International Journal of Robotics Research最新文献

{"title":"The Before, During, and After of Multi-robot Deadlock","authors":"J. Grover, Changliu Liu, K. Sycara","doi":"10.1177/02783649221074718","DOIUrl":"https://doi.org/10.1177/02783649221074718","url":null,"abstract":"Collision avoidance for multi-robot systems is a well-studied problem. Recently, control barrier functions (CBFs) have been proposed for synthesizing controllers that guarantee collision avoidance and goal stabilization for multiple robots. However, it has been noted that reactive control synthesis methods (such as CBFs) are prone to deadlock, an equilibrium of system dynamics that causes the robots to stall before reaching their goals. In this paper, we analyze the closed-loop dynamics of robots using CBFs, to characterize controller parameters, initial conditions, and goal locations that invariably lead the system to deadlock. Using tools from duality theory, we derive geometric properties of robot configurations of an N robot system once it is in deadlock and we justify them using the mechanics interpretation of KKT conditions. Our key deductions are that (1) system deadlock is characterized by a force equilibrium on robots and (2) deadlock occurs to ensure safety when safety is at the brink of being violated. These deductions allow us to interpret deadlock as a subset of the state space, and we show that this set is non-empty and located on the boundary of the safe set. By exploiting these properties, we analyze the number of admissible robot configurations in deadlock and develop a provably correct decentralized algorithm for deadlock resolution to safely deliver the robots to their goals. This algorithm is validated in simulations as well as experimentally on Khepera-IV robots For an interactive version of this paper, please visit https://arxiv.org/abs/2206.01781.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"42 1","pages":"317 - 336"},"PeriodicalIF":9.2,"publicationDate":"2022-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49532092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid control for combining model-based and model-free reinforcement learning","authors":"Allison Pinosky, Ian Abraham, Alexander Broad, B. Argall, T. Murphey","doi":"10.1177/02783649221083331","DOIUrl":"https://doi.org/10.1177/02783649221083331","url":null,"abstract":"We develop an approach to improve the learning capabilities of robotic systems by combining learned predictive models with experience-based state-action policy mappings. Predictive models provide an understanding of the task and the dynamics, while experience-based (model-free) policy mappings encode favorable actions that override planned actions. We refer to our approach of systematically combining model-based and model-free learning methods as hybrid learning. Our approach efficiently learns motor skills and improves the performance of predictive models and experience-based policies. Moreover, our approach enables policies (both model-based and model-free) to be updated using any off-policy reinforcement learning method. We derive a deterministic method of hybrid learning by optimally switching between learning modalities. We adapt our method to a stochastic variation that relaxes some of the key assumptions in the original derivation. Our deterministic and stochastic variations are tested on a variety of robot control benchmark tasks in simulation as well as a hardware manipulation task. We extend our approach for use with imitation learning methods, where experience is provided through demonstrations, and we test the expanded capability with a real-world pick-and-place task. The results show that our method is capable of improving the performance and sample efficiency of learning motor skills in a variety of experimental domains.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"42 1","pages":"337 - 355"},"PeriodicalIF":9.2,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44538438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reactivity and statefulness: Action-based sensors, plans, and necessary state","authors":"Grace McFassel, Dylan A. Shell","doi":"10.1177/02783649221078874","DOIUrl":"https://doi.org/10.1177/02783649221078874","url":null,"abstract":"Typically to a roboticist, a plan is the outcome of other work, a synthesized object that realizes ends defined by some problem; plans qua plans are seldom treated as first-class objects of study. Plans designate functionality: a plan can be viewed as defining a robot’s behavior throughout its execution. This informs and reveals many other aspects of the robot’s design, including: necessary sensors and action choices, history, state, task structure, and how to define progress. Interrogating sets of plans helps in comprehending the ways in which differing executions influence the interrelationships between these various aspects. Revisiting Erdmann’s theory of action-based sensors, a classical approach for characterizing fundamental information requirements, we show how plans (in their role of designating behavior) influence sensing requirements. Using an algorithm for enumerating plans, we examine how some plans for which no action-based sensor exists can be transformed into sets of sensors through the identification and handling of features that preclude the existence of action-based sensors. We are not aware of those obstructing features having been previously identified. Action-based sensors may be treated as standalone reactive plans; we relate them to the set of all possible plans through a lattice structure. This lattice reveals a boundary between plans with action-based sensors and those without. Some plans, specifically those that are not reactive plans and require some notion of internal state, can never have associated action-based sensors. Even so, action-based sensors can serve as a framework to explore and interpret how such plans make use of state.