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Quorum sensing without deliberation: biological inspiration for externalizing computation to physical spaces in multi-robot systems

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SWARM INTELLIGENCE 2021年第1-2期15卷 171-203页

作者： Pavlic, Theodore P. Hanson, Jake Valentini, Gabriele Walker, Sara Imari Pratt, Stephen C. Arizona State Univ Sch Comp Informat & Decis Syst Engn Tempe AZ 85281 USA Arizona State Univ Sch Sustainabil Tempe AZ 85281 USA Arizona State Univ Sch Complex Adapt Syst Tempe AZ 85281 USA Arizona State Univ BEYOND Ctr Fundamental Concepts Sci Tempe AZ 85281 USA Arizona State Univ Sch Life Sci Tempe AZ 85281 USA Arizona State Univ Sch Earth & Space Explorat Tempe AZ USA

Quorum sensing (QS) is ubiquitous in distributed, multi-agent systems in nature-from bacteria to arthropods to primates-and has been proposed as a useful distributed algorithm in engineered systems-from multi-robot systems to Internet server farms. Achieving QS requires groups to collectively integrate information about their numbers and reach consensus on an action contingent upon those numbers. In nest-site selection tasks that employ QS in ants, sensitivity to encounter rate has been implicated as a mechanism for how individuals sense that quorum has been reached. However, little is known about how individual ants estimate proximity to the critical rate. Ant-inspired QS algorithms proposed by computer scientists either heavily depend on communication between agents or the ability for individual agents to accumulate information over many encounters with others. Both communication and significant memory storage may be beyond the simple capabilities of small-scale robots in large collectives. Alternatively, if cognition was embodied across the group of agents and their physical environment, cognitive abilities could far exceed the abilities of each individual. Toward this end, we propose a novel bio-inspired algorithm for QS on mobile agents within a confined space. Our approach does not require individuals to communicate or count over long sequences of encounters;instead, QS emerges from the random interaction of mobile excitable agents with each other and the physical cavity. We validate theoretical predictions for our algorithm's performance in simulation, and we also show that it has good qualitative agreement with accuracy and response-time data from real ants. More broadly, our algorithm provides a new, concrete example of how ants can serve as conceptual models for hypothetical dynamic networks of mobile neurons.

关键词： Quorum sensing Collective decision making Bio-inspired Cognition Multi-agent systems Multi-robot systems Swarms distributed robot systems

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Cascaded Filtering Using the Sigma Point Transformation

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IEEE robotICS AND AUTOMATION LETTERS 2021年第3期6卷 4758-4765页

作者： Shalaby, Mohammed Cossette, Charles Champagne Le Ny, Jerome Forbes, James Richard McGill Univ Dept Mech Engn Montreal PQ H3A 0C3 Canada Polytech Montreal Dept Elect Engn Montreal PQ H3T 1J4 Canada

It is often convenient to separate a state estimation task into smaller "local" tasks, where each local estimator estimates a subset of the overall system state. However, neglecting cross-covariance terms between state estimates can result in overconfident estimates, which can ultimately degrade the accuracy of the estimator. Common cascaded filtering techniques focus on the problem of modelling cross-covariances when the local estimators share a common state vector. This letter introduces a novel cascaded and decentralized filtering approach that approximates the cross-covariances when the local estimators consider distinct state vectors. The proposed estimator is validated in simulations and in experiments on a three-dimensional attitude and position estimation problem. The proposed approach is compared to a naive cascaded filtering approach that neglects cross-covariance terms, a sigma point-based Covariance Intersection filter, and a full-state filter. In both simulations and experiments, the proposed filter outperforms the naive and the Covariance Intersection filters, while performing comparatively to the full-state filter.

