Tripody: An Overconstrained 3-SPR-like Parallel Robot for High-Reach Construction Tasks

• URL: http://arxiv.org/abs/2607.25781v1
• Date: Tue, 28 Jul 2026 14:36:16 GMT
• Title: Tripody: An Overconstrained 3-SPR-like Parallel Robot for High-Reach Construction Tasks
• Abstract summary: Tripody is a wheeled 3-DoF parallel robot for high-reach tasks.<n>It replaces the base spherical joints of a classical 3-SPR.<n>System extends from 1.7m to 3.4m in height, supports a continuous 32kg payload.
• Score: 5.351986678360277
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Many ceiling construction tasks still rely on heavy serial manipulators that are difficult to deploy in cluttered interiors, motivating lightweight, field-ready alternatives that reach ceiling height while maintaining millimeter-level accuracy and the stiffness demanded by overhead tool loads. We introduce Tripody, a wheeled 3-DoF parallel robot for high-reach tasks that replaces the base spherical joints of a classical 3-SPR (3 legs; S: base spherical joint; P: actuated prismatic joint; R: end-effector revolute joint) morphology with universal joints, intentionally overconstraining the mechanism; small, distributed elastic deflections absorb the resulting incompatibilities, preserving predominantly translational motion. The 33kg system extends from 1.7m to 3.4m in height, supports a continuous 32kg payload, and offers a modular end-effector interface for ceiling operations. We detail the mechanical design - including custom linear actuators and a kinematic-compatibility analysis - and a control stack for accurate positioning that combines SE(3) state estimation, forward kinematics, and task-space control. In experiments, Tripody exhibits similar in-plane stiffness to a spherical-base variant but substantially higher torsional stiffness - an increase of 67% at 1.7m, 196% at 2.6m, and 454% at 3.4m - while maintaining negligible cross-axis coupling. Closed-loop positioning with a total station converges below 0.6mm across the entire workspace; pure model extrapolation achieves a 95th-percentile error of 2.7mm (max 3.6mm). Finally, we demonstrate task-level ceiling-drilling feasibility in an open-loop study by drilling a 15-hole pattern with 4.5mm maximum relative hole-position error after rigid alignment. These results support overconstrained, compliance-absorbing 3-SPR-like architectures as a practical path to lightweight, high- reach, millimeter-accurate construction robots.

Related papers

• Vision-Guided Morphing Quadcopter for Multi-Geometry Payload Transport through Narrow Passages [0.0]
  This paper presents a vision-guided morphing quadcopter for multi-geometry payload transport through narrow passages.<n>The proposed platform uses four hybrid arm-leg structures that function as both landing supports and grasping members.
  arXiv  Detail & Related papers  (2026-08-22T09:45:13Z)
• H-PAC Hand: Control-Oriented Modeling and Tendon-Elasticity Compensation for an Underactuated Robotic Hand [14.429793775517608]
  H-PAC is a 6-actuator, 15-DoF robotic hand with a control-oriented modeling and implementation framework.<n>A mechanics-based compensation model is developed to account for tendon-actuatedity-elastic joint errors.<n>Experiments show that the compensation substantially improves joint-angle prediction.
  arXiv  Detail & Related papers  (2026-08-17T15:26:51Z)
• A Model-Based Decoupling Strategy for Proprioception and Contact Sensing in an Architected Soft Manipulator [49.225033144914214]
  We present a model-based strategy that decouples proprioceptive and contact signals from fluidic pressure sensors embedded in a soft architected segment.<n>On a single ITH segment, this approach achieves proprioceptive shape estimation with a relative bending error of 0.11 +/- 0.02 and a contact detection rate of 97% across 178 trials.
  arXiv  Detail & Related papers  (2026-07-17T03:03:19Z)
• Disturbance-aware Motion Planning for Over-actuated Underwater Vehicles Exploiting Actuation Redundancy for High-fidelity 3D Reconstruction [9.030271148215196]
  High-power thrusters resuspend sediments and induce turbulence, degrading image quality at the sensor input.<n>We address this actuation-to-perception coupling by exploiting redundancy in over-actuated platforms.<n>Across 440 trials, the approach reduces target-region particle velocity by 67%.<n>It improves 3D reconstruction RMSE by 55% versus a disturbance-unaware baseline.
  arXiv  Detail & Related papers  (2026-07-08T08:32:15Z)
• Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent [98.33217711280383]
  We introduce Agents-A1, a 35B Mixture-of-Experts Agentic Model that reaches trillion- parameter-level performance by scaling the agent horizon.<n>We build a long-horizon knowledge-action infrastructure that connects external knowledge, actions, observations, and verifier outcomes.<n>Agents-A1 achieves strong and broad performance for long-horizon agent benchmarks.
  arXiv  Detail & Related papers  (2026-06-29T17:50:54Z)
• Learning Dynamic Pick-and-Place for a Legged Manipulator [8.027246382283003]
  This work presents a hierarchical reinforcement learning framework for dynamic pick-and-place tasks using a quadruped equipped with a 6-DOF robotic arm.<n>In simulation, the system achieves an 86.05% success rate with payloads up to 2.3 kg.<n>Within a wide vertical workspace ranging from ground level to 1.1m-high tabletops, the system demonstrates an average success rate of 73.3% for payloads up to 1.3 kg.
  arXiv  Detail & Related papers  (2026-05-15T08:04:07Z)
• Off-Axis Compliant RCM Joint with Near-Isotropic Stiffness and Minimal Parasitic Error [5.683284334858979]
  This paper presents an off-axis, monolithic compliant Remote Center of Motion (RCM) joint for neuroendoscopic manipulation.<n>The end-effector is placed outside the tetrahedral flexure to improve line of sight, facilitate sterilization, and allow rapid tool release.
  arXiv  Detail & Related papers  (2026-03-30T09:59:18Z)
• A Soft Wrist with Anisotropic and Selectable Stiffness for Robust Robot Learning in Contact-rich Manipulation [8.659234970380966]
  CLAW (Compliant Leaf-spring Anisotropic soft Wrist) is a novel soft wrist mechanism that addresses limitations through a simple yet effective design.<n>CLAW provides large 6-degree-of-freedom deformation (40mm lateral, 20mm vertical), anisotropic stiffness that is tunable across three distinct modes, while maintaining lightweight construction.
  arXiv  Detail & Related papers  (2026-02-16T03:45:04Z)
• Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters [169.7981969517903]
  Step 3.5 Flash bridges frontier-level agentic intelligence and computational efficiency.<n>We focus on what matters most when building agents: sharp reasoning and fast, reliable execution.
  arXiv  Detail & Related papers  (2026-02-11T07:53:51Z)
• Modular Isoperimetric Soft Robotic Truss for Lunar Applications [0.0]
  We introduce a large-scale robotic system designed as a lightweight, modular, and reconfigurable structure for lunar applications.<n>The system consists of truss-like robotic triangles formed by continuous inflated fabric tubes routed through two robotic roller units and a connecting unit.<n>When deflated, the triangles compact to approximately the volume of the roller units, achieving a stowed-to-deployed volume ratio of 1:18.3.
  arXiv  Detail & Related papers  (2026-02-02T23:41:38Z)
• RoboTracer: Mastering Spatial Trace with Reasoning in Vision-Language Models for Robotics [53.053660003572965]
  We propose RoboTracer, a 3D-aware VLM that first achieves both 3D spatial referring and measuring.<n>RoboTracer advances multi-step metric-grounded reasoning via reinforcement fine-tuning.<n>We present TraceSpatial-Bench, a challenging benchmark to evaluate spatial tracing.
  arXiv  Detail & Related papers  (2025-12-15T18:52:43Z)
• Every Attention Matters: An Efficient Hybrid Architecture for Long-Context Reasoning [73.10669391954801]
  We present the Ring-linear model series, specifically including Ring-mini-linear-2.0 and Ring-flash-linear-2.0.<n>Both models adopt a hybrid architecture that effectively integrates linear attention and softmax attention.<n>Compared to a 32 billion parameter dense model, this series reduces inference cost to 1/10, and compared to the original Ring series, the cost is also reduced by over 50%.
  arXiv  Detail & Related papers  (2025-10-22T07:59:38Z)
• Tactile Grasp Refinement using Deep Reinforcement Learning and Analytic Grasp Stability Metrics [70.65363356763598]
  We show that analytic grasp stability metrics constitute powerful optimization objectives for reinforcement learning algorithms. We show that a combination of geometric and force-agnostic grasp stability metrics yields the highest average success rates of 95.4% for cuboids. In a second experiment, we show that grasp refinement algorithms trained with contact feedback perform up to 6.6% better than a baseline that receives no tactile information.
  arXiv  Detail & Related papers  (2021-09-23T09:20:19Z)

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.