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"42 1","pages":"385 - 411"},"PeriodicalIF":9.2,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43006505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Locally connected interrelated network: A forward propagation primitive","authors":"Nicholas Collins, H. Kurniawati","doi":"10.1177/02783649221093092","DOIUrl":"https://doi.org/10.1177/02783649221093092","url":null,"abstract":"End-to-end learning for planning is a promising approach for finding good robot strategies in situations where the state transition, observation, and reward functions are initially unknown. Many neural network architectures for this approach have shown positive results. Across these networks, seemingly small components have been used repeatedly in different architectures, which means improving the efficiency of these components has great potential to improve the overall performance of the network. This paper aims to improve one such component: The forward propagation module. In particular, we propose Locally Connected Interrelated Network (LCI-Net) – a novel type of locally connected layer with unshared but interrelated weights – to improve the efficiency of learning stochastic transition models for planning and propagating information via the learned transition models. LCI-Net is a small differentiable neural network module that can be plugged into various existing architectures. For evaluation purposes, we apply LCI-Net to VIN and QMDP-Net. VIN is an end-to-end neural network for solving Markov Decision Processes (MDPs) whose transition and reward functions are initially unknown, while QMDP-Net is its counterpart for the Partially Observable Markov Decision Process (POMDP) whose transition, observation, and reward functions are initially unknown. Simulation tests on benchmark problems involving 2D and 3D navigation and grasping indicate promising results: Changing only the forward propagation module alone with LCI-Net improves VIN’s and QMDP-Net generalisation capability by more than 3× and 10×, respectively.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"42 1","pages":"371 - 384"},"PeriodicalIF":9.2,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48996411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic encoding and repair of reactive high-level tasks with learned abstract representations","authors":"Adam Pacheck, Steven D. James, G. Konidaris, H. Kress-Gazit","doi":"10.1177/02783649231167207","DOIUrl":"https://doi.org/10.1177/02783649231167207","url":null,"abstract":"We present a framework for the automatic encoding and repair of high-level tasks. Given a set of skills a robot can perform, our approach first abstracts sensor data into symbols and then automatically encodes the robot’s capabilities in Linear Temporal Logic (LTL). Using this encoding, a user can specify reactive high-level tasks, for which we can automatically synthesize a strategy that executes on the robot, if the task is feasible. If a task is not feasible given the robot’s capabilities, we present two methods, one enumeration-based and one synthesis-based, for automatically suggesting additional skills for the robot or modifications to existing skills that would make the task feasible. We demonstrate our framework on a Baxter robot manipulating blocks on a table, a Baxter robot manipulating plates on a table, and a Kinova arm manipulating vials, with multiple sensor modalities, including raw images.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"42 1","pages":"263 - 288"},"PeriodicalIF":9.2,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49515007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetic concentric tube robots: Introduction and analysis","authors":"Quentin Peyron, Q. Boehler, P. Rougeot, Pierre Roux, B. Nelson, N. Andreff, K. Rabenorosoa, P. Renaud","doi":"10.1177/02783649211071113","DOIUrl":"https://doi.org/10.1177/02783649211071113","url":null,"abstract":"In this paper, we propose a new type of continuum robot, referred to as a magnetic concentric tube robot (M-CTR), for performing minimally invasive surgery in narrow and difficult-to-access areas. The robot combines concentric tubes and magnetic actuation to benefit from the ‘follow the leader’ behaviour, the dexterity and stability of existing robots, while targeting millimetre-sized external diameters. These three kinematic properties are assessed through numerical and experimental studies performed on a prototype of a M-CTR. They are performed with general forward and inverse kineto-static models of the robot, continuation and bifurcation analysis, and a specific experimental setup. The prototype presents unique capabilities in terms of deployment and active stability management, while its dexterity in terms of tip orientability is also among the best reported for other robots at its scale.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"41 1","pages":"418 - 440"},"PeriodicalIF":9.2,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43318229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequential contact-based adaptive grasping for robotic hands","authors":"G. J. Pollayil, M. J. Pollayil, M. Catalano, A. Bicchi, G. Grioli","doi":"10.1177/02783649221081154","DOIUrl":"https://doi.org/10.1177/02783649221081154","url":null,"abstract":"This paper proposes a novel type of grasping strategy that draws inspiration from the role of touch and the importance of wrist motions in human grasping. The proposed algorithm, which we call Sequential Contact-based Adaptive Grasping, can be used to reactively modify a given grasp plan according to contacts arising between the hand and the object. This technique, based on a systematic constraint categorization and an iterative task inversion procedure, is shown to lead to synchronized motions of the fingers and the wrist, as it can be observed in humans, and to increase grasp success rate by substantially mitigating the relevant problems of object slippage during hand closure and of uncertainties caused by the environment and by the perception system. After describing the grasping problem in its quasi-static aspects, the algorithm is derived and discussed with some simple simulations. The proposed method is general as it can be applied to different kinds of robotic hands. It refines a priori defined grasp plans and significantly reduces their accuracy requirements by relying only on a forward kinematic model and elementary contact information. The efficacy of our approach is confirmed by experimental results of tests performed on a collaborative robot manipulator equipped with a state-of-the-art underactuated soft hand.