关键词： State estimation Random variables Covariance matrices Task analysis Noise measurement Kalman filters Estimation error Sensor fusion distributed robot systems

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Design, Control, and Motion Strategy of TRADY: Tilted-Rotor-Equipped Aerial robot With Autonomous In-Flight Assembly and Disassembly Ability

ADVANCED INTELLIGENT SYSTEMS

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ADVANCED INTELLIGENT systems 2023年第10期5卷

作者： Sugihara, Junichiro Nishio, Takuzumi Nagato, Keisuke Nakao, Masayuki Zhao, Moju Univ Tokyo Dept Mechanoinfomat Bunkyo ku Tokyo 1138656 Japan Univ Tokyo Dept Mech Engn Bunkyo ku Tokyo 1138656 Japan

State-of-the-art aerial robots often prioritize maneuverability or manipulation capabilities, making it difficult to achieve both. The issue arises because aerial robots with agile mobility lack sufficient rotors for manipulation tasks, while those with manipulation ability are too large for agile mobility. To tackle this problem, a novel aerial robot unit named TRADY, tilted-rotor-equipped aerial robot with autonomous in-flight assembly and disassembly capability, is introduced. The TRADY unit can self-assemble/disassemble with another unit in mid-air, adjusting the aircraft's control freedom by switching between under-actuated and fully-actuated control models. The system implementation involves a docking mechanism design, optimized rotor configuration, as well as a control system with the ability to switch between under-actuated and fully-actuated controllers. A proposed state transition method compensates for discrete changes during the controller switchover process. Also, a motion strategy for assembly/disassembly with hazardous condition recovery behavior is presented. Finally, through experiments, TRADY demonstrated a 90 % success rate in executing assembly/disassembly motions, and in the assembly state, it can utilize full-pose tracking and generate over nine times the torque of a single unit. This is the first aerial robot developed to perform both assembly and disassembly while seamlessly transitioning between fully-actuated and under-actuated models.

关键词： aerial assembly and disassembly aerial robot cellular and modular robots distributed robot systems

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Decentralized Localization in Homogeneous Swarms Considering Real-World Non-Idealities

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IEEE robotICS AND AUTOMATION LETTERS 2021年第4期6卷 6765-6772页

作者： Wang, Hanlin Rubenstein, Michael Northwestern Univ Dept Comp Sci Evanston IL 60601 USA Northwestern Univ Dept Comp Sci Evanston IL 60208 USA Northwestern Univ Dept Mech Engn Evanston IL 60208 USA

This letter presents a decentralized algorithm that allows a swarm of identically programmed agents to cooperatively estimate their global poses using local range and bearing measurements. The design of our algorithm explicitly considers the phase asynchrony of each agent's local clock, moreover, the execution of our algorithm does not require each agent to actively keep the same neighbors over time. A theoretical analysis about the effect of each agent's sensing noise and communication loss is given, in addition, we validate the presented algorithm via experiments running on a swarm of up to 256 simulated robots and a swarm of 100 physical robots. The results from the experiments show that the presented algorithm allows each agent to estimate its global pose quickly and reliably. Video of 100 robots executing the presented algorithm as well as supplementary material can be found in [1] and [2].

关键词： Terms-Swarms distributed robot systems sensor networks

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Neural Tree Expansion for Multi-robot Planning in Non-Cooperative Environments

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IEEE robotICS AND AUTOMATION LETTERS 2021年第4期6卷 6868-6875页

作者： Riviere, Benjamin Honig, Wolfgang Anderson, Matthew Chung, Soon-Jo CALTECH Grad Aerosp Labs Pasadena CA 91125 USA

We present a self-improving, Neural Tree Expansion (NTE) method for multi-robot online planning in non-cooperative environments, where each robot attempts to maximize its cumulative reward while interacting with other self-interested robots. Our algorithm adapts the centralized, perfect information, discrete-action space method from AlphaZero to a decentralized, partial information, continuous action space setting for multi-robot applications. Our method has three interacting components: (i) a centralized, perfect-information "expert" Monte Carlo Tree Search (MCTS) with large computation resources that provides expert demonstrations, (ii) a decentralized, partial-information "learner" MCTS with small computation resources that runs in real-time and provides self-play examples, and (iii) policy & value neural networks that are trained with the expert demonstrations and bias both the expert and the learner tree growth. Our numerical experiments demonstrate Neural Tree Expansion's computational advantage by finding better solutions than a MCTS with 20 times more resources. The resulting policies are dynamically sophisticated, demonstrate coordination between robots, and play the Reach-Target-Avoid differential game significantly better than the state-of-the-art control-theoretic baseline for multi-robot, double-integrator systems. Our hardware experiments on an aerial swarm demonstrate the computational advantage of Neural Tree Expansion, enabling online planning at 20 Hz with effective policies in complex scenarios.

