Pub Date : 2020-05-01DOI: 10.1109/ICRA40945.2020.9196549
W. Lai, Lin Cao, P. T. Phan, I. Wu, S. Tjin, S. Phee
Accurate motion control of surgical robots is critical for the efficiency and safety of both state-of-the-art teleoperated robotic surgery and the ultimate autonomous robotic surgery. However, fine motion control for a flexible endoscopic surgical robot is highly challenging because of the shape-dependent and speed-dependent motion hysteresis of tendon-sheath mechanisms (TSMs) in the long, tortuous, and dynamically shape-changing robot body. Aiming to achieve precise closed-loop motion control, we propose a small and flexible sensor to directly sense the large and sharp rotations of the articulated joints of a flexible endoscopic surgical robot. The sensor—a Fiber Bragg Grating (FBG) eccentrically embedded in a thin and flexible epoxy substrate—can be significantly bent with a large bending angle range of [-62.9°, 75.5°] and small bending radius of 6.9 mm. Mounted in-between the two pivot-connected links of a joint, the sensor will bend once the joint is actuated, resulting in the wavelength shift of the FBG. In this study, the relationship between the wavelength shift and the rotation angle of the joint was theoretically modeled and then experimentally verified before and after the installation of the sensor in a robotic endoscopic grasper. The sensor, with the calibrated model, can track the rotation of the robotic joint with an RMSE of 3.34°. This small and flexible sensor has good repeatability, high sensitivity (around 147.5 pm/degree), and low hysteresis (7.72%). It is suitable for surgical robots and manipulators whose articulated joints have a large rotation angle and small bending radius.
{"title":"Joint Rotation Angle Sensing of Flexible Endoscopic Surgical Robots","authors":"W. Lai, Lin Cao, P. T. Phan, I. Wu, S. Tjin, S. Phee","doi":"10.1109/ICRA40945.2020.9196549","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9196549","url":null,"abstract":"Accurate motion control of surgical robots is critical for the efficiency and safety of both state-of-the-art teleoperated robotic surgery and the ultimate autonomous robotic surgery. However, fine motion control for a flexible endoscopic surgical robot is highly challenging because of the shape-dependent and speed-dependent motion hysteresis of tendon-sheath mechanisms (TSMs) in the long, tortuous, and dynamically shape-changing robot body. Aiming to achieve precise closed-loop motion control, we propose a small and flexible sensor to directly sense the large and sharp rotations of the articulated joints of a flexible endoscopic surgical robot. The sensor—a Fiber Bragg Grating (FBG) eccentrically embedded in a thin and flexible epoxy substrate—can be significantly bent with a large bending angle range of [-62.9°, 75.5°] and small bending radius of 6.9 mm. Mounted in-between the two pivot-connected links of a joint, the sensor will bend once the joint is actuated, resulting in the wavelength shift of the FBG. In this study, the relationship between the wavelength shift and the rotation angle of the joint was theoretically modeled and then experimentally verified before and after the installation of the sensor in a robotic endoscopic grasper. The sensor, with the calibrated model, can track the rotation of the robotic joint with an RMSE of 3.34°. This small and flexible sensor has good repeatability, high sensitivity (around 147.5 pm/degree), and low hysteresis (7.72%). It is suitable for surgical robots and manipulators whose articulated joints have a large rotation angle and small bending radius.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"60 1","pages":"4789-4795"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90535841","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9197303
V. Osadcuks, Mihails Pudzs, A. Zujevs, A. Pecka, Arturs Ardavs
The Dynamic Visual Sensor is considered to be a next-generation vision sensor. Since event-based vision is in its early stage of development, a small number of datasets has been created during the last decade. Dataset creation is motivated by the need for real data from one or many sensors. Temporal accuracy of data in such datasets is crucially important since the events have high temporal resolution measured in microseconds and, during an algorithm evaluation task, such type of visual data is usually fused with data from other types of sensors. The main aim of our research is to achieve the most accurate possible time synchronization between an event camera, LIDAR, and ambient environment sensors during a session of data acquisition. All the mentioned sensors as well as a stereo and a monocular camera were installed on a mobile robotic platform. In this work, a time synchronization architecture and algorithm are proposed for time synchronization with an implementation example on a PIC32 microcontroller. The overall time synchronization approach is scalable for other sensors where there is a need for accurate time synchronization between many nodes. The evaluation results of the proposed solution are reported and discussed in the paper.
