A5053260432- Robot Manipulation and Learning
- Motor Control and Adaptation
- Muscle activation and electromyography studies
- Robotic Locomotion and Control
- Occupational Health and Safety Research
- Human Pose and Action Recognition
- Action Observation and Synchronization
Polytechnic Institute of Porto
2022
University of Minho
2015-2022
As robots are starting to become part of our daily lives, they must be able cooperate in a natural and efficient manner with humans socially accepted. Human-like morphology motion often considered key features for intuitive human–robot interactions because allow human peers easily predict the final intention robotic movement. Here, we present novel planning algorithm, Upper-limb Motion Planner, upper limb anthropomorphic robots, that generates collision-free trajectories human-like...
In previous work we have presented a model capable of generating human-like movements for dual arm-hand robot involved in human-robot cooperative tasks. However, the focus was on generation reach-to-grasp and reach-to-regrasp bimanual no synchrony timing taken into account. this paper extend order to accomplish manipulation tasks by synchronously moving both arms hands an anthropomorphic robotic system. Specifically, new extended has been designed two different with degrees difficulty....
Human-like motion is often considered a key feature for intuitive human–robot interactions. In fact, this allows human peers to easily predict the robot's intention, which perfectly aligned with paradigm of collaborative industries, contributing more human-centric and resilient industries. The one-sixth power law (1/6-PL) well known in motor control. work, Upper-limb Motion Planner used generate three-dimensional (3D) movements an anthropomorphic robotic arm. By applying direct kinematics,...
Inspired from established human motor control theories, our HUMP algorithm plans upper-limb collisions-free movements for anthropomorphic systems, which show kinematic human-like features [1]. Related cognitive issues can be further resolved when robots act as they are familiar with their workspace and take initiative faster than in the early onsets of a task. Here, continual learning technique is proposed to improve performance under uncertainties items given scenario. Given locality...