关键词： distributed robot systems motion and path planning reinforcement learning

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distributed decentralized EKF for very large-scale networks with application to satellite mega-constellations navigation

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CONTROL ENGINEERING PRACTICE 2023年第1期135卷

作者： Pedroso, Leonardo Batista, Pedro Univ Lisbon Inst Syst & Robot Inst Super Tecn Lisbon Portugal

The design of a decentralized and distributed filtering solution for large-scale networks of interconnected systems is addressed considering (i) generic nonlinear dynamics and (ii) generic coupled nonlinear outputs in a generic, possibly time-varying, topology. The local filters, which follow the structure of the extended Kalman filter, are implemented in each system, which estimates its own state exclusively. To be suitable for the heavily restricted implementation to very large-scale systems, a novel algorithm is proposed, which: (i) does not rely on instantaneous data transmission;(ii) allows local communication exclusively;and (iii) requires computational, memory, and data transmission resources for each system that do not scale with the dimension of the network. The scalability of the proposed algorithm allows for its application to the cooperative localization problem of very large-scale systems. In particular, it is applied herein to the on-board position estimation problem of LEO mega-constellations using GNSS featuring numerical simulations for the Starlink constellation.

关键词： Extended Kalman filter Decentralized filtering distributed robot systems Networked robots Space robotics

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Autonomous Multirobot Navigation and Cooperative Mapping in Partially Unknown Environments

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023年 72卷 1页

作者： Xie, Hongyu Zhang, Dong Hu, Xiaobo Zhou, MengChu Cao, Zhengcai Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China Macau Univ Sci & Technol Macao Inst Syst Engn Collaborat Lab Intelligent Sci & Syst Macau 999078 Peoples R China New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA

To perform collaborative exploration tasks in outdoor environments, multirobot systems require effective task planning and high-precision colocalization. However, there are many challenges in real-world environments, such as unavailable navigation maps and unpredictable obstacles. In this article, we present a system architecture for autonomous multirobot navigation and cooperative simultaneous localization and mapping (SLAM). To enable accurate and efficient multiagent navigation, this work proposes a hierarchical multirobot path planning pipeline involving two tasks, i.e., global multirobot planning and local navigation. The first task is formulated into a min-max k -Chinese postman problem and solved by a genetic algorithm (GA). The second task is transformed into the autonomous collision-free movement of each robot and solved by a reinforcement learning method. To improve the flexibility of cooperative mapping in unknown outdoor environments, this work proposes an online multirobot light detection and ranging (LiDAR) SLAM system, which can flexibly select heterogeneous robots equipped with different sensor combinations. Under the condition of no prior navigation map, this work realizes multirobot cooperative environmental exploration and reconstruction. The proposed system architecture is tested and validated via real-world experiments and some public datasets. Experimental results exhibit the superior performance of the proposed method concerning accuracy, stability, and data efficiency.