{"title":"Clock-based time sync hronization for an event-based camera dataset acquisition platform *","authors":"V. Osadcuks, Mihails Pudzs, A. Zujevs, A. Pecka, Arturs Ardavs","doi":"10.1109/ICRA40945.2020.9197303","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197303","url":null,"abstract":"The Dynamic Visual Sensor is considered to be a next-generation vision sensor. Since event-based vision is in its early stage of development, a small number of datasets has been created during the last decade. Dataset creation is motivated by the need for real data from one or many sensors. Temporal accuracy of data in such datasets is crucially important since the events have high temporal resolution measured in microseconds and, during an algorithm evaluation task, such type of visual data is usually fused with data from other types of sensors. The main aim of our research is to achieve the most accurate possible time synchronization between an event camera, LIDAR, and ambient environment sensors during a session of data acquisition. All the mentioned sensors as well as a stereo and a monocular camera were installed on a mobile robotic platform. In this work, a time synchronization architecture and algorithm are proposed for time synchronization with an implementation example on a PIC32 microcontroller. The overall time synchronization approach is scalable for other sensors where there is a need for accurate time synchronization between many nodes. The evaluation results of the proposed solution are reported and discussed in the paper.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"27 1","pages":"4695-4701"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78033551","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9197280
Yulin Yang, B. W. Babu, Chuchu Chen, G. Huang, Liu Ren
Batch optimization based inertial measurement unit (IMU) and visual sensor fusion enables high rate localization for many robotic tasks. However, it remains a challenge to ensure that the batch optimization is computationally efficient while being consistent for high rate IMU measurements without marginalization. In this paper, we derive inspiration from maximum likelihood estimation with partial-fixed estimates to provide a unified approach for handing both IMU preintegration and time-offset calibration. We present a modularized analytic combined IMU integrator (ACI2) with elegant derivations for IMU integrations, bias Jabcobians and related covariances. To simplify our derivation, we also prove that the right Jacobians for Hamilton quaterions and SO(3) are equivalent. Finally, we present a time offset calibrator that operates by fixing the linearization point for a given time offset. This reduces re-integration of the IMU measurements and thus improve efficiency. The proposed ACI2 and time-offset calibration is verified by intensive Monte-Carlo simulations generated from real world datasets. A proof-of-concept real world experiment is also conducted to verify the proposed ACI2 estimator.
{"title":"Analytic Combined IMU Integration (ACI2) For Visual Inertial Navigation","authors":"Yulin Yang, B. W. Babu, Chuchu Chen, G. Huang, Liu Ren","doi":"10.1109/ICRA40945.2020.9197280","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197280","url":null,"abstract":"Batch optimization based inertial measurement unit (IMU) and visual sensor fusion enables high rate localization for many robotic tasks. However, it remains a challenge to ensure that the batch optimization is computationally efficient while being consistent for high rate IMU measurements without marginalization. In this paper, we derive inspiration from maximum likelihood estimation with partial-fixed estimates to provide a unified approach for handing both IMU preintegration and time-offset calibration. We present a modularized analytic combined IMU integrator (ACI2) with elegant derivations for IMU integrations, bias Jabcobians and related covariances. To simplify our derivation, we also prove that the right Jacobians for Hamilton quaterions and SO(3) are equivalent. Finally, we present a time offset calibrator that operates by fixing the linearization point for a given time offset. This reduces re-integration of the IMU measurements and thus improve efficiency. The proposed ACI2 and time-offset calibration is verified by intensive Monte-Carlo simulations generated from real world datasets. A proof-of-concept real world experiment is also conducted to verify the proposed ACI2 estimator.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"126 1","pages":"4680-4686"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78093421","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9197442
Noah D. Kohls, Beatriz Dias, Yaw A. Mensah, B. Ruddy, Y. Mazumdar
Soft materials and compliant actuation concepts have generated new design and control approaches in areas from robotics to wearable devices. Despite the potential of soft robotic systems, most designs currently use hard pumps, valves, and electromagnetic actuators. In this work, we take a step towards fully soft robots by developing a new compliant electromagnetic actuator architecture using gallium-indium liquid metal conductors, as well as compliant permanent magnetic and compliant iron composites. Properties of the new materials are first characterized and then co-fabricated to create an exemplary biologically-inspired soft actuator with pulsing or grasping motions, similar to Xenia soft corals. As current is applied to the liquid metal coil, the compliant permanent magnetic tips on passive silicone arms are attracted or repelled. The dynamics of the robotic actuator are characterized using stochastic system identification techniques and then operated at the resonant frequency of 7 Hz to generate high-stroke (>6 mm) motions.
