R. Eustice, Hanumant Singh, J. Leonard, Matthew R. Walter, R. Ballard
This paper describes a vision-based large-area simultaneous localization and mapping (SLAM) algorithm that respects the constraints of low-overlap imagery typical of underwater vehicles while exploiting the information associated with the inertial sensors that are routinely available on such platforms. We present a novel strategy for efficiently accessing and maintaining consistent covariance bounds within a SLAM information filter, greatly increasing the reliability of data association. The technique is based upon solving a sparse system of linear equations coupled with the application of constant-time Kalman updates. The method is shown to produce consistent covariance estimates suitable for robot planning and data association. Realworld results are presented for a vision-based 6 DOF SLAM implementation using data from a recent ROV survey of the wreck of the RMS Titanic.
{"title":"Visually Navigating the RMS Titanic with SLAM Information Filters","authors":"R. Eustice, Hanumant Singh, J. Leonard, Matthew R. Walter, R. Ballard","doi":"10.15607/RSS.2005.I.008","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.008","url":null,"abstract":"This paper describes a vision-based large-area simultaneous localization and mapping (SLAM) algorithm that respects the constraints of low-overlap imagery typical of underwater vehicles while exploiting the information associated with the inertial sensors that are routinely available on such platforms. We present a novel strategy for efficiently accessing and maintaining consistent covariance bounds within a SLAM information filter, greatly increasing the reliability of data association. The technique is based upon solving a sparse system of linear equations coupled with the application of constant-time Kalman updates. The method is shown to produce consistent covariance estimates suitable for robot planning and data association. Realworld results are presented for a vision-based 6 DOF SLAM implementation using data from a recent ROV survey of the wreck of the RMS Titanic.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"70 1","pages":"57-64"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86255399","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}
Here we introduce one simulated and two physical three-dimensional stochastic modular robot systems, all capable of self-assembly and self-reconfiguration. We assume that individual units can only draw power when attached to the growing structure, and have no means of actuation. Instead they are subject to random motion induced by the surrounding medium when unattached. We present a simulation environment with a flexible scripting language that allows for parallel and serial selfassembly and self-reconfiguration processes. We explore factors that govern the rate of assembly and reconfiguration, and show that self-reconfiguration can be exploited to accelerate the assembly of a particular shape, as compared with static self-assembly. We then demonstrate the ability of two different physical three-dimensional stochastic modular robot systems to self-reconfigure in a fluid. The second physical implementation is only composed of technologies that could be scaled down to achieve stochastic self-assembly and self-reconfiguration at the microscale.
{"title":"Three Dimensional Stochastic Reconfiguration of Modular Robots","authors":"P. White, V. Zykov, J. Bongard, Hod Lipson","doi":"10.15607/RSS.2005.I.022","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.022","url":null,"abstract":"Here we introduce one simulated and two physical three-dimensional stochastic modular robot systems, all capable of self-assembly and self-reconfiguration. We assume that individual units can only draw power when attached to the growing structure, and have no means of actuation. Instead they are subject to random motion induced by the surrounding medium when unattached. We present a simulation environment with a flexible scripting language that allows for parallel and serial selfassembly and self-reconfiguration processes. We explore factors that govern the rate of assembly and reconfiguration, and show that self-reconfiguration can be exploited to accelerate the assembly of a particular shape, as compared with static self-assembly. We then demonstrate the ability of two different physical three-dimensional stochastic modular robot systems to self-reconfigure in a fluid. The second physical implementation is only composed of technologies that could be scaled down to achieve stochastic self-assembly and self-reconfiguration at the microscale.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"23 1","pages":"161-168"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81646150","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}
Motion planning research has been successful in developing planning algorithms which are effective for solving problems with complicated geometric and kinematic constraints. Various applications in robotics and in other fields demand additional physical realism. Some progress has been made for non-holonomic systems. However systems with significant dr ift, underactuation and discrete system changes remain challenging for existing planning techniques particularly as the dimensional- ity of the state space increases. In this paper, we demonstrate a motion planning technique for the solution of problems with these challenging characteristics. Our approach uses sampling-based motion planning and subdivision methods. The problem that we solve is a game that was chosen to exemplify characteristics of dynamical systems that are difficult for planning. To our knowledge, this is first application of algorithmic motion p lanning to a problem of this type and complexity.
