#motionplanning
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ieeetro.bsky.social
This T-RO paper presenting at ‪#ICRA2025 introduces a method integrating parametric curves into Motion Manifold Primitives. This approach ensures isometric latent spaces for better performance & online adaptation.
ieeexplore.ieee.org/document/106...

#Robotics #MotionPlanning #AI #IEEEras
There are 15 demonstration trajectories (red, green, and blue trajectories) that travel from the start to the goal, avoiding the obstacle. Middle and Right: MMP++ and IMMP++ learn 2-D manifolds in the curve parameter space and produce 2-D latent coordinate spaces. Latent values of the demonstration trajectories are visualized in the latent coordinate spaces, marked as ×. GMMs of three components are fitted in the latent spaces, and the sampled points are visualized as stars ∗. The corresponding generated trajectories are also visualized.
May 20, 2025 at 7:41 PM
ai-bloom.warp-studio.com
ロボットが「安全な衝突」を判断する新AIシステム：USC Viterbiが開発した状況認識型AI『IMPACT』の技術的深掘り

USC ViterbiのAI「IMPACT」がロボットに状況に応じた安全な衝突判断を可能に。

#AI #Robotics #MotionPlanning #CollisionAvoidance #Context-AwareAI
ロボットが「安全な衝突」を判断する新AIシステム：USC Viterbiが開発した状況認識型AI『IMPACT』の技術的深掘り
USC ViterbiのAI「IMPACT」がロボットに状況に応じた安全な衝突判断を可能に。
ai.warp-studio.com
July 21, 2026 at 10:45 PM
ieeetro.bsky.social
#HonorableMention: Physics-Informed #NeuralMapping & Motion Planning in Unknown Environments; bridges neural representations with classic planning by embedding physics priors into learned environment maps. Enabling efficient #MotionPlanning w/o knowledge
https://ieeexplore.ieee.org/document/10916504
July 3, 2026 at 2:30 PM
getnews-me.bsky.social
Two multi‑query motion‑planning algorithms for linear Gaussian systems guarantee reachability to a Euclidean ball and an ellipsoid‑plus‑ball region, improving coverage. https://getnews.me/efficient-probabilistic-planning-with-robust-reachable-trees/ #probabilisticplanning #motionplanning
Efficient Probabilistic Planning with Robust Reachable Trees
October 8, 2025 at 4:52 AM
getnews-me.bsky.social
A graph‑based planner for a soft robotic arm with three artificial muscle fibers can produce collision‑free, energy‑aware paths in just a few milliseconds. Read more: https://getnews.me/shape-space-graphs-enable-fast-collision-free-planning-for-soft-robots/ #softrobots #motionplanning
Shape‑Space Graphs Enable Fast Collision‑Free Planning for Soft Robots
October 7, 2025 at 4:38 PM
getnews-me.bsky.social
A new framework fuses diffusion models with artificial potential fields for real‑time motion planning from raw point clouds, succeeding in pursuit‑evasion tests. Read more: https://getnews.me/fast-motion-planning-using-point-cloud-diffusion-and-potential-fields/ #motionplanning #pointcloud
Fast Motion Planning Using Point Cloud Diffusion and Potential Fields
September 20, 2025 at 12:01 PM
getnews-me.bsky.social
A new motion-planning layer for wearable robotic limbs enforces angular-acceleration and position-deviation limits, cutting peak torque in simulations. Read more: https://getnews.me/new-motion-planning-approach-cuts-torque-in-wearable-robotic-limbs/ #wearablerobotics #motionplanning
New Motion Planning Approach Cuts Torque in Wearable Robotic Limbs
September 17, 2025 at 7:07 AM
grarknal.bsky.social
We are looking for #MotionPlanning users to answer a small survey on understanding and explanation of motion plans. Can you help? @MartimBrandao @senka_snow @rosorg @OpenRoboticsOrg @ROSIndustrial @PickNikRobotics @_TheConstruct_ #moveit #goros https://t.co/dR4kicHfC1
Motion planning explanations
Estimated time to complete: 25 minutes The goal of this questionnaire is to understand current issues with the use of motion planners, as well as the potential role that planner-generated explanations could have in dealing with these issues. The questionnaire has 5 parts: 1. Questions about yourself and your experience with planners 2. Questions about issues of failure to find feasible solutions 3. Questions about issues of unexpected motion 4. Your feedback 5. Evaluating examples of explanations Your input will be anonymized. The authors of this questionnaire are: Martim Brandao, Gerard Canal, Senka Krivic (King's College London) In case of concerns regarding the questionnaire and/or data protection, please contact martim.brandao@kcl.ac.uk
docs.google.com
February 20, 2025 at 5:47 PM
azoai.bsky.social
GPD-1: The Next Leap in Autonomous Driving Technology 🚗🤖✨ www.azoai.com/news/2025010... #AutonomousDriving #AI #MachineLearning #GenerativeModels #TrafficSimulation #MotionPlanning #SmartTechnology #FutureMobility #AI #Research @arxiv-stat-ml.bsky.social
GPD-1: The Next Leap in Autonomous Driving Technology
Explore GPD-1's transformative approach to motion planning and traffic simulation for smarter vehicles.
www.azoai.com
January 2, 2025 at 2:47 AM
gitrated.bsky.social
A new AI review! zhm-real/MotionPlanning ⭐2.7/5.0
zhm-real/MotionPlanning is a Python-based educational repository that implements several classic autonomous-vehicle motion planning and path-tracking components: Hybrid A, Frenet optimal trajectory gene...
https://gitrated.com/zhm-real/MotionPlanning
GitRated repository card for zhm-real/MotionPlanning
May 26, 2026 at 5:51 PM