Influence of Visual-Inertial Sensor-to-Segment Calibration on Upper Limb Joint Angles Estimation

Influence of Visual-Inertial Sensor-to-Segment Calibration on Upper Limb Joint Angles Estimation

Research on Upper Limb Joint Angle Estimation Based on Visual-Inertial Sensors and the Impact of Calibration Methods Academic Background Upper limb dysfunction, especially in post-stroke patients, significantly impacts their ability to perform daily activities. Rehabilitation training is a critical method for restoring upper limb function, but its ...

Reinforcement Learned Multiagent Cooperative Navigation in Hybrid Environment with Relational Graph Learning

Multi-agent Cooperative Navigation in Hybrid Environments: A New Reinforcement Learning Approach Based on Relational Graph Learning Mobile robotics is witnessing a surge in applications, fueled by advancements in artificial intelligence, with navigation capabilities being one of the core focus areas of research. Traditional navigation methods often...

Adaptive Composite Fixed-Time RL-Optimized Control for Nonlinear Systems and Its Application to Intelligent Ship Autopilot

Nonlinear Fixed-Time Reinforcement Learning Optimized Control for Intelligent Ship Autopilots In recent years, intelligent autopilot technology has gradually become a research hotspot in the field of automation control. For complex nonlinear systems, the design of optimized control strategies, especially the achievement of system stability and perf...

Preference Prediction-Based Evolutionary Multiobjective Optimization for Gasoline Blending Scheduling

Preference Prediction-Based Evolutionary Multiobjective Optimization for Gasoline Blending Scheduling Background Introduction With the continuous evolution of the global energy market, gasoline production and blending processes face increasing challenges. As a key product of the oil industry, gasoline’s blending and scheduling processes directly af...

Multiobjective Dynamic Flexible Job Shop Scheduling with Biased Objectives via Multitask Genetic Programming

Breakthrough Research in Multiobjective Dynamic Flexible Job Shop Scheduling: An Innovative Approach to Optimize Biased Objectives via Multitask Learning in Genetic Programming Background Introduction Dynamic Flexible Job Shop Scheduling (DFJSS) is an essential combinatorial optimization problem with extensive real-world applications in areas such ...