{"title":"Motion Planning in the Presence of Drift, Underactuation and Discrete System Changes","authors":"Andrew M. Ladd, L. Kavraki","doi":"10.15607/RSS.2005.I.031","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.031","url":null,"abstract":"Motion planning research has been successful in developing planning algorithms which are effective for solving problems with complicated geometric and kinematic constraints. Various applications in robotics and in other fields demand additional physical realism. Some progress has been made for non-holonomic systems. However systems with significant dr ift, underactuation and discrete system changes remain challenging for existing planning techniques particularly as the dimensional- ity of the state space increases. In this paper, we demonstrate a motion planning technique for the solution of problems with these challenging characteristics. Our approach uses sampling-based motion planning and subdivision methods. The problem that we solve is a game that was chosen to exemplify characteristics of dynamical systems that are difficult for planning. To our knowledge, this is first application of algorithmic motion p lanning to a problem of this type and complexity.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"1999 1","pages":"233-240"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88269611","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}
Haptic rendering involving deformable objects has seen many applications, from surgical simulation and training, to virtual prototyping, to teleoperation, etc. High quality rendering demands both physical fidelity and real-time performance, which are often conflicting requirements. In this paper, we simulate contact force between a held rigid body and an elastic object and the corresponding shape deformation of the elastic object efficiently and realistically based on a nonlinear physical model and a novel beam-skeleton model, taking into account friction, compliant motion, and multiple contact regions. Our approach is able to achieve a combined update rate of over 1 kHz in realistic, smooth, and stable rendering, as demonstrated by our implemented examples.
{"title":"Modeling Complex Contacts Involving Deformable Objects for Haptic and Graphic Rendering","authors":"Qi Luo, J. Xiao","doi":"10.15607/RSS.2005.I.021","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.021","url":null,"abstract":"Haptic rendering involving deformable objects has seen many applications, from surgical simulation and training, to virtual prototyping, to teleoperation, etc. High quality rendering demands both physical fidelity and real-time performance, which are often conflicting requirements. In this paper, we simulate contact force between a held rigid body and an elastic object and the corresponding shape deformation of the elastic object efficiently and realistically based on a nonlinear physical model and a novel beam-skeleton model, taking into account friction, compliant motion, and multiple contact regions. Our approach is able to achieve a combined update rate of over 1 kHz in realistic, smooth, and stable rendering, as demonstrated by our implemented examples.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"81 10 1","pages":"153-160"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89581474","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}
This paper introduces a dynamic map for mobile robots that adapts continuously over time. It resolves the stability plasticity dilemma (the tradeoff between adaptation to new patterns and preservation of old patterns) by representing the environment over multiple time scales simultaneously (five in our experiments). A sample-based representation is proposed, where older memories fade at different rates depending on the time scale. Robust statistics are used to interpret the samples. It is shown that this approach can track both stationary and non-stationary elements of the environment, covering the full spectrum of variations from moving objects to structural changes. The method was evaluated in a five-week experiment in a real dynamic environment. Experimental results show that the resulting map is stable, improves its quality over time and adapts to changes.
{"title":"Dynamic Maps for Long-Term Operation of Mobile Service Robots","authors":"P. Biber, T. Duckett","doi":"10.15607/RSS.2005.I.003","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.003","url":null,"abstract":"This paper introduces a dynamic map for mobile robots that adapts continuously over time. It resolves the stability plasticity dilemma (the tradeoff between adaptation to new patterns and preservation of old patterns) by representing the environment over multiple time scales simultaneously (five in our experiments). A sample-based representation is proposed, where older memories fade at different rates depending on the time scale. Robust statistics are used to interpret the samples. It is shown that this approach can track both stationary and non-stationary elements of the environment, covering the full spectrum of variations from moving objects to structural changes. The method was evaluated in a five-week experiment in a real dynamic environment. Experimental results show that the resulting map is stable, improves its quality over time and adapts to changes.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"549 1","pages":"17-24"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77839167","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}
Edwin Olson, Matthew R. Walter, S. Teller, J. Leonard
We present SCGP, an algorithm for finding a single cluster of well-connected nodes in a graph. The general problem is NP-hard, but our algorithm produces an approximate solution in O(N 2 ) time by considering the spectral properties of the graph's adjacency matrix. We show how this algorithm can be used to find sets of self-consistent hypotheses while rejecting incorrect hypotheses, a problem that frequently arises in robotics. We present results from a range-only SLAM system, a polynomial time data association algorithm, and a method for parametric line fitting that can outperform RANSAC.
