Pub Date : 2019-05-20DOI: 10.1109/ICRA.2019.8794388
S. S. Groothuis, S. Stramigioli
Passivity is a necessary condition for a system’s stability, meaning that an energy generating system may readily become unstable. Energy-aware actuation can enforce passivity by monitoring the amount of energy that is exchanged with a system, while using an allocated energy budget to execute a task. Careful communication of the energy budgets is important to prevent accidental generation of energy. Therefore, this paper proposes an energy transaction protocol to communicate energy budgets in a distributed robotic system to guarantee that passivity is kept. Simulations are performed with a model of the protocol that is applied to a simulated unreliable communication channel. It is verified that the proposed protocol keeps passivity in the system, while a naive communication strategy either violates passivity or is unnecessarily dissipative.
{"title":"Energy Budget Transaction Protocol for Distributed Robotic Systems","authors":"S. S. Groothuis, S. Stramigioli","doi":"10.1109/ICRA.2019.8794388","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794388","url":null,"abstract":"Passivity is a necessary condition for a system’s stability, meaning that an energy generating system may readily become unstable. Energy-aware actuation can enforce passivity by monitoring the amount of energy that is exchanged with a system, while using an allocated energy budget to execute a task. Careful communication of the energy budgets is important to prevent accidental generation of energy. Therefore, this paper proposes an energy transaction protocol to communicate energy budgets in a distributed robotic system to guarantee that passivity is kept. Simulations are performed with a model of the protocol that is applied to a simulated unreliable communication channel. It is verified that the proposed protocol keeps passivity in the system, while a naive communication strategy either violates passivity or is unnecessarily dissipative.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"116 1","pages":"1563-1568"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86799951","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.2019.8793688
Yifeng Zhu, Devin Schwab, M. Veloso
Achieving effective task performance on real mobile robots is a great challenge when hand-coding algorithms, both due to the amount of effort involved and manually tuned parameters required for each skill. Learning algorithms instead have the potential to lighten up this challenge by using one single set of training parameters for learning different skills, but the question of the feasibility of such learning in real robots remains a research pursuit. We focus on a kind of mobile robot system - the robot soccer “small-size” domain, in which tactical and high-level team strategies build upon individual robot ball-based skills. In this paper, we present our work using a Deep Reinforcement Learning algorithm to learn three real robot primitive skills in continuous action space: go-to-ball, turn-and-shoot and shoot-goalie, for which there is a clear success metric to reach a destination or score a goal. We introduce the state and action representation, as well as the reward and network architecture. We describe our training and testing using a simulator of high physical and hardware fidelity. Then we test the policies trained from simulation on real robots. Our results show that the learned skills achieve an overall better success rate at the expense of taking 0.29 seconds slower on average for all three skills. In the end, we show that our policies trained in simulation have good performance on real robots by directly transferring the policy.
{"title":"Learning Primitive Skills for Mobile Robots","authors":"Yifeng Zhu, Devin Schwab, M. Veloso","doi":"10.1109/ICRA.2019.8793688","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793688","url":null,"abstract":"Achieving effective task performance on real mobile robots is a great challenge when hand-coding algorithms, both due to the amount of effort involved and manually tuned parameters required for each skill. Learning algorithms instead have the potential to lighten up this challenge by using one single set of training parameters for learning different skills, but the question of the feasibility of such learning in real robots remains a research pursuit. We focus on a kind of mobile robot system - the robot soccer “small-size” domain, in which tactical and high-level team strategies build upon individual robot ball-based skills. In this paper, we present our work using a Deep Reinforcement Learning algorithm to learn three real robot primitive skills in continuous action space: go-to-ball, turn-and-shoot and shoot-goalie, for which there is a clear success metric to reach a destination or score a goal. We introduce the state and action representation, as well as the reward and network architecture. We describe our training and testing using a simulator of high physical and hardware fidelity. Then we test the policies trained from simulation on real robots. Our results show that the learned skills achieve an overall better success rate at the expense of taking 0.29 seconds slower on average for all three skills. In the end, we show that our policies trained in simulation have good performance on real robots by directly transferring the policy.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"38 1","pages":"7597-7603"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90262304","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.2019.8794103
Nicholas Fung, J. Rogers, Carlos Nieto, H. Christensen, S. Kemna, G. Sukhatme
As robotic platforms have become more capable and autonomous, they have increasingly been utilized in time sensitive applications such as search and rescue. To that end, we have developed a system for teams of robots to efficiently explore an environment while taking sensor measurements. The system utilizes an information seeking algorithm that generates high priority points of interest based on the highest expected information gained per distance travelled. In order to coordinate multiple robots, the system partitions the area into different regions according to the effort needed to explore each region. Robots are assigned different regions to measure in order to minimize repetition of work and reduce interference between each robot.We present an information rate adaptive sampling approach for tasking robots within an environment to gather sensor measurements. We evaluated our approach within a simulation environment with one to four robots. Multiple robots are coordinated through our region segmentation approach. The data shows efficiency gains through the use of adaptive information gain rate tasking above a naïve closest point approach. We also see positive results from using the region segmentation technique. We further the experimentation by testing the algorithm on real world robots and verify the results in real world experimentation.
