A Compiler for Scalable Construction by the TERMES Robot Collective

Deng, Yawen; Hua, Yiwen; Napp, Nils; Petersen, Kirstin

doi:10.1016/j.robot.2019.07.010

Cited by 14 publications

(3 citation statements)

References 7 publications

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“…The algorithms presented are centralized; scalable compilers 37 and decentralized control strategies 38 will be needed as the system size grows. These algorithms provided constructive demonstrations but are not shown to be optimal; more complex path planning and collision avoidance strategies could be implemented to decrease the construction time 39 , and exploring the number and location of pickup stations is an important design parameter that greatly affects the robots' throughput 25 .…”

Section: Discussionmentioning

confidence: 99%

Self-replicating hierarchical modular robotic swarms

et al. 2022

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Modular robotic systems built of reconfigurable components offer an efficient and versatile alternative to traditional monolithic robots. However, as modular systems scale up, construction efficiency is compromised due to an increase in travel time and path planning complexity. Here we introduce a discrete modular material-robot system that is capable of serial, recursive (making more robots), and hierarchical (making larger robots) assembly. This is accomplished by discretizing the construction into a feedstock of simple primitive building blocks which can be re-configured to create a wide range of functionality. The discretization significantly simplifies the swarm’s navigation, error correction, and coordination. The component composition is supported by an algorithm to compile the building blocks into swarms and plan the optimal construction path. Our approach challenges the convention that larger constructions need larger machines to build them, and could be applied in areas that today either require substantial capital investments for fixed infrastructure or are altogether unfeasible.

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Section: Discussionmentioning

confidence: 99%

Self-replicating hierarchical modular robotic swarms

et al. 2022

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“…In [40], an assembly planning algorithm for a large number of bricks that are assembled in a plane is introduced, but the approach, in contrast to our work, does not take the path-planning problem into account. In [41], a method that computes assembly plans for a large numbers of objects is presented, but the approach is not general purpose, i.e., it is only applicable to grid-like structures, and the specific robot-building material pairing of TERMES [42]. A review on collective robotic construction can be found in [43].…”

Section: B Assembly Planningmentioning

confidence: 99%

Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly

et al. 2023

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Robotic construction assembly planning aims to find feasible assembly sequences as well as the corresponding robotpaths and can be seen as a special case of task and motion planning (TAMP). As construction assembly can well be parallelized, it is desirable to plan for multiple robots acting concurrently. Solving TAMP instances with many robots and over a long time-horizon is challenging due to coordination constraints, and the difficulty of choosing the right task assignment. We present a planning system which enables parallelization of complex task and motion planning problems by iteratively solving smaller subproblems. Combining optimization methods to jointly solve for manipulation constraints with a sampling-based bi-directional space-time path planner enables us to plan cooperative multi-robot manipulation with unknown arrival-times. Thus, our solver allows for completing subproblems and tasks with differing timescales and synchronizes them effectively. We demonstrate the approach on multiple construction case-studies to show the robustness over long planning horizons and scalability to many objects and agents. Finally, we also demonstrate the execution of the computed plans on two robot arms to showcase the feasibility in the real world.

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“…The human-swarm interaction (HSI) [1,2] system is an intelligent organization composed of front-end robot swarm (such as unmanned aerial vehicles and unmanned ground vehicles) and back-end humans [3]. This intelligent organization combines the advantages of humans and machines, has the characteristics of diversified functions, high overall survival rate and complex processing capabilities.…”

Section: Introductionmentioning

confidence: 99%

A human-supported robot swarm information gathering task planning method

Xin,

Tian,

Zhijie

et al. 2023

J. of Syst. Eng. Electron.

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It is a complex system problem to dispatch the robot swarm to complete exploration missions with high quality in uncertain environments. To solve the challenge, an algorithm of the robot swarm exploration mission planning supported by humans is proposed in this paper. Firstly, the target environment is decomposed into several areas, where it takes a price to explore these areas and each robot gets a reward after exploring. Secondly, the exploration problem is modeled as a multiagent dynamic programming problem with the help of humans. Then, an extensible greedy based planning algorithm is proposed, where the searching policy of each robot is calculated based on the judgment index. Finally, the proposed algorithm is optimal through theoretical analysis, and simulation experiments show that the algorithm can provide high-quality solutions for the swarm exploration.

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A Compiler for Scalable Construction by the TERMES Robot Collective

Cited by 14 publications

References 7 publications

Self-replicating hierarchical modular robotic swarms

Self-replicating hierarchical modular robotic swarms

Long-Horizon Multi-Robot Rearrangement Planning for Construction Assembly

A human-supported robot swarm information gathering task planning method

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