{"title":"Compliant Electromagnetic Actuator Architecture for Soft Robotics","authors":"Noah D. Kohls, Beatriz Dias, Yaw A. Mensah, B. Ruddy, Y. Mazumdar","doi":"10.1109/ICRA40945.2020.9197442","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197442","url":null,"abstract":"Soft materials and compliant actuation concepts have generated new design and control approaches in areas from robotics to wearable devices. Despite the potential of soft robotic systems, most designs currently use hard pumps, valves, and electromagnetic actuators. In this work, we take a step towards fully soft robots by developing a new compliant electromagnetic actuator architecture using gallium-indium liquid metal conductors, as well as compliant permanent magnetic and compliant iron composites. Properties of the new materials are first characterized and then co-fabricated to create an exemplary biologically-inspired soft actuator with pulsing or grasping motions, similar to Xenia soft corals. As current is applied to the liquid metal coil, the compliant permanent magnetic tips on passive silicone arms are attracted or repelled. The dynamics of the robotic actuator are characterized using stochastic system identification techniques and then operated at the resonant frequency of 7 Hz to generate high-stroke (>6 mm) motions.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"21 1","pages":"9042-9049"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78136203","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9196551
Aaron T. Becker, S. Fekete, Li Huang, Phillip Keldenich, Linda Kleist, Dominik Krupke, Christian Rieck, Arne Schmidt
We investigate algorithmic approaches for targeted drug delivery in a complex, maze-like environment, such as a vascular system. The basic scenario is given by a large swarm of micro-scale particles ("agents") and a particular target region ("tumor") within a system of passageways. Agents are too small to contain on-board power or computation and are instead controlled by a global external force that acts uniformly on all particles, such as an applied fluidic flow or electromagnetic field. The challenge is to deliver all agents to the target region with a minimum number of actuation steps. We provide a number of results for this challenge. We show that the underlying problem is NP-hard, which explains why previous work did not provide provably efficient algorithms. We also develop a number of algorithmic approaches that greatly improve the worst-case guarantees for the number of required actuation steps. We evaluate our algorithmic approaches by a number of simulations, both for deterministic algorithms and searches supported by deep learning, which show that the performance is practically promising.
{"title":"Targeted Drug Delivery: Algorithmic Methods for Collecting a Swarm of Particles with Uniform, External Forces","authors":"Aaron T. Becker, S. Fekete, Li Huang, Phillip Keldenich, Linda Kleist, Dominik Krupke, Christian Rieck, Arne Schmidt","doi":"10.1109/ICRA40945.2020.9196551","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9196551","url":null,"abstract":"We investigate algorithmic approaches for targeted drug delivery in a complex, maze-like environment, such as a vascular system. The basic scenario is given by a large swarm of micro-scale particles (\"agents\") and a particular target region (\"tumor\") within a system of passageways. Agents are too small to contain on-board power or computation and are instead controlled by a global external force that acts uniformly on all particles, such as an applied fluidic flow or electromagnetic field. The challenge is to deliver all agents to the target region with a minimum number of actuation steps. We provide a number of results for this challenge. We show that the underlying problem is NP-hard, which explains why previous work did not provide provably efficient algorithms. We also develop a number of algorithmic approaches that greatly improve the worst-case guarantees for the number of required actuation steps. We evaluate our algorithmic approaches by a number of simulations, both for deterministic algorithms and searches supported by deep learning, which show that the performance is practically promising.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"13 1","pages":"2508-2514"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78221472","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9196717
Matthias Pollach, Felix Schiegg, A. Knoll
This work proposes a probabilistic low level automotive sensor fusion approach using LiDAR, RADAR and camera data. The method is stateless and directly operates on associated data from all sensor modalities. Tracking is not used, in order to reduce the object detection latency and create existence hypotheses per frame. The probabilistic fusion uses input from 3D and 2D space. An association method using a combination of overlap and distance metrics, avoiding the need for sensor synchronization is proposed. A Bayesian network executes the sensor fusion. The proposed approach is compared with a state of the art fusion system, which is using multiple sensors of the same modality and relies on tracking for object detection. Evaluation was done using low level sensor data recorded in an urban environment. The test results show that the low level sensor fusion reduces the object detection latency.