{"title":"Coordinating multi-robot systems through environment partitioning for adaptive informative sampling","authors":"Nicholas Fung, J. Rogers, Carlos Nieto, H. Christensen, S. Kemna, G. Sukhatme","doi":"10.1109/ICRA.2019.8794103","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794103","url":null,"abstract":"As robotic platforms have become more capable and autonomous, they have increasingly been utilized in time sensitive applications such as search and rescue. To that end, we have developed a system for teams of robots to efficiently explore an environment while taking sensor measurements. The system utilizes an information seeking algorithm that generates high priority points of interest based on the highest expected information gained per distance travelled. In order to coordinate multiple robots, the system partitions the area into different regions according to the effort needed to explore each region. Robots are assigned different regions to measure in order to minimize repetition of work and reduce interference between each robot.We present an information rate adaptive sampling approach for tasking robots within an environment to gather sensor measurements. We evaluated our approach within a simulation environment with one to four robots. Multiple robots are coordinated through our region segmentation approach. The data shows efficiency gains through the use of adaptive information gain rate tasking above a naïve closest point approach. We also see positive results from using the region segmentation technique. We further the experimentation by testing the algorithm on real world robots and verify the results in real world experimentation.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"2 1","pages":"3231-3237"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86371086","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.2019.8794243
L. Dressel, Mykel J. Kochenderfer
Unauthorized drone flights near aircraft, airports, and emergency operations compromise the safety of passengers and bystanders. A detection system that can quickly find and track drones could help mitigate the risk of unauthorized drone flights. In this work, we show how a consumer drone outfitted with antennas and commodity radios can autonomously localize another drone by its telemetry radio emissions. We show how a non-myopic planner improves tracking performance over traditionally used greedy, one-step planners. Improved tracking is validated with simulations and the system is demonstrated with real drones in flight tests.
{"title":"Hunting Drones with Other Drones: Tracking a Moving Radio Target","authors":"L. Dressel, Mykel J. Kochenderfer","doi":"10.1109/ICRA.2019.8794243","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794243","url":null,"abstract":"Unauthorized drone flights near aircraft, airports, and emergency operations compromise the safety of passengers and bystanders. A detection system that can quickly find and track drones could help mitigate the risk of unauthorized drone flights. In this work, we show how a consumer drone outfitted with antennas and commodity radios can autonomously localize another drone by its telemetry radio emissions. We show how a non-myopic planner improves tracking performance over traditionally used greedy, one-step planners. Improved tracking is validated with simulations and the system is demonstrated with real drones in flight tests.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"138 1","pages":"1905-1912"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85421571","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.2019.8793632
Yongbo Chen, Shoudong Huang, R. Fitch, Liang Zhao, Huan Yu, Di Yang
In this paper, we present an on-line active pose-graph simultaneous localization and mapping (SLAM) frame-work for robots in three-dimensional (3D) environments using graph topology and sub-maps. This framework aims to find the best trajectory for loop-closure by re-visiting old poses based on the T-optimality and D-optimality metrics of the Fisher information matrix (FIM) in pose-graph SLAM. In order to reduce computational complexity, graph topologies are introduced, including weighted node degree (T-optimality metric) and weighted tree-connectivity (D-optimality metric), to choose a candidate trajectory and several key poses. With the help of the key poses, a sampling-based path planning method and a continuous-time trajectory optimization method are combined hierarchically and applied in the whole framework. So as to further improve the real-time capability of the method, the sub-map joining method is used in the estimation and planning process for large-scale active SLAM problems. In simulations and experiments, we validate our approach by comparing against existing methods, and we demonstrate the on-line planning part using a quad-rotor unmanned aerial vehicle (UAV).
