soft robotic design

This paper addresses the lack of systematic definition and analysis of adaptability in soft robotics. It first rigorously categorizes adaptability into *external adaptability*—encompassing responses to environmental conditions, object properties, geometric variations, and task dynamics—and *internal adaptability*, covering tolerance to manufacturing imperfections, material aging, and cross-platform control generalization. Through a comprehensive review of representative applications—including surgical, wearable, locomotive, and manipulative systems—the work systematically analyzes the synergistic interplay among structural design, soft sensing, and adaptive control. A unified analytical framework is proposed to address application-driven challenges, integrating materials science and robotics methodologies. The study identifies fundamental limitations in modeling fidelity, real-time soft sensing, and general-purpose adaptive control. These findings provide both theoretical foundations and practical pathways for enhancing the robustness and deployability of soft robots across diverse operational scenarios.

Existing robotic tails face a fundamental trade-off between rigidity (enabling high output force but compromising safety) and softness (ensuring safety yet suffering from insufficient force and speed). This work proposes a bioinspired vertebral soft robotic tail that integrates pneumatic soft actuators with a passive, jointed spinal architecture, effectively decoupling load-bearing and actuation functions to overcome the inherent speed and force limitations of conventional soft actuators. A kinematic-dynamic model incorporating vertebral geometric constraints is formulated and experimentally validated. The prototype achieves a peak angular velocity of 670°/s, maximum inertial force of 5.58 N, and torque of 1.21 N·m—representing over a 200% improvement over spine-free soft tail designs. The tail has been successfully deployed on high-speed steering vehicles, obstacle-crossing platforms, and quadrupedal robots, significantly enhancing stability and maneuverability of agile mobile systems.

This work addresses two key challenges in dynamic physical interaction tasks: insufficient exploitation of passive compliance in soft actuators under high-impact, contact-rich conditions, and the difficulty of designing effective rigid–soft coupled structures. We present Baloo, a large-scale hybrid rigid–soft robotic torso. Its core innovation lies in the first full-scale integration of a 2-meter pneumatic soft arm with a rigid torso, achieving a 19 kg end-effector payload—comparable to similarly sized rigid robots—while maintaining a high strength-to-weight ratio. We further propose a physics-informed simplified closed-loop control strategy enabling whole-torso coordinated motion planning and haptic grasping. Across 30 trials, Baloo achieves 100% grasping success on six heterogeneous objects. This work establishes a scalable design paradigm and control framework for rigid–soft collaborative robots operating in dynamic, unstructured physical interaction environments.

This work proposes SoFiE, a modular soft finger exoskeleton designed to overcome the limitations of conventional rigid hand exoskeletons, which are often bulky and incompatible with natural finger kinematics. The system employs a 3D-printed compliant structure actuated by tendon-driven DC motors to provide lightweight, low-profile flexion assistance, while passive elastic elements enable extension. Innovatively integrating StretchSense resistive proprioceptive springs and MagSense magnetic tactile sensors—fused with motor encoder feedback—SoFiE achieves accurate finger pose estimation, object stiffness recognition, and grasp-type classification. Its fully wireless, co-located actuation-sensing architecture demonstrates high-fidelity finger state perception and adaptability across multiple tasks in experimental validation, offering an effective solution for soft wearable hand-assistive robotics.

This study addresses the gait interference commonly caused by the added mass and rigid structures of conventional exoskeletons. To overcome this limitation, the authors propose a lightweight, low-complexity soft bilateral ankle exoskeleton that delivers plantarflexion assistance through an integrated shoe-upper design, ensuring compatibility with arbitrary footwear. The system combines a compliant mechanical structure with a universal shoe-mounted mechanism and a customized control algorithm, and its biomechanical impact is evaluated under zero-torque mode. Experimental results demonstrate that the device imposes no significant alterations on lower-limb kinematics or kinetics in healthy subjects, thereby confirming its non-intrusive nature and wearability. This work establishes a novel paradigm for gait assistance characterized by high compatibility and minimal interference with natural locomotion.

