Results 311 to 320 of about 4,794,580 (401)
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
A Review on Sensor Technologies, Control Approaches, and Emerging Challenges in Soft Robotics
This review provides an introspective of sensors and controllers in soft robotics. Initially describing the current sensing methods, then moving on to the control methods utilized, and finally ending with challenges and future directions in soft robotics focusing on the material innovations, sensor fusion, and embedded intelligence for sensors and ...
Ean Lovett +5 more
wiley +1 more source
Conserving Freshwater Biodiversity in U. S. Protected Areas - Management Intervention and the RAD Framework. [PDF]
Carim KJ +7 more
europepmc +1 more source
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley +1 more source
One health-sustainability intersections: an umbrella systematic review with a new integrated definition of sustainability and a meta-conceptual framework. [PDF]
Dar OA +7 more
europepmc +1 more source
TreeSpider: In‐Canopy Exploration With Tether‐Based Aerial Modular Arms
A tethered drone with perching arms and a 360° ring enables unprecedented maneuverability within dense forest canopies. By dynamically adjusting tether length and decoupling pitch from the frame, it navigates between branches, senses multiple trees, and interacts physically with foliage.
Luca Romanello +7 more
wiley +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source

