Beyond-Human-Scale Robotic Manipulators

• BHSRMs are robotic systems defined by their capacity to interact with objects or environments that vastly exceed human scale, utilizing extendable booms, modular joints, and hybrid architectures.
• They integrate advanced soft–rigid components, distributed tactile sensing, and adaptive control methods to manage high payloads and ensure safe manipulation in complex settings like space and disaster response.
• Emerging research is focused on improving kinematics, enhancing teleoperation interfaces, and developing robust human-centered safety models to tackle challenges in unstructured and hazardous environments.

Beyond-Human-Scale Robotic Manipulators (BHSRMs) are robotic systems engineered to manipulate, interact with, or operate upon objects and environments that substantially exceed human scale in terms of physical reach, payload, or workspace complexity. Distinguished from conventional manipulators by their size, adaptability, modularity, or ability to navigate unstructured environments, BHSRMs leverage advances in soft robotics, modular kinematics, innovative control paradigms, and immersive teleoperation to address application domains where traditional human-scale or rigid-link robots are insufficient.

1. Architectural Principles and Enabling Mechanisms

The design of BHSRMs integrates diverse architectures, materials, and actuation strategies purpose-built for operating in environments and on structures vastly larger or more variable than those accessible to human operators or anthropomorphic robots. Key principles include:

• Extendable and Tension-Optimized Mechanisms: The ReachBot system deploys a series of extendable booms, each capable of spanning distances many times the robot's body size, enabling interaction with sparse anchor points in large or gravitationally adverse environments. Each boom utilizes a robust spiny gripper at its tip for sustained, high-force engagement on a variety of surfaces (Schneider et al., 2021).
• Hybrid Soft–Rigid Integration: The Baloo architecture demonstrates the combination of meter-scale soft pneumatic actuators with rigid elements for increased structural support. Soft elements distribute contact loads and absorb impacts, while rigid segments provide necessary force bandwidth for large payloads (Johnson et al., 12 Sep 2024).
• Modular and Transformable Joints: The Prismatic-Bending Transformable (PBT) joint comprises an integrated module capable of prismatic (extension/contraction), bending, and rotational motion, supporting assembly of custom manipulators with variable reach, dexterity, and workspace coverage. Serial connection of standardized PBT units enables manipulators to unfold or reshape for constrained environments (Zhou et al., 7 Mar 2025).
• Distributed Sensing and Compliance: Systems such as Punyo-1 augment existing rigid arms with soft, tactile-sensing skins, bubble sensors, and compliant chest arrays. This distributed sensing, combined with passive compliance, supports “whole-body” rich-contact manipulation—directly conforming to the geometry and material properties of large or irregular objects (Goncalves et al., 2021).

2. Kinematics, Dynamics, and Force Transmission

BHSRMs necessitate novel kinematic and dynamic models to handle their unconventional structures and operating regimes:

• Kinematic Configurability: The PBT joint's dual-mode operation (prismatic followed by bending or vice versa) yields significantly expanded reachable workspaces, particularly for overcoming obstacles or navigating through confined volumes. Mathematical formulation of forward and inverse kinematics incorporates the link stack’s interdependencies and directional maintenance mechanisms (Zhou et al., 7 Mar 2025).
• Force Processing and Structural Constraints: In ReachBot, each contact point is analyzed in a locally defined (fₜ, fₙ) basis, with the force-conversion matrix:

$$\begin{bmatrix} \cos\phi & \sin\phi \ -\sin\phi & \cos\phi \end{bmatrix} \begin{bmatrix} f_\mathrm{t} \ f_\mathrm{n} \end{bmatrix} = \begin{bmatrix} f_\mathrm{r} \ f_\mathrm{l} \end{bmatrix}$$

Constraints (e.g., $f_\mathrm{n} - f_0 \geq (1/\mu)|f_\mathrm{t}|$, $$f_\mathrm{buckle} \leq f_\mathrm{r} \leq f_\mathrm{max}$$) ensure grip stability and resistance to buckling during large-scale, load-bearing tasks (Schneider et al., 2021).

• Adaptive, Feedback-Rich Control: The Baloo platform employs an adaptive controller governed by $\dot{\hat\theta} = -\Gamma \Phi(x) s^T$ and torque law $\tau = \hat\theta^T \Phi(x) - K_D s$, permitting online adjustment to changing contact conditions and the nonlinearities induced by soft segments (Johnson et al., 12 Sep 2024).
• Passive Mechanical Intelligence: BHSRMs increasingly “offload” collision management and adaptation to compliant structures and materials, decreasing reliance on model-based or high-bandwidth sensing and control by exploiting inherently safe and robust mechanics (Goncalves et al., 2021).

3. Sensing, Control, and Whole-Body Manipulation Strategies

Sensing and control in BHSRMs evolve to address the manipulation of objects beyond human scale and in environments that are cluttered, dynamic, or partially modeled.