{"title":"Low Latency And Low-Level Sensor Fusion For Automotive Use-Cases","authors":"Matthias Pollach, Felix Schiegg, A. Knoll","doi":"10.1109/ICRA40945.2020.9196717","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9196717","url":null,"abstract":"This work proposes a probabilistic low level automotive sensor fusion approach using LiDAR, RADAR and camera data. The method is stateless and directly operates on associated data from all sensor modalities. Tracking is not used, in order to reduce the object detection latency and create existence hypotheses per frame. The probabilistic fusion uses input from 3D and 2D space. An association method using a combination of overlap and distance metrics, avoiding the need for sensor synchronization is proposed. A Bayesian network executes the sensor fusion. The proposed approach is compared with a state of the art fusion system, which is using multiple sensors of the same modality and relies on tracking for object detection. Evaluation was done using low level sensor data recorded in an urban environment. The test results show that the low level sensor fusion reduces the object detection latency.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"74 1","pages":"6780-6786"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75071511","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9197487
Alessia Benevento, María Santos, G. Notarstefano, K. Paynabar, M. Bloch, M. Egerstedt
We present an algorithm for multi-robot coverage of an initially unknown spatial scalar field characterized by a density function, whereby a team of robots simultaneously estimates and optimizes its coverage of the density function over the domain. The proposed algorithm borrows powerful concepts from Bayesian Optimization with Gaussian Processes that, when combined with control laws to achieve centroidal Voronoi tessellation, give rise to an adaptive sequential sampling method to explore and cover the domain. The crux of the approach is to apply a control law using a surrogate function of the true density function, which is then successively refined as robots gather more samples for estimation. The performance of the algorithm is justified theoretically under slightly idealized assumptions, by demonstrating asymptotic no-regret with respect to the coverage obtained with a known density function. The performance is also evaluated in simulation and on the Robotarium with small teams of robots, confirming the good performance suggested by the theoretical analysis.
{"title":"Multi-Robot Coordination for Estimation and Coverage of Unknown Spatial Fields","authors":"Alessia Benevento, María Santos, G. Notarstefano, K. Paynabar, M. Bloch, M. Egerstedt","doi":"10.1109/ICRA40945.2020.9197487","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197487","url":null,"abstract":"We present an algorithm for multi-robot coverage of an initially unknown spatial scalar field characterized by a density function, whereby a team of robots simultaneously estimates and optimizes its coverage of the density function over the domain. The proposed algorithm borrows powerful concepts from Bayesian Optimization with Gaussian Processes that, when combined with control laws to achieve centroidal Voronoi tessellation, give rise to an adaptive sequential sampling method to explore and cover the domain. The crux of the approach is to apply a control law using a surrogate function of the true density function, which is then successively refined as robots gather more samples for estimation. The performance of the algorithm is justified theoretically under slightly idealized assumptions, by demonstrating asymptotic no-regret with respect to the coverage obtained with a known density function. The performance is also evaluated in simulation and on the Robotarium with small teams of robots, confirming the good performance suggested by the theoretical analysis.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"67 1","pages":"7740-7746"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75181460","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9196911
C. McGreavy, Kai Yuan, Daniel F. N. Gordon, Kang Tan, W. Wolfslag, S. Vijayakumar, Zhibin Li
Currently for balance recovery, humans outperform humanoid robots which use hand-designed controllers in terms of the diverse actions. This study aims to close this gap by finding core control principles that are shared across ankle, hip, toe and stepping strategies by formulating experiments to test human balance recoveries and define criteria to quantify the strategy in use. To reveal fundamental principles of balance strategies, our study shows that a minimum jerk controller can accurately replicate comparable human behaviour at the Centre of Mass level. Therefore, we formulate a general Model-Predictive Control (MPC) framework to produce recovery motions in any system, including legged machines, where the framework parameters are tuned for time-optimal performance in robotic systems.
{"title":"Unified Push Recovery Fundamentals: Inspiration from Human Study","authors":"C. McGreavy, Kai Yuan, Daniel F. N. Gordon, Kang Tan, W. Wolfslag, S. Vijayakumar, Zhibin Li","doi":"10.1109/ICRA40945.2020.9196911","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9196911","url":null,"abstract":"Currently for balance recovery, humans outperform humanoid robots which use hand-designed controllers in terms of the diverse actions. This study aims to close this gap by finding core control principles that are shared across ankle, hip, toe and stepping strategies by formulating experiments to test human balance recoveries and define criteria to quantify the strategy in use. To reveal fundamental principles of balance strategies, our study shows that a minimum jerk controller can accurately replicate comparable human behaviour at the Centre of Mass level. Therefore, we formulate a general Model-Predictive Control (MPC) framework to produce recovery motions in any system, including legged machines, where the framework parameters are tuned for time-optimal performance in robotic systems.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"20 1","pages":"10876-10882"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75394924","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9197232
F. M. Ramos, M. Hayashibe
The development of algorithms for motion discrimination in home rehabilitation sessions poses numerous challenges. Recent studies have used the concept of synergies to discriminate a set of movements. However, the discrimination depends on the correlation of the reconstructed movement with the online data, and the training data requires well-defined movements. In this paper, we introduced the concept of a synergy probe, which makes a direct comparison between synergies and online data. The system represents synergies and movements in the same space and monitors their behavior. The results indicated that conventional methods are influenced by the segmentation of training data, and even though the reconstructed movement is similar to the ground-truth, it does not provide sufficient information to evaluate the data in real time. The synergy probes were used to discriminate and evaluate the performance of natural whole-body exercises without segmentation or previous determination of movements. An analysis of the results also demonstrated the possibility to identify the strategies used by the subjects for movement. Such information aids in gaining a better insight and can prove beneficial in home rehabilitation.
