cs.ROSep 25, 2026

Modeling and Generative-AI-Based Design of Load-Adaptive Gravity Balancing Mechanisms

Authors: Ryotaro Kayawake, Kazuki Abe, Shota Miyake, Masahiro Watanabe, Kenjiro Tadakuma

Organizations: Embodied Intelligence and Robotics Laboratory Graduate School of Information Sciences Tohoku University 6-6-01, Aramaki, Aoba-ku, Sendai, Miyagi 9808579, Japan · Robot Mechanisms Laboratory Graduate School of Engineering Science The University of Osaka 1-3, Machikaneyama, Toyonaka, Osaka 5608531, Japan

Abstract

Load-adaptive gravity balancing mechanisms (LA-GBMs) can accommodate various loading conditions by passively changing their characteristics in response to payload variations. However, their design is difficult because both the desired mechanism motion and static equilibrium under variable payloads must be satisfied simultaneously. This study proposes a general design methodology for LA-GBMs that does not depend on specific mechanism architectures or mechanical elements. The necessary conditions for the potential fields of LA-GBMs are formulated, and two general forms are derived: an affine form representing the effect of payload mass and a factorized form representing state transitions associated with load adaptation and gravity balancing. These forms are then provided to generative AI as design requirements to generate candidate potential functions. The generated functions are analytically verified in terms of their conformity to the two general forms and the conditions required for valid LA-GBMs. Furthermore, the obtained potential functions are decomposed into individual terms, and an example of a method for constructing an LA-GBM by combining springs, counterweights, and function-generating linkage mechanisms is presented. By using potential functions as an intermediate representation, the proposed framework enables the generation of LA-GBM design candidates without prescribing a mechanism architecture in advance. Mechanical realizability and manufacturability of the generated potential fields remain important issues for future work.

Figures & tables

Explore similar work

Sep 14, 2026

Task-Distribution-Aware Counterweight Synthesis and Constrained Co-Design for Serial Manipulators

Passive counterweights are simple gravity compensators, but a counterweight selected from a single pose is not generally optimal for the configurations and tasks a manipulator actually executes. This paper develops a task-distribution-aware synthesis framework in which the operating distribution ρ(q)ρ(q) enters the design explicitly. For a counterweight moment p=mcrcp=m_c r_c with gravity torque −gpφ(q)-gpφ(q), the weighted mean-square residual gravity torque has the closed-form minimizer p∗=Eρ[τgφ]/(gEρ[φ2])p^*=E_ρ[τ_gφ]/(gE_ρ[φ^2]). If payload gravity torque is affine in payload mass, the optimum is also affine: p∗(mp,ρ)=p0∗(ρ)+mpKp(ρ)p^*(m_p,ρ)=p_0^*(ρ)+m_pK_p(ρ). For fixed static moment, added counterweight inertia is Ic=prcI_c=pr_c while mass is mc=p/rcm_c=p/r_c, so mass-radius selection is underdetermined unless physical constraints are specified. A recovered three-link manipulator is used as a case study. At rc=0.20r_c=0.20 m, zero-payload equivalent optima are 0.672 kg for uniform joint-space operation, 0.683 kg for approximately uniform task-space operation, 0.713 kg for a representative pick-and-place family, and 0.952 kg for a high-gravity-biased distribution, a change of more than 40% caused solely by the operating distribution. Nondominated fronts show that preferred mass-radius pairs depend on declared engineering bounds. A rated-torque-referenced all-joint screen increases zero-payload feasible task-space coverage from 78.1% without compensation to 93.7% for the uniform-distribution design. A lumped point-mass trajectory study gives a provisional crossover from no counterweight at very aggressive motion to stronger compensation as motion slows. These actuator and dynamic results are engineering consequence studies rather than physical validation.
Aug 17, 2026

Design Optimization for Large High-Force Soft Robot Manipulators Under Gravitational Loads

Designing large soft robots capable of generating high forces for physical human-robot interaction remains a significant challenge in soft robotics. Prior work in large soft robots has focused on proof-of-concept prototypes, and no systematic framework exists for determining the suitability of a design paradigm for a desired task. This manuscript introduces a method for optimizing the geometry of a soft robot limb, maximizing its blocking force subject to an anti-bucking constraint under its own gravitational loading. We demonstrate that an explicit solution exists to the proposed optimization problem under certain assumptions. Experiments with three geometries of a large, soft, pneumatically-actuated manipulator demonstrate that the method correctly predicts which designs meet constraints and which produces the largest end-effector forces. This method, with its closed-form solution, can allow designers to determine a-priori if an intended class of soft manipulators is an appropriate choice for physical interaction at large size scales.
Mar 19, 2026

TiBCLaG: Hybrid design approach for a trigger-induced bistable compliant laparoscopic grasper

Industrial laparoscopic graspers rely on multi-link rigid mechanisms manufactured to tight tolerances, resulting in high manufacturing and assembly costs. This work presents the design and proof-of-concept validation of a monolithic, fully compliant, bistable, laparoscopic grasper that eliminates the need for multiple rigid links, thereby reducing part count. The device integrates a compliant trigger and a compliant gripper end-effector, coupled via a control push-rod, to achieve stable grasping without continuous user input. A hybrid approach combining an analytical model, iterative prototyping, and finite element analyses is employed to design the laparoscopic grasper. The trigger mechanism is synthesized using a Two-Element Beam Constraint Model as a design framework to control the deformation and stiffness of I-beam-like elements. This technique enables elastic energy storage while preventing snap-through instability. The end-effector is designed as a compliant gripper to achieve adaptive grasping through elastic deformation. The laparoscopic design presented here is fabricated using fused deposition 3D printing. A comparative study of the jaws' opening and closing performance is presented using nonlinear finite element analysis and experimentation. The fabricated prototype demonstrates reliable bistable actuation, confirming the feasibility of such compliant laparoscopic grasper architectures.