{"title":"Single-Cluster Spectral Graph Partitioning for Robotics Applications","authors":"Edwin Olson, Matthew R. Walter, S. Teller, J. Leonard","doi":"10.15607/RSS.2005.I.035","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.035","url":null,"abstract":"We present SCGP, an algorithm for finding a single cluster of well-connected nodes in a graph. The general problem is NP-hard, but our algorithm produces an approximate solution in O(N 2 ) time by considering the spectral properties of the graph's adjacency matrix. We show how this algorithm can be used to find sets of self-consistent hypotheses while rejecting incorrect hypotheses, a problem that frequently arises in robotics. We present results from a range-only SLAM system, a polynomial time data association algorithm, and a method for parametric line fitting that can outperform RANSAC.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"49 1","pages":"265-272"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80710011","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}
Efficient motion planning is obtained by focusing computation on relevant regions of configuration space. In t he following we propose a new approach to multi-query samplingbased motion planning, which exploits information obtained from earlier exploration and its current state to guide exploration. This approach attempts to minimize the selection of samples to th ose required to completely capture configuration space connect ivity. Our planner constructs an approximate model of configuration space that is used in conjunction with a utility function to select configurations with maximal expected importance giv en the planner’s current state. The resulting utility-guided planner is online and adaptive. Its behavior adjusts to the developi ng state of the motion planner and its understanding of the confi guration space. Experimental comparisons with existing planners show that this utility-guided approach significantly decreases the runtime required for motion planning.
{"title":"Toward Optimal Configuration Space Sampling","authors":"B. Burns, O. Brock","doi":"10.15607/RSS.2005.I.015","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.015","url":null,"abstract":"Efficient motion planning is obtained by focusing computation on relevant regions of configuration space. In t he following we propose a new approach to multi-query samplingbased motion planning, which exploits information obtained from earlier exploration and its current state to guide exploration. This approach attempts to minimize the selection of samples to th ose required to completely capture configuration space connect ivity. Our planner constructs an approximate model of configuration space that is used in conjunction with a utility function to select configurations with maximal expected importance giv en the planner’s current state. The resulting utility-guided planner is online and adaptive. Its behavior adjusts to the developi ng state of the motion planner and its understanding of the confi guration space. Experimental comparisons with existing planners show that this utility-guided approach significantly decreases the runtime required for motion planning.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"549 1","pages":"105-112"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79641082","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}
This paper describes an efficient approach to (self) collision detection and distance computations for complex articulated mechanisms such as molecular chains. The proposed algorithm called BioCD is particularly designed for samplingbased motion planning on molecular models described by long kinematic chains possibly including cycles. The algorithm considers that the kinematic chain is structured into a number of rigid groups articulated by preselected degrees of freedom. This structuring is exploited by a two-level spatially-adapted hierarchy. The proposed algorithm is not limited to particular kinematic topologies and allows good collision detection times. BioCD is also tailored to deal with the particularities imposed by the molecular context on collision detection. Experimental results show the effectiveness of the proposed approach which is able to process thousands of (self) collision tests per second on flexible protein models with up to hundreds of degrees of freedom.
{"title":"BioCD : An Efficient Algorithm for Self-collision and Distance Computation between Highly Articulated Molecular Models","authors":"V. R. D. Angulo, Juan Cortés, T. Siméon","doi":"10.15607/RSS.2005.I.032","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.032","url":null,"abstract":"This paper describes an efficient approach to (self) collision detection and distance computations for complex articulated mechanisms such as molecular chains. The proposed algorithm called BioCD is particularly designed for samplingbased motion planning on molecular models described by long kinematic chains possibly including cycles. The algorithm considers that the kinematic chain is structured into a number of rigid groups articulated by preselected degrees of freedom. This structuring is exploited by a two-level spatially-adapted hierarchy. The proposed algorithm is not limited to particular kinematic topologies and allows good collision detection times. BioCD is also tailored to deal with the particularities imposed by the molecular context on collision detection. Experimental results show the effectiveness of the proposed approach which is able to process thousands of (self) collision tests per second on flexible protein models with up to hundreds of degrees of freedom.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"70 1","pages":"241-248"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83747296","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}
We develop decentralized cooperative controllers, which are based on local navigation functions and yield (almost) global asymptotic stability of a group of mobile agents to a desired formation and simultaneous collision avoidance. The formation could be achieved anywhere in the free space; there are no pre-specified final positions for the agents and is rendered stable both in terms of shape and in terms of orientation. Shape and orientation stabilization is possible because the agents regulate relative positions rather than distances with respect to their network neighbors. Asymptotic stability is provable and guaranteed, once the parameters in the local navigation functions are tuned based on the geometry of the environment and the degree of the interconnection network. Feedback controllers steer the agents away from stationary point-obstacles and into the desired formation using information that can be obtained within their sensing neighborhood and through communication with their network neighbors. The methodology is tested in simulation where groups of three and four mobile agents come into formations of triangles and diamonds, navigating amongst obstacles.
