Collision Detection for Modular Robots: It Is Easy to Cause Collisions and Hard to Avoid Them

Publication date

2024-12-27

Authors

Gupta, Siddharth
van Kreveld, M.J.ORCID 0000-0001-8208-3468ISNI 0000000116732175
Michail, Othon
Padalkin, Andreas

Editors

Bramas, Quentin
Casteigts, Arnaud
Meeks, Kitty

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

Abstract

We consider geometric collision-detection problems for modular reconfigurable robots. Assuming the nodes (modules) are connected squares on a grid, we investigate the complexity of deciding whether collisions may occur, or can be avoided, if a set of expansion and contraction operations is executed. We study both discrete- and continuous-time models, and allow operations to be coupled into a single parallel group. Our algorithms to decide if a collision may occur run in O(n2log2n) time, O(n2) time, or O(nlog2n) time, depending on the presence and type of coupled operations, in a continuous-time model for a modular robot with n nodes. To decide if collisions can be avoided, we show that a very restricted version is already NP-complete in the discrete-time model, while the same problem is polynomial in the continuous-time model. A less restricted version is NP-hard in the continuous-time model.

Keywords

Collision detection, Complexity, Computational geometry, Modular robots, Taverne, Theoretical Computer Science, General Computer Science

Citation

Gupta, S, van Kreveld, M, Michail, O & Padalkin, A 2024, Collision Detection for Modular Robots : It Is Easy to Cause Collisions and Hard to Avoid Them. in Q Bramas, A Casteigts & K Meeks (eds), Algorithmics of Wireless Networks - 20th International Symposium, ALGOWIN 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 15026 LNCS, Springer Nature, pp. 76-90, 20th International Symposium on Algorithmics of Wireless Networks, ALGOWIN 2024, Egham, United Kingdom, 5/09/24. https://doi.org/10.1007/978-3-031-74580-5_6, conference