Tensegrity Continuum Robots Enable Task-Adaptive Morphologies for Cooperative Behaviors
- URL: http://arxiv.org/abs/2608.27221v1
- Date: Thu, 27 Aug 2026 15:05:30 GMT
- Title: Tensegrity Continuum Robots Enable Task-Adaptive Morphologies for Cooperative Behaviors
- Abstract summary: We introduce an MRR that unifies the advantages of both architectures by combining a tensegrity-based compliant body with claw-based connection mechanisms.<n>We demonstrate the robots' capability across diverse tasks and environments, including coordinated object manipulation and transport, multimodal locomotion, and loco-manipulation.<n>These results lay a foundation for adaptable and multifunctional robotic collectives, with broad potential applications in manufacturing, space exploration, and search-and-rescue operations.
- Score: 3.443736248915025
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Robots that can change their morphologies and behaviors for different tasks and environments hold great promise for adaptable, multifunctional systems. Modular reconfigurable robots (MRRs) can achieve such functionalities by docking and rearranging individual units, but most rely on rigid modules that lack structural compliance, resulting in limited capabilities. Continuum robots offer compliance through flexible backbones, yet they cannot self-reconfigure into task-adaptive multi-robot configurations. Here, we introduce an MRR that unifies the advantages of both architectures by combining a tensegrity-based compliant body with claw-based connection mechanisms. Each robot can manipulate and locomote independently, and multiple robots can self-reconfigure into different morphologies (e.g., chains, loops, branches) for cooperative manipulation and locomotion. We demonstrate the robots' capability across diverse tasks and environments, including coordinated object manipulation and transport, multimodal locomotion, and loco-manipulation in real-world scenarios. These results lay a foundation for adaptable and multifunctional robotic collectives, with broad potential applications in manufacturing, space exploration, and search-and-rescue operations.
Related papers
- Reinforcement learning in linear embedding space unlocks generalizable control across soft robot configurations [60.42735420750131]
Soft-bodied organisms such as octopuses and elephant trunks exhibit remarkable morphological adaptability.<n>Various soft robots have emerged in recent decades, featuring diverse materials, stiffnesses, and morphologies tailored to specific tasks.<n>Here, we introduce a generalizable control system that enables rapid adaptation across diverse soft robot configurations.
arXiv Detail & Related papers (2026-06-06T11:09:46Z) - Physical Human-Robot Interaction for Grasping in Augmented Reality via Rigid-Soft Robot Synergy [43.680646123465316]
Hybrid rigid-soft robots combine the precision of rigid manipulators with the compliance and adaptability of soft arms.<n>We present a novel augmented reality (AR)-based physical human-robot interaction framework that enables direct teleoperation of a hybrid rigid-soft robot.
arXiv Detail & Related papers (2026-02-19T06:56:47Z) - LEO-RobotAgent: A General-purpose Robotic Agent for Language-driven Embodied Operator [1.5566524830295307]
We propose LEO-RobotAgent, a general-purpose language-driven intelligent agent framework for robots.<n>This framework features strong generalization, robustness, and efficiency.<n>Experiments have verified that this framework can be easily adapted to mainstream robot platforms.
arXiv Detail & Related papers (2025-12-11T12:58:36Z) - Capability-Aware Shared Hypernetworks for Flexible Heterogeneous Multi-Robot Coordination [1.5970870882365]
We propose Capability-Aware Shared Hypernetworks (CASH) for multi-robot teams.<n>CASH is a soft weight sharing architecture that uses hypernetworks to efficiently learn a flexible shared policy.<n>We show that CASH consistently outperforms baseline architectures in terms of performance and sample efficiency during both training and zero-shot generalization.
arXiv Detail & Related papers (2025-01-10T15:39:39Z) - Holistic Construction Automation with Modular Robots: From High-Level Task Specification to Execution [7.012962572096341]
In situ robotic automation in construction is challenging due to constantly changing environments, a shortage of robotic experts, and a lack of standardized frameworks bridging robotics and construction practices.<n>This work proposes a holistic framework for construction task specification, optimization of robot morphology, and mission execution using a mobile modular reconfigurable robot.
arXiv Detail & Related papers (2024-12-30T11:11:13Z) - EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents [33.77674812074215]
We introduce a novel multi-agent framework designed to enable effective collaboration among heterogeneous robots.<n>We propose a self-prompted approach, where agents comprehend robot URDF files and call robot kinematics tools to generate descriptions of their physics capabilities.<n>The Habitat-MAS benchmark is designed to assess how a multi-agent framework handles tasks that require embodiment-aware reasoning.
arXiv Detail & Related papers (2024-10-30T03:20:01Z) - Controlling diverse robots by inferring Jacobian fields with deep networks [48.279199537720714]
Mirroring the complex structures and diverse functions of natural organisms is a long-standing challenge in robotics.<n>We introduce a method that uses deep neural networks to map a video stream of a robot to its visuomotor Jacobian field.<n>Our approach achieves accurate closed-loop control and recovers the causal dynamic structure of each robot.
arXiv Detail & Related papers (2024-07-11T17:55:49Z) - Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models [81.55156507635286]
Legged robots are physically capable of navigating a diverse variety of environments and overcoming a wide range of obstructions.
Current learning methods often struggle with generalization to the long tail of unexpected situations without heavy human supervision.
We propose a system, VLM-Predictive Control (VLM-PC), combining two key components that we find to be crucial for eliciting on-the-fly, adaptive behavior selection.
arXiv Detail & Related papers (2024-07-02T21:00:30Z) - RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis [102.1876259853457]
We propose a tree-structured multimodal code generation framework for generalized robotic behavior synthesis, termed RoboCodeX.
RoboCodeX decomposes high-level human instructions into multiple object-centric manipulation units consisting of physical preferences such as affordance and safety constraints.
To further enhance the capability to map conceptual and perceptual understanding into control commands, a specialized multimodal reasoning dataset is collected for pre-training and an iterative self-updating methodology is introduced for supervised fine-tuning.
arXiv Detail & Related papers (2024-02-25T15:31:43Z) - RoboScript: Code Generation for Free-Form Manipulation Tasks across Real
and Simulation [77.41969287400977]
This paper presents textbfRobotScript, a platform for a deployable robot manipulation pipeline powered by code generation.
We also present a benchmark for a code generation benchmark for robot manipulation tasks in free-form natural language.
We demonstrate the adaptability of our code generation framework across multiple robot embodiments, including the Franka and UR5 robot arms.
arXiv Detail & Related papers (2024-02-22T15:12:00Z) - A Capability and Skill Model for Heterogeneous Autonomous Robots [69.50862982117127]
capability modeling is considered a promising approach to semantically model functions provided by different machines.
This contribution investigates how to apply and extend capability models from manufacturing to the field of autonomous robots.
arXiv Detail & Related papers (2022-09-22T10:13:55Z) - Malleable Agents for Re-Configurable Robotic Manipulators [0.0]
We propose an RL agent with sequence neural networks embedded in the deep neural network to adapt to robotic arms with varying number of links.
With the additional tool of domain randomization, this agent adapts to different configurations with varying number/length of links and dynamics noise.
arXiv Detail & Related papers (2022-02-04T21:22:00Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.