8 citations · 11 across the 8 of their papers we have counts for
Showing cs.ROShow all
3 papers · 1 filter
cs.RO2023★ 1 cited
Hybrid of representation learning and reinforcement learning for dynamic and complex robotic motion planning
Chengmin Zhou, Xin Lu, Jiapeng Dai +3
Motion planning is the soul of robot decision making. Classical planning algorithms like graph search and reaction-based algorithms face challenges in cases of dense and dynamic ob…
cs.RO2021★ 1 cited
An advantage actor-critic algorithm for robotic motion planning in dense and dynamic scenarios
Chengmin Zhou, Bingding Huang, Pasi Fränti
Intelligent robots provide a new insight into efficiency improvement in industrial and service scenarios to replace human labor. However, these scenarios include dense and dynamic…
cs.RO2021★ 8 cited
A review of motion planning algorithms for intelligent robotics
Chengmin Zhou, Bingding Huang, Pasi Fränti
We investigate and analyze principles of typical motion planning algorithms. These include traditional planning algorithms, supervised learning, optimal value reinforcement learnin…