Abstract-We propose an online iterative path optimisation method to enable a Baxter humanoid robot to assist human users to dress. The robot searches for the optimal personalised dressing path using vision and force sensor information: vision information is used to recognise the human pose and model the movement space of upper-body joints; force sensor information is used for the robot to detect external force resistance and to locally adjust its motion. We propose a new stochastic path optimisation method based on adaptive moment estimation. We first compare the proposed method with other path optimisation algorithms on synthetic data. Experimental results show that the performance of the method achieves the smallest error with fewer iterations and less computation time. We also evaluate real-world data by enabling the Baxter robot to assist real human users with their dressing.
A novel optimization algorithm, Group Area Search (GAS), is proposed, which is inspired by searching behavior patterns of human beings and social animals. In GAS, the search area of each individual is automatically adjusted and gradually shrunk to the most promising region. A cruising-following mechanism is introduced to GAS, which allows individuals with low fitness chances to follow the historical best individual. The algorithm strikes a good balance between global search and local search. The experimental results on 6 benchmark functions show that GAS has good performance on both unimodal and multimodal test functions, especially on multimodal ones. It significantly outperforms six other population-based algorithms. It shows potential to solve complicated function optimization problems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.