Smooth Feedback Motion Planning with Reduced Curvature | Signal Canvas | ScienceToStartup

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Smooth Feedback Motion Planning with Reduced Curvature

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stale

Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-04-03
Score updated: 2026-04-03
Score fresh until: 2026-05-03
References: 0
Source count: 0
Coverage: 33%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Smooth Feedback Motion Planning with Reduced Curvature

Canonical ID smooth-feedback-motion-planning-with-reduced-curvature | Route /signal-canvas/smooth-feedback-motion-planning-with-reduced-curvature

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/smooth-feedback-motion-planning-with-reduced-curvature

MCP example

{
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  "arguments": {
    "mode": "paper",
    "paper_ref": "smooth-feedback-motion-planning-with-reduced-curvature",
    "query_text": "Summarize Smooth Feedback Motion Planning with Reduced Curvature"
  }
}

source_context

{
  "surface": "signal_canvas",
  "mode": "paper",
  "query": "Smooth Feedback Motion Planning with Reduced Curvature",
  "normalized_query": "2604.01614",
  "route": "/signal-canvas/smooth-feedback-motion-planning-with-reduced-curvature",
  "paper_ref": "smooth-feedback-motion-planning-with-reduced-curvature",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Paper mode· single-doc scopescope: smooth-feedback-motion-planning-with-reduced-curvature

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GitHub Code Pulse

No public code linked for this paper yet.

Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
reducing total bending by an average of 91.40%
Implicationpartial
Explicitly stated numeric result in abstract with specific percentage
Verificationpartial
partial
Evidencepartial
LQR control effort by an average of 45.47%
Implicationpartial
Explicitly stated numeric result in abstract with specific percentage
Verificationpartial
partial
Evidencepartial
a novel geometric algorithm that constructs a maximal star-shaped chain of simplexes around the goal
Implicationpartial
Directly stated as a novel contribution in the abstract
Verificationpartial
partial
Evidencepartial
presents a computationally efficient method to mitigate this issue for a given simplicial decomposition
Implicationpartial
Directly stated in abstract but without specific timing measurements
Verificationpartial
partial
Evidencepartial
the practical application focuses on low-dimensional (d≤3) configuration spaces, where simplicial decomposition is computationally tractable
Implicationpartial
Explicit limitation stated in abstract with dimensional constraint
Verificationpartial
partial
Evidencepartial
our method generates measurably more direct paths
Implicationpartial
Directly stated in abstract with supporting evidence from bending reduction metrics
Verificationpartial
partial
Evidencepartial
comparative analysis against sampling-based and optimization-based planners confirms the time efficacy and robustness of our approach
Implicationpartial
Directly stated in abstract but without specific comparative metrics provided
Verificationpartial
partial
Evidencepartial
the proposed algorithms work over any finite-dimensional simplicial complex embedded in the collision-free subset of the configuration space
Implicationpartial
Explicit technical statement about algorithm generality in abstract
Verificationpartial
partial