{"title":"On-line 3D active pose-graph SLAM based on key poses using graph topology and sub-maps","authors":"Yongbo Chen, Shoudong Huang, R. Fitch, Liang Zhao, Huan Yu, Di Yang","doi":"10.1109/ICRA.2019.8793632","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793632","url":null,"abstract":"In this paper, we present an on-line active pose-graph simultaneous localization and mapping (SLAM) frame-work for robots in three-dimensional (3D) environments using graph topology and sub-maps. This framework aims to find the best trajectory for loop-closure by re-visiting old poses based on the T-optimality and D-optimality metrics of the Fisher information matrix (FIM) in pose-graph SLAM. In order to reduce computational complexity, graph topologies are introduced, including weighted node degree (T-optimality metric) and weighted tree-connectivity (D-optimality metric), to choose a candidate trajectory and several key poses. With the help of the key poses, a sampling-based path planning method and a continuous-time trajectory optimization method are combined hierarchically and applied in the whole framework. So as to further improve the real-time capability of the method, the sub-map joining method is used in the estimation and planning process for large-scale active SLAM problems. In simulations and experiments, we validate our approach by comparing against existing methods, and we demonstrate the on-line planning part using a quad-rotor unmanned aerial vehicle (UAV).","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"67 1","pages":"169-175"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78732343","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.2019.8794061
Hugo Sellet, Imane Khayour, L. Cuvillon, S. Durand, J. Gangloff
This work is a preliminary study assessing the feasibility of using cold-gas thrusters for active damping of flexible cable-driven parallel robots. The concept is validated experimentally on a planar robot embedding custom-built supersonic air thrusters operating at an industry-standard pressure level.
{"title":"Active Damping of Parallel Robots Driven by Flexible Cables Using Cold-Gas Thrusters","authors":"Hugo Sellet, Imane Khayour, L. Cuvillon, S. Durand, J. Gangloff","doi":"10.1109/ICRA.2019.8794061","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794061","url":null,"abstract":"This work is a preliminary study assessing the feasibility of using cold-gas thrusters for active damping of flexible cable-driven parallel robots. The concept is validated experimentally on a planar robot embedding custom-built supersonic air thrusters operating at an industry-standard pressure level.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"43 1","pages":"530-536"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78928941","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.2019.8794015
Drory Lee-Hee, David Zarrouk
In a recent study, we developed a minimally actuated wave-like robot and analyzed its kinematics. In this paper, we present the dynamic locomotion analysis of a miniature version of this wave robot. We examine different crawling environments, determine under which conditions it can advance, and evaluate its propulsion force. We first developed two locomotion models to characterize the cases where the robot is crawling between two straight surfaces or over a single flat surface. We specified the conditions in which the robot will advance and the advance time ratio as a function of the friction forces and weight of the robot. Next, we developed highly flexible tube-like shapes that we molded from silicone rubber to experimentally test the forces acting on the robot inside these tubes. Finally, we designed a miniature model of the robot and experimentally validated its crawling conditions (see video).
{"title":"Locomotion Dynamics of a Miniature Wave-Like Robot, Modeling and Experiments","authors":"Drory Lee-Hee, David Zarrouk","doi":"10.1109/ICRA.2019.8794015","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8794015","url":null,"abstract":"In a recent study, we developed a minimally actuated wave-like robot and analyzed its kinematics. In this paper, we present the dynamic locomotion analysis of a miniature version of this wave robot. We examine different crawling environments, determine under which conditions it can advance, and evaluate its propulsion force. We first developed two locomotion models to characterize the cases where the robot is crawling between two straight surfaces or over a single flat surface. We specified the conditions in which the robot will advance and the advance time ratio as a function of the friction forces and weight of the robot. Next, we developed highly flexible tube-like shapes that we molded from silicone rubber to experimentally test the forces acting on the robot inside these tubes. Finally, we designed a miniature model of the robot and experimentally validated its crawling conditions (see video).","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"19 1","pages":"8422-8428"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88478889","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.2019.8793657
Eleonora Mariotti, Emanuele Magrini, Alessandro De Luca
We present an approach to safe physical Human-Robot Interaction (pHRI) for industrial robots, including collision detection, distinguishing accidental from intentional contacts, and achieving collaborative tasks. Typical industrial robots have a closed control architecture that accepts only velocity/position reference inputs, there are no joint torque sensors, and little or no information is available to the user on robot dynamics and on low-level joint controllers. Nonetheless, taking also advantage of the presence of a Force/Torque (F/T) sensor at the end-effector, a safe pHRI strategy based on kinematic information, on measurements from joint encoders and motor currents, and on end-effector forces/torques can be realized. An admittance control law has been implemented for collaboration in manual guidance mode, with whole-body collision detection in place both when the robot is in autonomous operation and when is simultaneously collaborating with a human. Several pHRI experiments validate the approach on a KUKA KR5 Sixx R650 robot equipped with an ATI F/T sensor.