{"title":"Formation Stabilization of Multiple Agents Using Decentralized Navigation Functions","authors":"H. Tanner, Amit Kumar","doi":"10.15607/RSS.2005.I.007","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.007","url":null,"abstract":"We develop decentralized cooperative controllers, which are based on local navigation functions and yield (almost) global asymptotic stability of a group of mobile agents to a desired formation and simultaneous collision avoidance. The formation could be achieved anywhere in the free space; there are no pre-specified final positions for the agents and is rendered stable both in terms of shape and in terms of orientation. Shape and orientation stabilization is possible because the agents regulate relative positions rather than distances with respect to their network neighbors. Asymptotic stability is provable and guaranteed, once the parameters in the local navigation functions are tuned based on the geometry of the environment and the degree of the interconnection network. Feedback controllers steer the agents away from stationary point-obstacles and into the desired formation using information that can be obtained within their sensing neighborhood and through communication with their network neighbors. The methodology is tested in simulation where groups of three and four mobile agents come into formations of triangles and diamonds, navigating amongst obstacles.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"1 1","pages":"49-56"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82830805","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}
Abstract : We address the problem of testing complex reactive control systems and validating the effectiveness of multi-agent controllers. Testing and validation involve searching for conditions that lead to system failure by exploring all adversarial inputs and disturbances for errant trajectories. This problem of testing is related to motion planning, with one main difference. Unlike motion planning problems, systems are typically not controllable with respect to disturbances or adversarial inputs and therefore, the reachable set of states is a small subset of the entire state space. In both cases however, there is a goal or specification set consisting of a set of points in state space that is of interest, either for demonstrating failure or for validation. In this paper we consider the application of the Rapidly exploring Random Tree algorithm to the testing and validation problem. Because of the differences between testing and motion planning, we propose three modifications to the original RRT algorithm. First, we introduce a new distance function which incorporates information about the system's dynamics to select nodes for extension. Second, we introduce a weighting to penalize nodes which are repeatedly selected but fail to extend. Third we propose a scheme for adaptively modifying the sampling probability distribution based on tree growth. We demonstrate the application of the algorithm via three simple and one large scale example and provide computational statistics. Our algorithms are applicable beyond the testing problem to motion planning for systems that are not small time locally controllable.
{"title":"An RRT-Based Algorithm for Testing and Validating Multi-Robot Controllers","authors":"Jongwoo Kim, J. Esposito, Vijay R. Kumar","doi":"10.15607/RSS.2005.I.033","DOIUrl":"https://doi.org/10.15607/RSS.2005.I.033","url":null,"abstract":"Abstract : We address the problem of testing complex reactive control systems and validating the effectiveness of multi-agent controllers. Testing and validation involve searching for conditions that lead to system failure by exploring all adversarial inputs and disturbances for errant trajectories. This problem of testing is related to motion planning, with one main difference. Unlike motion planning problems, systems are typically not controllable with respect to disturbances or adversarial inputs and therefore, the reachable set of states is a small subset of the entire state space. In both cases however, there is a goal or specification set consisting of a set of points in state space that is of interest, either for demonstrating failure or for validation. In this paper we consider the application of the Rapidly exploring Random Tree algorithm to the testing and validation problem. Because of the differences between testing and motion planning, we propose three modifications to the original RRT algorithm. First, we introduce a new distance function which incorporates information about the system's dynamics to select nodes for extension. Second, we introduce a weighting to penalize nodes which are repeatedly selected but fail to extend. Third we propose a scheme for adaptively modifying the sampling probability distribution based on tree growth. We demonstrate the application of the algorithm via three simple and one large scale example and provide computational statistics. Our algorithms are applicable beyond the testing problem to motion planning for systems that are not small time locally controllable.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"138 1","pages":"249-256"},"PeriodicalIF":0.0,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86522366","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：