Conventional rigid wearable assistive devices for aging populations and individuals with neuromusculoskeletal disorders suffer from low force transmission efficiency and poor anatomical conformity. Method: This study proposes an integrated compliant pneumatic soft sleeve actuator fabricated from thermoplastic elastomer via an enhanced fused deposition modeling process, enabling hermetic, elastic actuators capable of linear, bending, torsional, and omnidirectional compound motions—without requiring complex anchoring mechanisms and operating stably at low pneumatic pressure. Contribution/Results: Experimental evaluation demonstrates substantial improvements in force transmission efficiency and wearer comfort, alongside advantages in lightweight design, high integration density, and multi-degree-of-freedom actuation capability. The architecture establishes an engineering-feasible paradigm for next-generation soft wearable assistive systems.

This work addresses the limitations of purely rigid robots in environmental adaptability and fully soft robots in load-bearing capacity and scalability by proposing an automated co-design framework for hybrid soft-rigid robots. For the first time in this domain, differentiable simulation coupled with gradient-based optimization is employed to jointly optimize free-form soft structures, rigid truss layouts, and multi-channel actuation configurations. The developed differentiable simulator integrates the Material Point Method (MPM) with Extended Position-Based Dynamics (XPBD), enabling end-to-end gradient optimization of coupled soft-rigid systems and automatically generating truss skeletons that efficiently transmit actuation forces and elicit effective gaits. Physical prototypes successfully reproduce the optimized locomotion patterns, and modal analysis confirms alignment between structural deformation modes and actuation frequencies, significantly enhancing locomotion performance.

This study addresses multifaceted challenges confronting soft wearable robots—namely, societal acceptance, bio-sensing ethics, and public expectations in real-world settings. We introduce the “speculative soft robotic garment” paradigm and present Sumbrella: a transformable garment integrating origami-inspired bistable structures, fabric-based pneumatic chambers, and cable-driven actuation, augmented with embedded computer vision and wearable electronics. For the first time, speculative design is rigorously embedded throughout the soft robotics development lifecycle. A qualitative focus group study with 12 creative technology experts elucidates human–robot tensions across three dimensions: bodily expression, social interaction, and surveillance/data misuse. Key contributions include: (1) a kinesic communication framework for human–robot interaction (HRI); (2) the first ethics-by-design guidelines for soft wearable robots in public contexts; and (3) a practice-oriented set of design principles grounded in empirical insight.

This work addresses the vulnerability of humanoid robots to damage from falls in human environments and the safety risks posed by their rigid structures. The authors propose a novel co-design framework that integrates non-Newtonian fluid-based responsive soft materials, physics-simulation-driven protective structure optimization, and a learning-based active fall control strategy. The soft material remains compliant under normal conditions but instantaneously stiffens upon impact to dissipate energy effectively. Through joint optimization of these components, the system achieves high robustness and environmental safety. Validated on a full-scale, 42-kg humanoid robot, the approach significantly reduces peak impact forces and enables repeated high-energy falls—including 3-meter drops and stair tumbles—without hardware damage.

This study addresses the limited efficacy of current soft robotic exogloves in fine motor rehabilitation, which stems from their standardized sizing and poor anatomical fit to individual hand structures. To overcome this, the authors propose a personalized pneumatic soft exoglove design methodology based on three-dimensional hand topology scanning. By integrating silicone molding fabrication, finite element analysis, and pneumatic control experiments, they develop a subject-specific biomechanical finger model and optimize the strain-limiting layer to enhance alignment accuracy between actuators and metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints. This approach achieves personalization in structural conformity, joint topological matching, and human–robot contact force modeling, thereby significantly improving precise actuation and rehabilitative support for dexterous hand movements.

This study addresses the challenge of simultaneously achieving precise end-effector positioning and adjustable compliance for soft robots operating in unstructured environments. The authors propose a seven-link hyper-redundant compliant manipulator that integrates a rigid-joint backbone with antagonistically actuated pneumatic muscles, enabling independent control of joint angles and stiffness. By introducing a task-space compliance model and a unified iterative inverse kinematics/inverse compliance control algorithm, the work demonstrates, for the first time on a physical system, quantitative, synchronous, and real-time control of both end-effector position and compliance. Experimental results show that the approach exhibits exceptional robustness and practicality in complex contact-rich tasks—such as whiteboard writing under perturbations and inserting a key or opening a drawer with unknown misalignments—surpassing the capabilities of conventional rigid or purely soft robotic arms.