Friday, November 13, 2026
18 papers added this day. New papers stay for 14 days.
Tactile sensing 2
Imitation learning and data collection 4
Robot foundation models 4
Humanoids and mobile manipulation 3
Planning and control 2
HRI and teleoperation 1
Robot hardware and actuators 2
FORGE: Force-Aware Multi-Granularity Control for Efficient Humanoid Loco-Manipulation
November 2026
One RL policy for a G1 humanoid takes velocity, foothold, wrist-pose and wrist-force commands, and estimates wrist contact forces from arm joint torques without force sensors. It cuts wrist tracking error to 4.15 cm (vs 6.42-7.76 cm for TWIST2 and SONIC), and a diffusion policy driving it carries boxes of up to 2 kg in 18-20 of 20 trials.
EgoX: Egocentric Cross-Embodiment Manipulation with Embodiment Dreaming
November 2026
EgoX pretrains one modular Transformer policy on egocentric demonstrations from humans, five real robots and a simulated humanoid, then fine-tunes it on each target robot. Pretraining raises average task progress from 0.63 to 0.80 across 13 task-robot pairs, and from 0.53 to 0.77 out of distribution.
STVLA: Spatial-aware and Temporal-memory for Vision-Language-Action Models
November 2026
STVLA adds a memory of past 3D scene-geometry features, taken from a frozen visual geometry model, to the pi0.5 VLA. On three real dual-arm tasks it averages 76.7% success against 35.6% for pi0.5, including 60/60 block stacks.
HALO: Human-Aligned Data Collection for WhoLe-body MObile Manipulation
November 2026
HALO collects whole-body mobile manipulation demonstrations by having the operator move the robot's arms by hand while walking a passive, base-free platform, then inpaints the operator's hands out of the video. Collection is up to 2.9x faster than Mobile ALOHA, and a fine-tuned pi0.5 policy completes a six-stage shelf-to-conveyor task in 11 of 15 trials.
I See What You Want: Decoding Hierarchical Operator Intent from Visual Teleoperation History
November 2026
A VLM fine-tuned on VI AMO, 6,600 robot episodes labeled with atomic actions and the missions they serve, guesses from a few teleoperation frames what the operator is doing and why, at 0.825/0.821 SBERT similarity versus at most 0.581/0.564 for GPT and robotics VLMs. Handing its predicted mission to a VLA policy on a real Franka cut teleoperation time by 34.6% compared with using GPT-4o.
ManiLadder: Benchmarking Robot Manipulation Through a Categorized and Multi-Difficulty Level Task Ladder
November 2026
A simulation benchmark of 112 manipulation tasks, sorted into four difficulty levels by how well a reference imitation policy learns each from 20 demonstrations. Fine-tuned π0.5 reliably clears only Level 1, and one π0.5 policy trained on all 112 tasks reaches 8.6% success against 33.5% for per-task policies.
Visibility-Aware Task and Motion Planning with Task-Centric Perception
November 2026
VA-TAMP wraps a fully observed TAMP solver so the robot must see the space it moves through and the surfaces it grasps before acting, inserting wrist-camera looks and refining only task-relevant object meshes. On three occluded real-robot tabletop tasks it succeeds in 9/10, 10/10 and 10/10 trials, against 2/10, 3/10 and 0/10 for the open-loop TiPToP baseline.
DexRemo: A Force-Sensing Hand Platform and Task Suite for Contact-Rich Removal Manipulation
November 2026
A low-cost three-finger hand with three-axis force sensors in every fingertip, plus a nine-task real-robot suite for peeling, scraping, wiping and digging targets free. Giving an imitation policy fingertip poses and forces rotated into a shared wrist frame raises success on six core tasks to 83%, against 55% with the same forces in each fingertip's local frame.
Video-Action Models for Data-Efficient Industrial Manipulation
November 2026
FLUX-mimic attaches an action expert to a large pretrained video model and trains it on video and actions from automotive assembly tasks. On a bimanual Franka with dexterous hands it averages 82.8% success over four factory tasks, against 52.6% for a single-task policy and 27.6% for pi0.5.
