Research on the Hybrid Unmanned Tracked Mobile Platform with High Environmental Adaptability and Traversability
Supported by the Ministry of Industry and Information Technology
Jun. 2020 – Current
- Designed a heavy tracked unmanned ground vehicle (HTUGV) working in the unstructured environment
- Designed the autonomous driving framework for the HTUGV and collected driving datasets under manual and autonomous modes
- Established the suspension-aware vehicle-terrain contact model (PHISI), which was applied to the motion planning on uneven terrain and the safety verification of obstacle-crossing control.
China Ground Unmanned Systems Challenge
Supported by the Ministry of Industry and Information Technology
Sep. 2021 – Sep. 2023
- As the team leader, led the team to participate in competitions across three categories.
- Developed and maintained the off-road topology extraction technology based on satellite imagery.
- Developed planning and control algorithms for unstructured environments, including FSM-A*-based global decision-making, V2V-based following strategy, PHISI-based local motion planning, and MPC-based tracking control algorithm.
Theoretical Fundamentals and Key Technologies of Brain-Machine Hybrid Control for Ground Mobile Platforms
Supported by the National Nature Science Foundation of China
Sep. 2020 – Jun. 2022
- Designed an Autonomous Suburban Utility Vehicle (ASUV) based on commercially available vehicles, capable of operating in both structured and unstructured environments.
- Proposed a time-series risk field as a brain-machine interface for drivers and autonomous systems. Constructed by collecting the driver's visual attention and Electroencephalography (EEG), it facilitates human-like planning for autonomous modules.
- Proposed an efficient risk-aware spatiotemporal trajectory planning method based on Adaptive Motion Primitives and Bilevel Corridor.
Economic Motion Planning and Powertrain Control Method for Hybrid Commercial Vehicles Based on Intelligent Network Connection
National Nature Science Foundation of China
Dec. 2023 – Current
- Proposed a spatiotemporally coupled decision-making and planning technique with both lateral and longitudinal integration.
- Proposed Behavior Cell for rapid semantic-level enumeration of maneuver homotopy in the spatiotemporal drivable space.
- Integrated and validated the proposed algorithm in real-world complex traffic scenarios.
Research on the Autonomous Capability Assessment System for Ground Unmanned Platforms and the Construction of an Environmental Database
Supported by the Ministry of Industry and Information Technology
Sep. 2020 – Jun. 2021
- Constructed a hierarchical assessment model for autonomous capabilities based on environment-task-performance.
- Proposes a sampling-based multi-dimensional entropy hierarchical evaluation method to quantify the environmental complexity.
- Built the data collection platform in the real-world environment and collected environmental datasets from various types of scenes.