{"title":"Admittance Control for Human-Robot Interaction Using an Industrial Robot Equipped with a F/T Sensor","authors":"Eleonora Mariotti, Emanuele Magrini, Alessandro De Luca","doi":"10.1109/ICRA.2019.8793657","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793657","url":null,"abstract":"We present an approach to safe physical Human-Robot Interaction (pHRI) for industrial robots, including collision detection, distinguishing accidental from intentional contacts, and achieving collaborative tasks. Typical industrial robots have a closed control architecture that accepts only velocity/position reference inputs, there are no joint torque sensors, and little or no information is available to the user on robot dynamics and on low-level joint controllers. Nonetheless, taking also advantage of the presence of a Force/Torque (F/T) sensor at the end-effector, a safe pHRI strategy based on kinematic information, on measurements from joint encoders and motor currents, and on end-effector forces/torques can be realized. An admittance control law has been implemented for collaboration in manual guidance mode, with whole-body collision detection in place both when the robot is in autonomous operation and when is simultaneously collaborating with a human. Several pHRI experiments validate the approach on a KUKA KR5 Sixx R650 robot equipped with an ATI F/T sensor.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"70 1","pages":"6130-6136"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89376367","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.2019.8793870
Wenyu Zuo, A. Keow, Zheng Chen
Three-dimensionally (3D) maneuverable robotic fish are highly desirable due to their abilities to explore and survey the underwater environment. Existing depth control mechanism is focused on using compressed air or piston to generate volume change, which makes the system bulky and impractical in a small size underwater robot. In this paper, a small and compact 3D maneuverable robotic fish is developed. Instead of using a compressed air tank, the robot is equipped with an on-board water electrolyzer to generate the gases for depth change. The fabricated robotic fish shows fast diving and rising performance. A servo motor is used to generate asymmetric flapping motion on the caudal fin, which leads to a two-dimensionally (2D) planar motion. A 3D dynamic model is then derived for the fabricated robotic fish. Several open-loop control experiments have been conducted to validate the model as well as the design. It has been demonstrated in the experimental results that the robot is capable of generating 3D motion. The robot can achieve 0.13 m/s forward velocity, 30.6 degree/s turning rate, and it takes about 5.5 s to dive to 0.55 m and 10 s to rise.
{"title":"Three-Dimensionally Maneuverable Robotic Fish Enabled by Servo Motor and Water Electrolyser","authors":"Wenyu Zuo, A. Keow, Zheng Chen","doi":"10.1109/ICRA.2019.8793870","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793870","url":null,"abstract":"Three-dimensionally (3D) maneuverable robotic fish are highly desirable due to their abilities to explore and survey the underwater environment. Existing depth control mechanism is focused on using compressed air or piston to generate volume change, which makes the system bulky and impractical in a small size underwater robot. In this paper, a small and compact 3D maneuverable robotic fish is developed. Instead of using a compressed air tank, the robot is equipped with an on-board water electrolyzer to generate the gases for depth change. The fabricated robotic fish shows fast diving and rising performance. A servo motor is used to generate asymmetric flapping motion on the caudal fin, which leads to a two-dimensionally (2D) planar motion. A 3D dynamic model is then derived for the fabricated robotic fish. Several open-loop control experiments have been conducted to validate the model as well as the design. It has been demonstrated in the experimental results that the robot is capable of generating 3D motion. The robot can achieve 0.13 m/s forward velocity, 30.6 degree/s turning rate, and it takes about 5.5 s to dive to 0.55 m and 10 s to rise.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"1 1","pages":"4667-4673"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89757595","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.2019.8793857
J. Stechschulte, N. Ahmed, C. Heckman
When registering 3-D point clouds it is expected that some points in one cloud do not have corresponding points in the other cloud. These non-correspondences are likely to occur near one another, as surface regions visible from one sensor pose are obscured or out of frame for another. In this work, a hidden Markov random field model is used to capture this prior within the framework of the iterative closest point algorithm. The EM algorithm is used to estimate the distribution parameters and learn the hidden component memberships. Experiments are presented demonstrating that this method outperforms several other outlier rejection methods when the point clouds have low or moderate overlap.
{"title":"Robust low-overlap 3-D point cloud registration for outlier rejection","authors":"J. Stechschulte, N. Ahmed, C. Heckman","doi":"10.1109/ICRA.2019.8793857","DOIUrl":"https://doi.org/10.1109/ICRA.2019.8793857","url":null,"abstract":"When registering 3-D point clouds it is expected that some points in one cloud do not have corresponding points in the other cloud. These non-correspondences are likely to occur near one another, as surface regions visible from one sensor pose are obscured or out of frame for another. In this work, a hidden Markov random field model is used to capture this prior within the framework of the iterative closest point algorithm. The EM algorithm is used to estimate the distribution parameters and learn the hidden component memberships. Experiments are presented demonstrating that this method outperforms several other outlier rejection methods when the point clouds have low or moderate overlap.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"27 1","pages":"7143-7149"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89045925","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：