MOSAIC: Modular Obstacle and Spatial-Aware Framework for Manipulation In Cluttered Scenes
November 2026
Add-on modules for a pretrained π0.5 VLA that predict target, destination and obstacle masks, inject object-level depth, and steer attention toward nearby obstacles. On the cluttered RoboPRO benchmark success rises from 52.7% to 57.8%, and under visual perturbations from 65.2% to 74.9%.
RUMI: A Robotiq-Matched Universal Manipulation Interface for Robot Learning with Augmented Reality and Haptic Feedback
November 2026
A handheld gripper that copies the Robotiq 2F-85's kinematics, takes swappable force or tactile fingertips, shows the target robot in AR while recording and locks its linkage for haptic feedback during teleoperation. With AR, novices' demonstrations hit joint limits in 3/50 episodes instead of 16/50, and fingertip force sensing lifts real-robot gear-assembly success from 7/20 to 20/20.
Helping Hand: A Continuum Robotic Grasper for Traction in Single-Channel Endoscopic Submucosal Dissection
November 2026
The Helping Hand is a tendon-driven, notched Nitinol continuum grasper with a slot at its base for an electrosurgical knife, so tissue traction and cutting both fit through one 3.7 mm colonoscope channel. It applied about 0.33 N of traction at every tested phantom height, and with the knife it removed a tissue sample from ex vivo chicken thigh in one piece in 15 min.
Generalized Inverse Kinematics via Conditional Flow
November 2026
GenGenIK trains one conditional flow-matching Transformer to sample whole-body IK solutions for mobile bases, multiple end-effectors, multi-target paths, observed scenes and posture preferences. On five simulated RB-Y1 path tasks it solves 92.7-100% of problems with 32 samples in 20-36 ms, against 22.0-92.0% and 167-1067 ms for cuRobo.
Actuation and Control of Passive Tendon-Driven Soft Extensions Through Rigid Manipulator Motion
November 2026
An industrial arm bends a passive tendon-driven soft extension with its own joint motion, because tendons anchored on upstream links tighten or slacken as the arm moves, while the end effector holds a position or fulcrum constraint. In simulation the tip reached every feasible target within 4 mm; on a real UR10 with handmade extensions costing under US$10, it reached 6 of 16 targets and every safety barrier held.
Low-Cost Mobile Bimanual Manipulation for Long-Horizon Toilet Cleaning
November 2026
A mobile bimanual robot costing about €3,200, built from two LeRobot SO-101 arms on a TurtleBot 4, used to compare open VLA policies on a five-stage toilet-cleaning task. Fine-tuned on 250 real demonstrations, π0 does best with 60% strict success (90% with one human intervention); π0.5, SmolVLA, GR00T and the memory- and progress-augmented variants all do worse.
Interactive Perception of Granular Materials via Robotic Scooping and Force-Torque Sensing
November 2026
A Franka scoops granular materials with a spoon on a wrist force-torque sensor, and Latent Filter++ estimates grain size and bulk density online from the raw signal. On materials left out of training it beats a supervised CNN+LSTM (grain-size error 0.50 vs 0.63 in log10 with five of 26 materials held out).
ILA: A Transferable Interface-Level Adapter for Compliant Humanoid Motion Tracking
November 2026
ILA is a small adapter, trained in simulation, that edits the arm reference a frozen humanoid motion tracker follows, so the robot yields when a person guides its hand. The same adapter cuts guidance-target error by 63.6-75.4% across three trackers and lets each of them complete wrist-pull, disturbance and handshake trials 10/10 on a real G1.
Learning Low-Latency Action Verification for Frozen Vision-Language-Action Models
November 2026
A compact verifier, trained only on whether a frozen pi0.5 policy's own past rollouts succeeded, scores two sampled action chunks and the robot executes the better one. On a real Franka this raises average success on three tasks from 44.7% to 67.3%; on LIBERO it adds 3.5 points for 5.4% more median query latency.
Summaries are written automatically from each paper's text. Figures and videos come from the paper and its project page; all credit goes to the authors.