首页|Studies from Beijing Institute of Technology in the Area of Robotics and Automat ion Described (Multi-step Continuous Decision Making and Planning In Uncertain D ynamic Scenarios Through Parallel Spatio-temporal Trajectory Searching)
Studies from Beijing Institute of Technology in the Area of Robotics and Automat ion Described (Multi-step Continuous Decision Making and Planning In Uncertain D ynamic Scenarios Through Parallel Spatio-temporal Trajectory Searching)
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Researchers detail new data in Robotic s -Robotics and Automation. According to news reporting originating from Beijin g, People's Republic of China, by NewsRx correspondents, research stated, "Auton omous driving in urban scenarios faces uncertain dynamic changes, especially in China, where a dense mixture of cars, cyclists and pedestrians travel together o n roads with random uncertain behaviors and high-risk road crossing. This letter proposes a Multi-step Continuous Decision Making and Spatiotemporal Trajectory Planning framework to achieve stable continuous decision making and high-qualit y trajectory planning in such uncertain and highly dynamic environments." Financial support for this research came from Huawei Technologies. Our news editors obtained a quote from the research from the Beijing Institute o f Technology, "Firstly, a 3D spatio-temporal probabilistic map is constructed to represent the uncertain future driving environment. Based on the map, parallel spatio-temporal trajectory search is performed to obtain multi-strategy feasible spatio-temporal trajectories that satisfy the short-term deterministic and long -term uncertain environmental constraints. Then considering the continuity and c onsistency of decision making, risk-aware rolling-fusion of trajectory sequences is proposed, achieving efficient and exploratory far-end planning with a stable and safe near-end driving trajectory. To validate the proposed framework, we co llected the Hard Case data from real Chinese urban roads, containing challenging scenarios such as dense traffic flows, mixed vehicle-pedestrian roads, and comp lex intersections, which are widely recognized barriers to the successful real-w orld deployment of autonomous driving. Moreover, the SMARTS simulator is used to build closed-loop simulation scenarios to verify the effectiveness of the frame work."
BeijingPeople's Republic of ChinaAsiaRobotics and AutomationRoboticsBeijing Institute of Technology
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