{"title":"Simultaneous Online Motion Discrimination and Evaluation of Whole-body Exercise by Synergy Probes for Home Rehabilitation","authors":"F. M. Ramos, M. Hayashibe","doi":"10.1109/ICRA40945.2020.9197232","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197232","url":null,"abstract":"The development of algorithms for motion discrimination in home rehabilitation sessions poses numerous challenges. Recent studies have used the concept of synergies to discriminate a set of movements. However, the discrimination depends on the correlation of the reconstructed movement with the online data, and the training data requires well-defined movements. In this paper, we introduced the concept of a synergy probe, which makes a direct comparison between synergies and online data. The system represents synergies and movements in the same space and monitors their behavior. The results indicated that conventional methods are influenced by the segmentation of training data, and even though the reconstructed movement is similar to the ground-truth, it does not provide sufficient information to evaluate the data in real time. The synergy probes were used to discriminate and evaluate the performance of natural whole-body exercises without segmentation or previous determination of movements. An analysis of the results also demonstrated the possibility to identify the strategies used by the subjects for movement. Such information aids in gaining a better insight and can prove beneficial in home rehabilitation.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"42 1","pages":"10118-10124"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75487217","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 : 2020-05-01DOI: 10.1109/ICRA40945.2020.9197421
Boyao Li, Tao Lu, Jiayi Li, N. Lu, Yinghao Cai, Shuo Wang
Exploration in environments with sparse feed-back remains a challenging research problem in reinforcement learning (RL). When the RL agent explores the environment randomly, it results in low exploration efficiency, especially in robotic manipulation tasks with high dimensional continuous state and action space. In this paper, we propose a novel method, called Augmented Curiosity-Driven Experience Replay (ACDER), which leverages (i) a new goal-oriented curiosity-driven exploration to encourage the agent to pursue novel and task-relevant states more purposefully and (ii) the dynamic initial states selection as an automatic exploratory curriculum to further improve the sample-efficiency. Our approach complements Hindsight Experience Replay (HER) by introducing a new way to pursue valuable states. Experiments conducted on four challenging robotic manipulation tasks with binary rewards, including Reach, Push, Pick&Place and Multi-step Push. The empirical results show that our proposed method significantly outperforms existing methods in the first three basic tasks and also achieves satisfactory performance in multi-step robotic task learning.
{"title":"ACDER: Augmented Curiosity-Driven Experience Replay","authors":"Boyao Li, Tao Lu, Jiayi Li, N. Lu, Yinghao Cai, Shuo Wang","doi":"10.1109/ICRA40945.2020.9197421","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197421","url":null,"abstract":"Exploration in environments with sparse feed-back remains a challenging research problem in reinforcement learning (RL). When the RL agent explores the environment randomly, it results in low exploration efficiency, especially in robotic manipulation tasks with high dimensional continuous state and action space. In this paper, we propose a novel method, called Augmented Curiosity-Driven Experience Replay (ACDER), which leverages (i) a new goal-oriented curiosity-driven exploration to encourage the agent to pursue novel and task-relevant states more purposefully and (ii) the dynamic initial states selection as an automatic exploratory curriculum to further improve the sample-efficiency. Our approach complements Hindsight Experience Replay (HER) by introducing a new way to pursue valuable states. Experiments conducted on four challenging robotic manipulation tasks with binary rewards, including Reach, Push, Pick&Place and Multi-step Push. The empirical results show that our proposed method significantly outperforms existing methods in the first three basic tasks and also achieves satisfactory performance in multi-step robotic task learning.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"15 1","pages":"4218-4224"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77965914","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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