• Distributed Tactile Feedback: The combination of inflatable armbands, Soft-bubble sensors, and large-area force/geometry arrays enables real-time feedback on contact forces, shear, and coarse geometry, allowing for sequential, tactile-triggered grasp primitives (Goncalves et al., 2021).
• Simple, Robust Motion Primitives: Controllers frequently favor staged or switching primitives over high-precision trajectory tracking. In Punyo-1, motion phases are triggered by scalar pressure thresholds ($P_k > P_{G,k}$), building whole-body, adaptive grasps through localized joint velocity commands rather than full-state optimization (Goncalves et al., 2021).
• Adaptive and Feedforward Control: For heavy, hybrid BHSRMs such as Baloo, adaptive control adjusts to changing payloads and soft actuator dynamics, while parallel feedforward terms counteract systematic errors, supporting successful execution of whole-body lifts with high payload-to-weight ratios (Johnson et al., 12 Sep 2024).
• Multi-Boom Coordination and Advanced Grasp Planning: As BHSRM systems scale and diversify, there is an increasing need for algorithms that coordinate multiple kinematically redundant appendages, particularly in manipulation tasks distributed over several anchor points or when object geometry is only partially known (Schneider et al., 2021).

4. Teleoperation, Immersive Interfaces, and Human-Centered Safety Models

Teleoperation of BHSRMs introduces unique cognitive and interface-level challenges, as well as new safety paradigms:

• Scale Disparity and Inertia Mismatch: BHSRMs’ mass and inertia drastically exceed those of typical master devices; direct bilateral force reflection risks hazardous force transmission to the operator, as articulated by $v_m = (1 - 2(M_s/M_m))v$, emphasizing the requirement for tuned force scaling and impedance shaping (Hejrati et al., 13 Aug 2025).
• Immersive Control Interfaces: Full-arm haptic exoskeletons capture multidimensional operator intent, supporting high-fidelity, whole-arm teleoperation. However, aggressive motion scaling (e.g., 1:13 operator:robot mapping) and non-anthropomorphic kinematics create sensorimotor mismatches—raising cognitive load and impeding embodiment (Hejrati et al., 13 Aug 2025).
• Feedback and Embodiment Trade-offs: Visual feedback via egocentric VR or dynamically positioned remote cameras can enhance body ownership and self-location, but must be carefully matched to the proprioceptive representation to avoid disorientation or error-prone control (Hejrati et al., 13 Aug 2025).
• Safety Models: Human-centered safety models incorporate both hardware-level (physical compliance, impact protection, collision avoidance) and cognitive-level (ergonomics, agency preservation, adaptive force scaling) measures—such as force-sensor-less estimation that experimentally reduced impact severity by 80% (Hejrati et al., 13 Aug 2025). Shared autonomy strategies blend operator intent with runtime autonomous corrections for safer intervention in high-risk environments.

5. Comparative Evaluation and Application Domains

BHSRMs are evaluated for their performance in domains where conventional machines exhibit fundamental limitations:

System	Distinctive Mechanism	Application Domains
ReachBot (Schneider et al., 2021)	Extendable tensile booms + spiny grip	Space climbing, low-gravity, sparse anchor traversal
Punyo-1 (Goncalves et al., 2021)	Soft, tactile whole-body compliance	Domestic, care, safe human-robot physical interaction
Baloo (Johnson et al., 12 Sep 2024)	Hybrid soft–rigid, meter-long arms	Logistics, search & rescue, care, high payloads
PBT Joint (Zhou et al., 7 Mar 2025)	Modular prismatic-bending wrists	Confined/obstructed industrial, rescue, space
BHSRM Teleoperation (Hejrati et al., 13 Aug 2025)	Immersive teleoperation + safety	Construction, mining, disaster response

Key points of comparison:

• Reach and Workspace: Extendable booms and modular joints offer workspaces significantly larger and more adaptable than standard link-joint arms, improving reach in cluttered or hazardous conditions.
• Payload and Strength-to-Weight: Hybrid soft–rigid manipulators (e.g., Baloo) achieve human-exceeding payloads (up to 19 kg) while maintaining compliance.
• Robustness and Safety: Passive compliance and distributed sensing enhance the ability to absorb unexpected contact, reduce control complexity, and improve operational safety.
• Configurability and Deployment: Modular transformable mechanisms allow rapid reconfiguration for constrained spaces or task-specific functions.

6. Limitations and Future Research Trajectories

Despite substantial progress, key challenges persist in the scalable deployment and control of BHSRMs:

• Multi-Dimensional Sensing and Higher-Order Control: Scaling tactile sensing to larger workspaces requires higher-resolution arrays and sophisticated sensor fusion; integration with richer feedback modalities (full contact geometry, shear) remains incomplete (Goncalves et al., 2021).
• Advanced Materials and Actuator Technologies: Further gains in strength-to-weight, durability, and performance are expected from the development of novel soft actuators and hybrid material systems (Johnson et al., 12 Sep 2024).
• Complex Coordination and Autonomous Adaptation: As BHSRMs become more modular and capable of multi-limb or multi-appender operations, development of multi-boom/limb coordination algorithms and autonomous planning for complex maneuvers is required (Schneider et al., 2021).
• Teleoperation Scaling and Human Factors: Reducing sensorimotor mismatch, improving scalable control (e.g., Virtual Decomposition Control), and developing validated embodiment metrics specific to large-scale, non-anthropomorphic manipulators are future research priorities (Hejrati et al., 13 Aug 2025).
• Application-Specific Safety Verification: Comprehensive human-centered safety models and runtime verification must advance to ensure fail-safety in high-risk domains such as disaster response and construction (Hejrati et al., 13 Aug 2025).

BHSRMs represent a cross-disciplinary confluence of materials science, mechanical design, control theory, sensory intelligence, and immersive computing. Continued research across these axes is likely to yield robotic platforms with capabilities and adaptabilities fundamentally surpassing those of traditional human-scale designs, addressing manipulation and teleoperation challenges in domains previously inaccessible to automation.