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"41 1","pages":"543 - 570"},"PeriodicalIF":9.2,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46066998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RadarSLAM: A robust simultaneous localization and mapping system for all weather conditions","authors":"Ziyang Hong, Y. Pétillot, Andrew M. Wallace, Sen Wang","doi":"10.1177/02783649221080483","DOIUrl":"https://doi.org/10.1177/02783649221080483","url":null,"abstract":"A Simultaneous Localization and Mapping (SLAM) system must be robust to support long-term mobile vehicle and robot applications. However, camera and LiDAR based SLAM systems can be fragile when facing challenging illumination or weather conditions which degrade the utility of imagery and point cloud data. Radar, whose operating electromagnetic spectrum is less affected by environmental changes, is promising although its distinct sensor model and noise characteristics bring open challenges when being exploited for SLAM. This paper studies the use of a Frequency Modulated Continuous Wave radar for SLAM in large-scale outdoor environments. We propose a full radar SLAM system, including a novel radar motion estimation algorithm that leverages radar geometry for reliable feature tracking. It also optimally compensates motion distortion and estimates pose by joint optimization. Its loop closure component is designed to be simple yet efficient for radar imagery by capturing and exploiting structural information of the surrounding environment. Extensive experiments on three public radar datasets, ranging from city streets and residential areas to countryside and highways, show competitive accuracy and reliability performance of the proposed radar SLAM system compared to the state-of-the-art LiDAR, vision and radar methods. The results show that our system is technically viable in achieving reliable SLAM in extreme weather conditions on the RADIATE Dataset, for example, heavy snow and dense fog, demonstrating the promising potential of using radar for all-weather localization and mapping.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"41 1","pages":"519 - 542"},"PeriodicalIF":9.2,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47655744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Planning to chronicle: Optimal policies for narrative observation of unpredictable events","authors":"Hazhar Rahmani, Dylan A. Shell, J. O’Kane","doi":"10.1177/02783649211069154","DOIUrl":"https://doi.org/10.1177/02783649211069154","url":null,"abstract":"One important class of applications entails a robot scrutinizing, monitoring, or recording the evolution of an uncertain time-extended process. This sort of situation leads to an interesting family of active perception problems that can be cast as planning problems in which the robot is limited in what it sees and must, thus, choose what to pay attention to. The distinguishing characteristic of this setting is that the robot has influence over what it captures via its sensors, but exercises no causal authority over the process evolving in the world. As such, the robot’s objective is to observe the underlying process and to produce a “chronicle” of occurrent events, subject to a goal specification of the sorts of event sequences that may be of interest. This paper examines variants of such problems in which the robot aims to collect sets of observations to meet a rich specification of their sequential structure. We study this class of problems by modeling a stochastic process via a variant of a hidden Markov model and specify the event sequences of interest as a regular language, developing a vocabulary of “mutators” that enable sophisticated requirements to be expressed. Under different suppositions on the information gleaned about the event model, we formulate and solve different planning problems. The core underlying idea is the construction of a product between the event model and a specification automaton. Using this product, we compute a policy that minimizes the expected number of steps to reach a goal state. We introduce a general algorithm for this problem as well as several more efficient algorithms for important special cases. The paper reports and compares performance metrics by drawing on some small case studies analyzed in depth via simulation. Specifically, we study the effect of the robot’s observation model on the average time required for the robot to record a desired story. We also compare our algorithm with a baseline greedy algorithm, showing that our algorithm outperforms the greedy algorithm in terms of the average time to record a desired story. In addition, experiments show that the algorithms tailored to specialized variants of the problem are rather more efficient than the general algorithm.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"42 1","pages":"412 - 432"},"PeriodicalIF":9.2,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48632765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Boreas: A multi-season autonomous driving dataset","authors":"Keenan Burnett, David J. Yoon, Yuchen Wu, A. Z. Li, Haowei Zhang, Shichen Lu, Jingxing Qian, Wei-Kang Tseng, A. Lambert, K. Leung, Angela P. Schoellig, T. Barfoot","doi":"10.1177/02783649231160195","DOIUrl":"https://doi.org/10.1177/02783649231160195","url":null,"abstract":"The Boreas dataset was collected by driving a repeated route over the course of 1 year, resulting in stark seasonal variations and adverse weather conditions such as rain and falling snow. In total, the Boreas dataset includes over 350 km of driving data featuring a 128-channel Velodyne Alpha-Prime lidar, a 360° Navtech CIR304-H scanning radar, a 5MP FLIR Blackfly S camera, and centimetre-accurate post-processed ground truth poses. Our dataset will support live leaderboards for odometry, metric localization, and 3D object detection. The dataset and development kit are available at boreas.utias.utoronto.ca.","PeriodicalId":54942,"journal":{"name":"International Journal of Robotics Research","volume":"42 1","pages":"33 - 42"},"PeriodicalIF":9.2,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48399630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}