smooth and squishy. The learned features proved superior to traditional hand-crafted features by a large margin, almost doubling the average $F_{1}$ score across all adjectives. Additionally, particular exploratory procedures (EPs) and sensor channels were found to support perception of certain haptic adjectives, underlining the need for diverse interactions and multi-modal haptic data.
{"title":"Improving Haptic Adjective Recognition with Unsupervised Feature Learning","authors":"Benjamin A. Richardson, K. J. Kuchenbecker","doi":"10.1109/ICRA.2019.8793544","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793544","url":null,"abstract":"Humans can form an impression of how a new object feels simply by touching its surfaces with the densely innervated skin of the fingertips. Many haptics researchers have recently been working to endow robots with similar levels of haptic intelligence, but these efforts almost always employ hand-crafted features, which are brittle, and concrete tasks, such as object recognition. We applied unsupervised feature learning methods, specifically K-SVD and Spatio-Temporal Hierarchical Matching Pursuit (ST-HMP), to rich multi-modal haptic data from a diverse dataset. We then tested the learned features on 19 more abstract binary classification tasks that center on haptic adjectives such as smooth and squishy. The learned features proved superior to traditional hand-crafted features by a large margin, almost doubling the average $F_{1}$ score across all adjectives. Additionally, particular exploratory procedures (EPs) and sensor channels were found to support perception of certain haptic adjectives, underlining the need for diverse interactions and multi-modal haptic data.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"19 1","pages":"3804-3810"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89502725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8793998
Ela Sachyani Keneth, A. R. Epstein, Michal Soreni Harari, R. S. Pierre, S. Magdassi, S. Bergbreiter
This work demonstrates 3D printed soft actuators with complex shapes and remote actuation using an external magnetic field. Instead of embedding magnetic particles in a polymeric matrix, we fabricated a novel ferrofluid-based actuator, in which the fluid can be moved to different locations in the actuator to affect actuator response. We studied the effect of both the ferrofluid and the 3D printed material on the motion of simple actuators using 3D printed tubes. In addition, we 3D printed more complex actuators mimicking a human hand and a worm to demonstrate more complex motion.
{"title":"3D Printed Ferrofluid Based Soft Actuators","authors":"Ela Sachyani Keneth, A. R. Epstein, Michal Soreni Harari, R. S. Pierre, S. Magdassi, S. Bergbreiter","doi":"10.1109/ICRA.2019.8793998","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793998","url":null,"abstract":"This work demonstrates 3D printed soft actuators with complex shapes and remote actuation using an external magnetic field. Instead of embedding magnetic particles in a polymeric matrix, we fabricated a novel ferrofluid-based actuator, in which the fluid can be moved to different locations in the actuator to affect actuator response. We studied the effect of both the ferrofluid and the 3D printed material on the motion of simple actuators using 3D printed tubes. In addition, we 3D printed more complex actuators mimicking a human hand and a worm to demonstrate more complex motion.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"156 1","pages":"7569-7574"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79877674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8793893
C. Vong, K. Ryan, Hoam Chung
There are many potential applications that require flying robots to navigate through tunnel-like environments, such as inspections of small railway culverts and mineral mappings of mining tunnels. Nevertheless, those environments present many challenges for quadrotors to navigate through. The aerodynamic disturbances created from the fluid interaction between the propellers’ downwash and the surrounding surfaces of the environment, as well as longitudinal wind gusts, add hardship in stabilising the vehicle while the restricted narrow space increases the risk of collision. Furthermore, poor visibility and dust blown by the downwash make vision-based localisation extremely difficult. This paper presents a cross-sectional localisation system using Hough Scan Matching and a simple kinematic Kalman filter. Using the estimated state information, an integral backstepping controller is implemented which enables quadrotors to robustly fly in tunnel-like confined environments. A semi-autonomous system is proposed with self-stabilisation in the vertical and lateral axes while a pilot provides commands in the longitudinal direction. The results of a series of experiments in a simulated tunnel show that the proposed system successfully hovered itself and tracked various trajectories in a cross-sectional area without the aid of any external sensing or computing system.
