CuBot-STT: Simultaneously Transport and Tighten for Lattice-type Modular Reconfiguration Robot
Authors: Chongxi Meng, Da Zhao, Yanmin Zhou, Runjie Shen, Zhipeng Wang, Bin He
Organizations: Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China · Department of Mechanical and Automation Engineering and T Stone Robotics Institute, The Chinese University of Hong Kong, Hong Kong · Department of Control Science and Engineering, Tongji University, Shanghai, China
Lattice-type modular reconfigurable robots rearrange standardized modules across tasks. Dedicated transport robots reduce module weight and cost by eliminating module level reconfiguration actuators. But existing systems use low capacity connections or internal fastening robots that occupy space for functional components. This paper presents CuBot-STT, which integrates module transport, interface locking, and release in one external robot. Cubic modules provide structural support and 24V power distribution. On each face, a gear transmission converts one external input into motion of four helical locking points, preserving internal space. The robot uses alternating foot support, a gripper for module handling, and a tightening head for interface actuation. The controller coordinates two-foot support and module locking through continuous constraint transfers. The planner decomposes relocation costs into an analytical lower bound and a residual learned through expert-guided, goal conditioned Q-learning. Contact face A∗ search expands relocation sequences into robot primitives satisfying connectivity, asymmetric manipulation, and foot stance constraints. Experiments demonstrate normal and tangential interface capacities of 300N and 490N, electrical continuity across six modules, and autonomous reconfiguration of an 11-module lattice. Planning benchmarks show superior search efficiency over analytical guidance and bidirectional heuristic search, with generalization beyond training lattice sizes without fine-tuning.
Figures & tables
Symbol
Meaning
Value
Module unit
d
Module unit side length / lattice pitch
120mm
zo
External ring gear teeth
59
zr
Internal ring gear teeth
59
nh
Number of helical pinions
4
zh
Helical pinion teeth
10
TABLE I: Main Mechanical Design Parameters
Fig. 3: CMU handling and alternating-support locomotion. (a) CMU lifting, five locomotion states, and released and clamped foot configurations; smax denotes the timing-belt clamping stroke. (b) Pickup and placement poses and tightening-head engagement states at 0∘ , 45∘ , and 90∘ .
Figure 3
Primitive
Success (%)
Median ( s )
Cost c^(o) ( s )
Unloaded step
100
15.0
15
Loaded step
100
15.0
15
90∘ turn
100
22.0
20
180∘ turn
100
28.0
30
Face unlocking
96
24.0
25
Module unit pickup
100
9.0
10
TABLE II: Primitive Success Rates, Durations, and Calibrated Search Costs ( 100 Trials per Type)
The continuously deformable geometry of modular robots makes it difficult to define a fixed representation for reconfiguration planning and analysis. This letter introduces a square-cell abstraction that maps deformable rhombus modules to fixed-size grid cells while retaining physically interpretable local motions through two primitives, pivoting and shearing. Under this abstraction, we prove that every non-straight edge-connected configuration with N≥7 can be transformed to a fixed canonical staircase using only admissible primitive motions. Since these motions are reversible, any two configurations in this class are mutually reconfigurable. The proof is constructive and directly yields a staircase-canonicalization planner that transports removable boundary modules while preserving connectivity. As a practical enhancement, we further introduce a boundary-to-delivery lookahead selector that ranks admissible high level choices without affecting the completeness guarantee. Experiments demonstrate the constructive reconfiguration process and show that the selector substantially reduces planning time, while reference comparisons indicate lower planning times than the prior framework over the shared module counts.
Jie Gu, Tingting Wang, Hongrun Gao +4
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China · Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China
Robotic construction systems often treat the material system and the robot as separate design problems, locating intelligence primarily in hardware, sensing, motion planning, and control. This project instead investigates how geometric intelligence can be encoded within architected material systems to simultaneously address requirements for robotic grasping, self-alignment, reversible connection, structural performance, and three-dimensional aggregation. We introduce a self-aligning compound nested lattice module composed of conjoined cuboctahedral-octahedral units. The cuboctahedral features of the modules provide defined surfaces for robotic grasping and alignment, while the octahedral features incorporate screw-releasable snap-fit connectors and corresponding receptors. Additionally, we present a nested arrangement that enables interlocking aggregation along the x, y, and z axes. We demonstrate the system through furniture and architectural scale structures assembled using both a robotic arm and mobile assembler. The resulting configurations include seating, spanning structures, surfaces, and vertical frames. Compression testing of the compound module produced a stiffness of 4,556 N/mm, a maximum load of 3,445 N, and a compressive modulus of 17.5 MPa. The modules can also be disassembled and reused across different configurations, supporting reconfigurable and circular construction.
Alexander Htet Kyaw, Miana Smith, Paul Richard +1
Massachusetts Instittue of Technology (MIT) · École Polytechnique Fédérale de Lausanne (EPFL)
Research in modular robotics has produced capable approaches allowing a robot's morphology to change online, with recent efforts also developing approaches to decide which morphology to assume and automatically propagate that decision into the robot's motion planning and control. These approaches are powerful and increase adaptability in the field. However, an alternative objective is not to build robots whose structures can change, but robots whose fundamental capabilities can change, where capability is a joint function across several domains, including kino-dynamics, perception, compute, and high-level coordinating behaviors. A robot designed to be reconfigured across these domains has a greater capacity to alter its capability than one that can be reconfigured in a single domain. We refer to this cross-domain reconfigurability as integration span, and recognize a complementary measure of the resistance to reconfiguration, which we refer to as integration inertia. Current modular robots have reduced integration inertia in the structural domain while it remains high in the other domains that contribute to integration span. We assert that the systems that can provide the most utility through reconfiguration in practice are those maximizing span and minimizing inertia and call this general problem recompositional robotics: adaptation over a heterogeneous set of modules including hardware, software, compute, and behavior that abstracts each component by the interfaces it requires and provides such that they can be reasoned over holistically. We define the problem, ground it in two deployed systems and active research efforts, and pose open questions about the future of recompositional robotics.
Steven Swanbeck, Jonathan Salfity, Corrie Van Sice +2
Texas Robotics and the Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA