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ARXIV:2604.02256 · ROBOTICS · SUBMITTED 03 APR · 20:50 UTC · FRESHNESS STALE
ARXIV:2604.02256ROBOTICSSUBMITTED 03 APR · 20:50 UTCFRESHNESS STALEWeiting Feng · Federico Renda · Yunjie Yang · Francesco Giorgio-Serchi · arXiv
A novel method for robustly solving inverse kinematics in multi-segment continuum robots, improving convergence rates and reducing iteration counts.
Opportunity summary
Pain A novel method for robustly solving inverse kinematics in multi-segment continuum robots, improving convergence rates and reducing iteration counts.
Evidence 0 refs | 0 sources | 33% coverage
Blocker Evidence unverified
A novel method for robustly solving inverse kinematics in multi-segment continuum robots, improving convergence rates and reducing iteration counts. Conventional Jacobian-based solvers, especially when initialized from neutral/rest configurations, often exhibit slow convergence and, in…
This paper proposes a new, robust method to solve the inverse kinematics (IK) of multi-segment continuum manipulators. Conventional Jacobian-based solvers, especially when initialized from neutral/rest configurations, often exhibit slow convergence and, in certain conditions,…
ScienceToStartup currently rates this 4.0/10 on the public viability pass. While deadlocks are not restricted to workspace boundaries and may occur at arbitrary poses, our empirical study identifies boundary-proximal configurations as a frequent cause…
Robotics moved forward this cycle; last verified April 2026. Public score 4.0/10. Production flags indicate code availability.
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A novel method for robustly solving inverse kinematics in multi-segment continuum robots, improving convergence rates and reducing iteration counts.
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10.48550/arXiv.2604.02256A novel method for robustly solving inverse kinematics in multi-segment continuum robots, improving convergence rates and reducing iteration counts.
Abstract
This paper proposes a new, robust method to solve the inverse kinematics (IK) of multi-segment continuum manipulators. Conventional Jacobian-based solvers, especially when initialized from neutral/rest configurations, often exhibit slow convergence and, in certain conditions, may fail to converge (deadlock). The Virtual-Variable-Length (VVL) method proposed here introduces fictitious variations of segments' length during the solution iteration, conferring virtual axial degrees of freedom that alleviate adverse behaviors and constraints, thus enabling or accelerating convergence. Comprehensive numerical experiments were conducted to compare the VVL method against benchmark Jacobian-based and Damped Least Square IK solvers. Across more than $1.8\times 10^6$ randomized trials covering manipulators with two to seven segments, the proposed approach achieved up to a 20$\%$ increase in convergence success rate over the benchmark and a 40-80$\%$ reduction in average iteration count under equivalent accuracy thresholds ($10^{-4}-10^{-8}$). While deadlocks are not restricted to workspace boundaries and may occur at arbitrary poses, our empirical study identifies boundary-proximal configurations as a frequent cause of failed convergence and the VVL method mitigates such occurrences over a statistical sample of test cases.
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PROBLEM
A novel method for robustly solving inverse kinematics in multi-segment continuum robots, improving convergence rates and reducing iteration counts. Conventional Jacobian-based solvers, especially when initialized from neutral/rest configurations, often exhibit slow convergence...
METHOD
This paper proposes a new, robust method to solve the inverse kinematics (IK) of multi-segment continuum manipulators. Conventional Jacobian-based solvers, especially when initialized from neutral/rest configurations, often exhibit slow convergence and, in certain conditions, ma...
RESULT
ScienceToStartup currently rates this 4.0/10 on the public viability pass. While deadlocks are not restricted to workspace boundaries and may occur at arbitrary poses, our empirical study identifies boundary-proximal configurations as a frequent cause of failed convergence and t...
WHY NOW
Robotics moved forward this cycle; last verified April 2026. Public score 4.0/10. Production flags indicate code availability.
the proposed approach achieved up to a 20% increase in convergence success rate over the benchmark
Directly stated in abstract with specific numeric result (20% increase)
partial
a 40-80% reduction in average iteration count under equivalent accuracy thresholds (10^{-4}-10^{-8})
Directly stated in abstract with specific numeric range (40-80% reduction)
partial
The Virtual-Variable-Length (VVL) method proposed here introduces fictitious variations of segments' length during the solution iteration, conferring virtual axial degrees of freedom
Directly stated in abstract as the core mechanism of the proposed method
partial
Conventional Jacobian-based solvers, especially when initialized from neutral/rest configurations, often exhibit slow convergence and, in certain conditions, may fail to converge (deadlock)
Directly stated in abstract as motivation for the research
partial
While deadlocks are not restricted to workspace boundaries and may occur at arbitrary poses
Directly stated in abstract, though presented as an empirical finding
partial
our empirical study identifies boundary-proximal configurations as a frequent cause of failed convergence
Directly stated in abstract as an empirical finding from the study
partial
Across more than $1.8\times 10^6$ randomized trials covering manipulators with two to seven segments
Directly stated in abstract with specific numeric details about the experimental scope
partial
the VVL method mitigates such occurrences over a statistical sample of test cases
Directly stated in abstract as a conclusion of the empirical study
partial
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A novel method for robustly solving inverse kinematics in multi-segment continuum robots, improving convergence rates and reducing iteration counts.
Segment
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