{"title":"Integral Backstepping Position Control for Quadrotors in Tunnel-Like Confined Environments","authors":"C. Vong, K. Ryan, Hoam Chung","doi":"10.1109/ICRA.2019.8793893","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793893","url":null,"abstract":"There are many potential applications that require flying robots to navigate through tunnel-like environments, such as inspections of small railway culverts and mineral mappings of mining tunnels. Nevertheless, those environments present many challenges for quadrotors to navigate through. The aerodynamic disturbances created from the fluid interaction between the propellers’ downwash and the surrounding surfaces of the environment, as well as longitudinal wind gusts, add hardship in stabilising the vehicle while the restricted narrow space increases the risk of collision. Furthermore, poor visibility and dust blown by the downwash make vision-based localisation extremely difficult. This paper presents a cross-sectional localisation system using Hough Scan Matching and a simple kinematic Kalman filter. Using the estimated state information, an integral backstepping controller is implemented which enables quadrotors to robustly fly in tunnel-like confined environments. A semi-autonomous system is proposed with self-stabilisation in the vertical and lateral axes while a pilot provides commands in the longitudinal direction. The results of a series of experiments in a simulated tunnel show that the proposed system successfully hovered itself and tracked various trajectories in a cross-sectional area without the aid of any external sensing or computing system.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"62 1","pages":"6425-6431"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75144043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8794148
Adam Bignell, Lily Li, R. Vaughan
We propose a novel scheme that jointly addresses the problems of powering and coordinating a population of mini-robots for collective construction. In our setting, a population of simple mobile robots must push blocks into desired polygonal shapes. Each robot performs only simple phototaxis. Coordination is purely open-loop: a global light field guides and powers the robots. We demonstrate this concept in simulation and explore a series of dynamic light field design strategies that robustly result in assembled shapes including nonconvex polygons.
{"title":"Open-Loop Collective Assembly Using a Light Field to Power and Control a Phototaxic Mini-Robot Swarm","authors":"Adam Bignell, Lily Li, R. Vaughan","doi":"10.1109/ICRA.2019.8794148","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794148","url":null,"abstract":"We propose a novel scheme that jointly addresses the problems of powering and coordinating a population of mini-robots for collective construction. In our setting, a population of simple mobile robots must push blocks into desired polygonal shapes. Each robot performs only simple phototaxis. Coordination is purely open-loop: a global light field guides and powers the robots. We demonstrate this concept in simulation and explore a series of dynamic light field design strategies that robustly result in assembled shapes including nonconvex polygons.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"2 1","pages":"5851-5857"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76241209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8794019
M. Watson, D. Gladwin, T. Prescott, Sebastian O. Conran
While much research has been conducted into the generation of smooth trajectories for underactuated unstable aerial vehicles such as quadrotors, less attention has been paid to the application of the same techniques to ground based omnidirectional dynamically balancing robots. These systems have more control authority over their linear accelerations than aerial vehicles, meaning trajectory smoothness is less of a critical design parameter. However, when operating in indoor environments these systems must often adhere to relatively low velocity constraints, resulting in very conservative trajectories when enforced using existing trajectory optimisation methods. This paper makes two contributions; this gap is bridged by the extension of these existing methods to create a fast velocity constrained trajectory planner, with trajectory timing characteristics derived from the optimal minimum-time solution of a simplified acceleration and velocity constrained model. Next, a differentially flat model of an omnidirectional balancing robot utilizing a collinear Mecanum drive is derived, which is used to allow an experimental prototype of this configuration to smoothly follow these velocity constrained trajectories.
{"title":"Velocity Constrained Trajectory Generation for a Collinear Mecanum Wheeled Robot","authors":"M. Watson, D. Gladwin, T. Prescott, Sebastian O. Conran","doi":"10.1109/ICRA.2019.8794019","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794019","url":null,"abstract":"While much research has been conducted into the generation of smooth trajectories for underactuated unstable aerial vehicles such as quadrotors, less attention has been paid to the application of the same techniques to ground based omnidirectional dynamically balancing robots. These systems have more control authority over their linear accelerations than aerial vehicles, meaning trajectory smoothness is less of a critical design parameter. However, when operating in indoor environments these systems must often adhere to relatively low velocity constraints, resulting in very conservative trajectories when enforced using existing trajectory optimisation methods. This paper makes two contributions; this gap is bridged by the extension of these existing methods to create a fast velocity constrained trajectory planner, with trajectory timing characteristics derived from the optimal minimum-time solution of a simplified acceleration and velocity constrained model. Next, a differentially flat model of an omnidirectional balancing robot utilizing a collinear Mecanum drive is derived, which is used to allow an experimental prototype of this configuration to smoothly follow these velocity constrained trajectories.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"42 1","pages":"4444-4450"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75803766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8794407
Kaiyan Yu, Chaoke Guo, J. Yi
A simultaneous robotic footprint and sensor coverage planning scheme is proposed to efficiently detect all the unknown targets with range sensors and cover the targets with the robot’s footprint in a structured environment. The proposed online Sensor-based Complete Coverage (online SCC) planning minimizes the total traveling distance of the robot, guarantees the complete sensor coverage of the whole free space, and achieves near-optimal footprint coverage of all the targets. The planning strategy is applied to a crack-filling robotic prototype to detect and fill all the unknown cracks on ground surfaces. Simulation and experimental results are presented that confirm the efficiency and effectiveness of the proposed online planning algorithm.
