This work proposes a framework that generates and optimally selects task-specific assembly configurations for a large group of homogeneous modular aerial systems, explicitly enforcing bounds on inter-module downwash. Prior work largely focuses on planar layouts and often ignores aerodynamic interference. In contrast, firstly we enumerate non-isomorphic connection topologies at scale; secondly, we solve a nonlinear program to check feasibility and select the configuration that minimizes control input subject to actuation limits and downwash constraints. We evaluate the framework in physics-based simulation and demonstrate it in real-world experiments.
Figures & tables
Fig. 1: The optimal assembly of 12 modules, given the target wrench set defined in Section IV . Each black square represents one module, each blue rectangle represents a rigid connection, each red arrow represents the module frame z -axis, and the purple capsules indicate the collision-free downwash volume for each module.
Fig. 2: An illustration of two modules with four connection ports on each frame. Each connector can rotate along the green axis, where the orange screw can fix the connector. The white circles on the connector are permanent magnets.
Fig. 3: An example of a four-module assembly and its matrix representation, where a black square represents a single module, the four rectangles within each square are the connectors. Blue indicates a valid connection, yellow indicates a blocked connection, and gray indicates an available connector.
Fig. 4: All non-isomorphic configurations under the symmetric point group C4 using 5 modules.
n
Number of available configurations
Number of non-isomorphic configurations
CPU Time (s)
1
1
1
0.0000
2
4
1
0.0006
3
6
2
0.0007
4
16
7
0.0017
5
68
24
0.0072
6
272
97
0.0261
TABLE I: Exhaustive enumeration of non-isomorphic configurations for connector angles all fixed to π/2 .
Fig. 5: Comparison of exhaustive and sampling-based enumeration. The sample count is fixed at Nn=500 for all n . For n>11 , CPU time is shown only for every fifth value of n .
Fig. 6: All optimal configurations with control costs Jcost using 4 modules for the wrench set specified in Section IV-C .
m
cf
cm
larm
lc
r
0.24kg
3.87×10−7
1.06×10−8
0.06m
0.11m
0.095m
TABLE II: Single module parameters used in this work.
Fig. 7: Achievable force polytope for the best configuration in Fig. 6 (c); the blue, red, and purple vectors are projections onto the force subspace at zero torque and all lie within the polytope.
Fig. 8: Computation time, averaged per CPU core, with 10 randomly selected wrenches for n∈{10,20,…,90} .
Fig. 9: Two optimal configurations from Fig. 8 with n=30 and n=60 , tracking a circular trajectory with fixed identity orientation.
Fig. 10: The 2 -module configuration hovering in the air.
Fig. 11: Experiment results of the system in free flight when tracking a 3D figure- 8 trajectory while maintaining the target roll angle at 0∘ (left) and −5∘ (right). The black dashed lines are the target trajectories.
Aerial robotics studies the design, perception, control, and coordination of flying robots for navigation, inspection, transport, and physical interaction.
Aerial manipulation with multirotor platforms enables physical interaction in complex environments, but rotor-induced airflow remains a critical limitation for tasks involving airflow-sensitive targets or surroundings. This paper presents an optimization-based design framework for modular aerial manipulators that jointly considers task wrench feasibility, end-effector placement, and airflow exposure constraints. We first introduce a novel categorization of target-side airflow tolerance and formulate the corresponding exposure requirements as geometric constraints. To efficiently model rotor-induced airflow, we introduce a compact cone-sphere envelope that approximates the spreading structure of a quadrotor's airflow while preserving computational tractability for optimization. Building on this formulation, we propose a reconfiguration optimization that adapts a modular aerial manipulator to diverse task wrench requirements while enforcing both target-side airflow exposure and intra-platform airflow interference constraints. Unlike prior designs that assume a fixed end-effector location, the proposed framework optimizes the end-effector placement together with the platform configuration. Scalability experiments and ablation studies validate the effectiveness of the proposed framework.
Mengguang Li, Heinz Koeppl
Department of Electrical Engineering and Information Technology, Technische Universität Darmstadt, 64287 Darmstadt, Germany
Continuum arm aerial manipulation systems leverage soft-manipulator compliance and dexterity for tasks in confined or hazardous environments, but propeller downwash can degrade performance, particularly near walls and the ground. This effect remains uncharacterized for continuum manipulators. This letter experimentally studies downwash-induced kinematic deviations of a tendon-driven continuum manipulator integrated with a multirotor platform. Under still-air conditions, the CM is compared with a constant-curvature (CC) model. Downwash- induced end-effector pose deviations are then quantified relative to the mean still-air experimental baseline at four propeller throttle levels in free space, and at maximum throttle near a wall, and near the ground. Vertical position and yaw show the largest deviations and are amplified by ground effect. A CC-guided Gaussian process regression (GPR) residual model is learned from experimental data that improves forward pose prediction RMSE (position by 89-95%, orientation by 47-79%), and support compensation-oriented, downwash-aware modeling of continuum arm aerial manipulation systems.
Modular Aerial Robot Systems (MARS) consist of multiple drone modules that are physically bound together to form a single structure for flight. Exploiting structural redundancy, MARS can be reconfigured into different formations to mitigate unit or rotor failures and maintain stable flight. Prior work on MARS self-reconfiguration has solely focused on maximizing controllability margins to tolerate a single rotor or unit fault for rectangular-shaped MARS. We propose TransforMARS, a general fault-tolerant reconfiguration framework that transforms arbitrarily shaped MARS under multiple rotor and unit faults while ensuring continuous in-air stability. Specifically, we develop algorithms to first identify and construct minimum controllable assemblies containing faulty units. We then plan feasible disassembly-assembly sequences to transport MARS units or subassemblies to form target configuration. Our approach enables more flexible and practical feasible reconfiguration. We validate TransforMARS in challenging arbitrarily shaped MARS configurations, demonstrating substantial improvements over prior works in both the capacity of handling diverse configurations and the number of faults tolerated. The videos and source code of this work are available at https://github.com/RuiHuangNUS/TransforMARS
Rui Huang, Zhiyu Gao, Siyu Tang +4
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583 · Department of Mechanical Engineering, National University of Singapore, Singapore 117583