Tag: trajectory optimization

Engineers developed an enhanced swarm algorithm that integrates dynamic collision response times and nonlinear flight adjustments to plan safer, more ...

A new computational framework integrates genetic algorithms, neural networks, and reinforcement learning to optimize robotic kinematics and control, significantly reducing ...

Researchers developed a federated reinforcement learning algorithm that jointly optimizes task offloading and trajectory control in multi-UAV mobile edge computing ...

A parallel hybrid algorithm combining sine cosine and tabu search improves mobile robot path planning performance by up to 265% ...

Researchers have developed a distributed exploration framework that combines cooperative grid allocation with velocity-aware risk prediction to keep autonomous drone ...

A new local planner maintains a probabilistic estimate of a hidden person's position, letting indoor robots keep following targets through ...

Researchers at KTH Royal Institute of Technology show that geometry-aware normalization lets simple neural networks rapidly approximate Lambert transfer solutions ...

A comprehensive new review traces how diffusion models, the generative engines behind modern image synthesis, have become the dominant force ...

Researchers have combined conflict-based search with model predictive control to let four autonomous magnetic movers plan and execute collision-free paths ...

Researchers in China have developed VDDM, a framework combining dynamic virtual machine partitioning, matching theory, and deep reinforcement learning to ...