cs.RO · 2026-09-15 · No. 114

Robotics, 2026-09-15.

5 new papers in cs.RO. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

5 entries
  1. 01

    SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection

    Tong Jian, Aditya Thurvas Senthil Kumar, Xinyi Li, Ziling Chen, Tianyu Dai, Ali Sengul, Matteo Grimaldi, Wenjie Lu,...

    cs.RO · cs.AI · cs.LG

    Slip detection is fundamental to dexterous manipulation, yet existing systems often lack precise characterization of detection latency and cross-platform generalization. We present SlipSense, a multimodal tactile slip-detection framework built on TacV5, a compact sensor integrating a $32 \times 32$ piezoresistive array operating at 240 Hz and a 3-axis MEMS accelerometer operating at 8 kHz. The piezoresistive array captures spatial pressure...

    arxiv.org/abs/2609.15910 · PDF

  2. 02

    Bench2Dex: Benchmarking Visuo-Tactile Bimanual Dexterous Manipulation Across Dexterous Hands

    Zhenjie Yang, Yideng Zhang, Dongjie Zhang, Chenyu Jiang, Xianshuai Liu, Yufeng Li, Zuhao Ge, Xingyu Jiao, Zheng...

    cs.RO · cs.AI · cs.CV

    Tactile sensing provides contact information that can be difficult to infer from vision alone, but tactile hardware for dexterous hands has not converged to a common design. Dexterous hands differ in finger structure, contact surfaces, and sensor layouts, while simulated tactile signals still differ from measurements produced by physical sensors. These factors make it difficult to study visuo-tactile manipulation across diverse dexterous...

    arxiv.org/abs/2609.15726 · PDF

  3. 03

    Planning in the Backbone: DiffAdapterVLA for Native Continuous Trajectory Generation with Driving VLMs

    Changxin Lu, Xiaoliang Meng, Yu Wu, Rui Huang, Honglin Li, Tao Chen, Kaixuan Zhou, Yadong Shao

    cs.RO · cs.AI

    Pretrained driving vision-language models (VLMs) integrate visual, route, language, and driving context into rich driving priors, yet their representation objectives remain separated from continuous driving planning. Existing methods typically begin trajectory generation only after the VLM has formed a final condition, leaving depth-wise condition computation outside the stepwise formation of trajectory state. We introduce DiffAdapterVLA,...

    arxiv.org/abs/2609.15322 · PDF

  4. 04

    Legislating World-Model-Based Planning with Legal Reasoning

    Dylan Waldner, Yiannis Kantaros, Guido Governatori, Risto Miikkulainen, Amir Banifatemi

    cs.RO · cs.AI · cs.LO

    As robotic systems grow more general, legal norms are needed to integrate them into society. This paper extends the isomorphism problem of aligning legal source texts with their encodings, and measures two key challenges to robot normative control: (1) the \textit{grounding isomorphism gap}, where perception error grounds false atoms for legal reasoning, and (2) the \textit{ontological isomorphism gap}, where one legal conclusion admits many...

    arxiv.org/abs/2609.15113 · PDF

  5. 05

    Task-Distribution-Aware Counterweight Synthesis and Constrained Co-Design for Serial Manipulators

    Mohammad Abbadi

    cs.RO · cs.LG

    Passive counterweights are simple gravity compensators, but a counterweight selected from a single pose is not generally optimal for the configurations and tasks a manipulator actually executes. This paper develops a task-distribution-aware synthesis framework in which the operating distribution $ρ(q)$ enters the design explicitly. For a counterweight moment $p=m_c r_c$ with gravity torque $-gpφ(q)$, the weighted mean-square residual gravity...

    arxiv.org/abs/2609.15082 · PDF

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