关键词： distributed robot systems light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) multirobot systems navigation path planning

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Message flow analysis with complex causal links for distributed ROS 2 systems

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robotICS AND AUTONOMOUS systems 2023年第1期161卷

作者： Bedard, Christophe Lajoie, Pierre-Yves Beltrame, Giovanni Dagenais, Michel Polytech Montreal Dept Comp Engn & Software Engn Montreal PQ H3T 1J4 Canada

distributed robotic systems rely heavily on the publish-subscribe communication paradigm and middleware frameworks that support it, such as the robot Operating System (ROS), to efficiently implement modular computation graphs. The ROS 2 executor, a high-level task scheduler which handles ROS 2 messages, is a performance bottleneck. We extend ros2_tracing, a framework with instrumentation and tools for real-time tracing of ROS 2, with the analysis and visualization of the flow of messages across distributed ROS 2 systems. Our method detects one-to-many and many-to-many causal links between input and output messages, including indirect causal links through simple user -level annotations. We validate our method on both synthetic and real robotic systems, and demonstrate its low runtime overhead. Moreover, the underlying intermediate execution representation database can be further leveraged to extract additional metrics and high-level results. This can provide valuable timing and scheduling information to further study and improve the ROS 2 executor as well as optimize any ROS 2 system. The source code is available at: ***/christophebedard/ros2-message-flow-analysis.(c) 2023 Elsevier B.V. All rights reserved.

关键词： Software tools for robot programming distributed robot systems robot Operating System (ROS) Performance analysis Tracing

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Cooperative Manipulation in Unknown Environment with distributed Control 40

Cooperative Manipulation in Unknown Environment with Distrib...

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40th Chinese Control Conference (CCC)

作者： Xu, Hao Hou, Yongjin Luo, Jia-Wei Wu, Tianyu Wu, Yue Chen, Shifeng Li, Xianglei Zhang, Hai-Tao Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518060 Peoples R China Baode Comp Syst Co Ltd Shenzhen 518060 Peoples R China

ISBN: (纸本)9789881563804

In this paper, a novel distributed control scheme for cooperative manipulation in unknown environment is developed for multi-robot system. Based on the compliant control framework, the follower robots interact with the leader robot through network communication to estimate the desired trajectory when has no ability to perceive the environment. The communication between the robot and its neighbors makes the trajectory tracking and force maintenance tasks of cooperative object manipulation perform both excellent, meanwhile, ensuring force unbiased tracking through trajectory compensation when environmental information is inaccurate. Numerical results are given to demonstrate the effectiveness and superiority of our method. With the proposed method, the robots are able to cooperatively manipulate an object in real time securely, while achieving the task of object carrying.

关键词： Cooperative manipulation distributed robot systems networked robots

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A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2019年第7期38卷 813-832页

作者： Kapoutsis, Athanasios Ch Chatzichristofis, Savvas A. Kosmatopoulos, Elias B. Democritus Univ Thrace Dept Elect & Comp Engn GR-67100 Xanthi Greece Ctr Res & Technol Informat Technol Inst Thessaloniki Greece Neapolis Univ Dept Comp Sci Paphos Cyprus

This paper presents a distributed algorithm applicable to a wide range of practical multi-robot applications. In such multi-robot applications, the user-defined objectives of the mission can be cast as a general optimization problem, without explicit guidelines of the subtasks per different robot. Owing to the unknown environment, unknown robot dynamics, sensor nonlinearities, etc., the analytic form of the optimization cost function is not available a priori. Therefore, standard gradient-descent-like algorithms are not applicable to these problems. To tackle this, we introduce a new algorithm that carefully designs each robot's subcost function, the optimization of which can accomplish the overall team objective. Upon this transformation, we propose a distributed methodology based on the cognitive-based adaptive optimization (CAO) algorithm, that is able to approximate the evolution of each robot's cost function and to adequately optimize its decision variables (robot actions). The latter can be achieved by online learning only the problem-specific characteristics that affect the accomplishment of mission objectives. The overall, low-complexity algorithm can straightforwardly incorporate any kind of operational constraint, is fault tolerant, and can appropriately tackle time-varying cost functions. A cornerstone of this approach is that it shares the same convergence characteristics as those of block coordinate descent algorithms. The proposed algorithm is evaluated in three heterogeneous simulation set-ups under multiple scenarios, against both general-purpose and problem-specific algorithms.

关键词： distributed robot systems learning and adaptive systems cognitive robotics surveillance systems autonomous agents

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