{"title":"Complete and Near-Optimal Path Planning for Simultaneous Sensor-Based Inspection and Footprint Coverage in Robotic Crack Filling","authors":"Kaiyan Yu, Chaoke Guo, J. Yi","doi":"10.1109/ICRA.2019.8794407","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794407","url":null,"abstract":"A simultaneous robotic footprint and sensor coverage planning scheme is proposed to efficiently detect all the unknown targets with range sensors and cover the targets with the robot’s footprint in a structured environment. The proposed online Sensor-based Complete Coverage (online SCC) planning minimizes the total traveling distance of the robot, guarantees the complete sensor coverage of the whole free space, and achieves near-optimal footprint coverage of all the targets. The planning strategy is applied to a crack-filling robotic prototype to detect and fill all the unknown cracks on ground surfaces. Simulation and experimental results are presented that confirm the efficiency and effectiveness of the proposed online planning algorithm.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"1 1","pages":"8812-8818"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83761143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8794161
Byeong-uk Lee, Hae-Gon Jeon, Sunghoon Im, I. Kweon
In this paper, we present an end-to-end convolutional neural network (CNN) for depth completion. Our network consists of a geometry network and a context network. The geometry network, a single encoder-decoder network, learns to optimize a multi-task loss to generate an initial propagated depth map and a surface normal. The complementary outputs allow it to correctly propagate initial sparse depth points in slanted surfaces. The context network extracts a local and a global feature of an image to compute a bilateral weight, which enables it to preserve edges and fine details in the depth maps. At the end, a final output is produced by multiplying the initially propagated depth map with the bilateral weight. In order to validate the effectiveness and the robustness of our network, we performed extensive ablation studies and compared the results against state-of-the-art CNN-based depth completions, where we showed promising results on various scenes.
{"title":"Depth Completion with Deep Geometry and Context Guidance","authors":"Byeong-uk Lee, Hae-Gon Jeon, Sunghoon Im, I. Kweon","doi":"10.1109/ICRA.2019.8794161","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794161","url":null,"abstract":"In this paper, we present an end-to-end convolutional neural network (CNN) for depth completion. Our network consists of a geometry network and a context network. The geometry network, a single encoder-decoder network, learns to optimize a multi-task loss to generate an initial propagated depth map and a surface normal. The complementary outputs allow it to correctly propagate initial sparse depth points in slanted surfaces. The context network extracts a local and a global feature of an image to compute a bilateral weight, which enables it to preserve edges and fine details in the depth maps. At the end, a final output is produced by multiplying the initially propagated depth map with the bilateral weight. In order to validate the effectiveness and the robustness of our network, we performed extensive ablation studies and compared the results against state-of-the-art CNN-based depth completions, where we showed promising results on various scenes.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"8 1","pages":"3281-3287"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80419842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8794288
Dominik Riedelbauch, D. Henrich
We propose a highly flexible approach to human-robot cooperation, where a robot dynamically selects operations contributing to a shared goal from a given task model. Therefore, knowledge on the task progress is extracted from a world model constructed from eye-in-hand camera images. Data generated from such partial workspace observations is not reliable over time, as humans may interact with resources. We therefore use a human-aware world model maintaining a measure for trust in stored objects regarding recent human presence and previous task progress. Our contribution is an action selection algorithm that uses this trust measure to interleave task operations with active vision to refresh the world model. Large-scale experiments cover various sorts of human participation in different benchmark tasks through simulation of simplified, partially randomized human models. Results illuminate system behaviour and performance for different parametrizations of our human-robot teaming framework.
{"title":"Exploiting a Human-Aware World Model for Dynamic Task Allocation in Flexible Human-Robot Teams","authors":"Dominik Riedelbauch, D. Henrich","doi":"10.1109/ICRA.2019.8794288","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794288","url":null,"abstract":"We propose a highly flexible approach to human-robot cooperation, where a robot dynamically selects operations contributing to a shared goal from a given task model. Therefore, knowledge on the task progress is extracted from a world model constructed from eye-in-hand camera images. Data generated from such partial workspace observations is not reliable over time, as humans may interact with resources. We therefore use a human-aware world model maintaining a measure for trust in stored objects regarding recent human presence and previous task progress. Our contribution is an action selection algorithm that uses this trust measure to interleave task operations with active vision to refresh the world model. Large-scale experiments cover various sorts of human participation in different benchmark tasks through simulation of simplified, partially randomized human models. Results illuminate system behaviour and performance for different parametrizations of our human-robot teaming framework.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"165 1","pages":"6511-6517"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72784758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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