When the vehicle is on a split-μramp and is restricted by the differential's torque-equalizing characteristic,a sig-nificant functional conflict may occur between the driving force limitation requirement of the a...When the vehicle is on a split-μramp and is restricted by the differential's torque-equalizing characteristic,a sig-nificant functional conflict may occur between the driving force limitation requirement of the acceleration slip regulation(ASR)control strategy for low-adhesion side wheels and the driving force enhancement demand of the entire vehicle during hill starting.Aiming at this problem,this paper proposes an ASR control strategy for the start-up of the electric vehicle on the split-μramp based on the combined control architecture of the service brake system and the parking brake system.First,the relationship between the driving force,braking force,and road adhesion at the slip moment is analyzed,and the ground adhesion estimation algorithm based on the dynamic equation of the driving wheel slip moment is proposed.Second,a service braking torque control model is constructed,and an ASR controller method based on the super-twisting sliding mode control(STSMC)algorithm is proposed to study the hill start assist(HSA)control strategy of electric vehicles on split-μroads.Finally,the proposed control strategy is si-mulated in this paper.The simulation results show that the proposed strategy can accurately estimate the ground adhesion of the driving wheel on the low-adhesion side effectively preventing the vehicle from slipping back,and improving the dynamic performance of the vehicle under harsh conditions.展开更多
The objective of this work is to develop an innovative system(ROSGPT)that merges large language models(LLMs)with the robot operating system(ROS),facilitating natural language voice control of mobile robots.This integr...The objective of this work is to develop an innovative system(ROSGPT)that merges large language models(LLMs)with the robot operating system(ROS),facilitating natural language voice control of mobile robots.This integration aims to bridge the gap between human-robot interaction(HRI)and artificial intelligence(AI).ROSGPT integrates several subsystems,including speech recognition,prompt engineering,LLM and ROS,enabling seamless control of robots through human voice or text commands.The LLM component is optimized,with its performance refined from the open-source Llama2 model through fine-tuning and quantization procedures.Through extensive experiments conducted in both real-world and virtual environments,ROSGPT demonstrates its efficacy in meeting user requirements and delivering user-friendly interactive experiences.The system demonstrates versatility and adaptability through its ability to comprehend diverse user commands and execute corresponding tasks with precision and reliability,thereby showcasing its potential for various practical applications in robotics and AI.The demonstration video can be viewed at https://iklxo6z9yv.feishu.cn/docx/Lux3dmTDxoZ5YnxWJTZcxUCWnTh.展开更多
基金Supported by the National Natural Science Foundation of China(Grant No.52172369).
文摘When the vehicle is on a split-μramp and is restricted by the differential's torque-equalizing characteristic,a sig-nificant functional conflict may occur between the driving force limitation requirement of the acceleration slip regulation(ASR)control strategy for low-adhesion side wheels and the driving force enhancement demand of the entire vehicle during hill starting.Aiming at this problem,this paper proposes an ASR control strategy for the start-up of the electric vehicle on the split-μramp based on the combined control architecture of the service brake system and the parking brake system.First,the relationship between the driving force,braking force,and road adhesion at the slip moment is analyzed,and the ground adhesion estimation algorithm based on the dynamic equation of the driving wheel slip moment is proposed.Second,a service braking torque control model is constructed,and an ASR controller method based on the super-twisting sliding mode control(STSMC)algorithm is proposed to study the hill start assist(HSA)control strategy of electric vehicles on split-μroads.Finally,the proposed control strategy is si-mulated in this paper.The simulation results show that the proposed strategy can accurately estimate the ground adhesion of the driving wheel on the low-adhesion side effectively preventing the vehicle from slipping back,and improving the dynamic performance of the vehicle under harsh conditions.
基金National Natural Science Foundation of China(No.61601112)。
文摘The objective of this work is to develop an innovative system(ROSGPT)that merges large language models(LLMs)with the robot operating system(ROS),facilitating natural language voice control of mobile robots.This integration aims to bridge the gap between human-robot interaction(HRI)and artificial intelligence(AI).ROSGPT integrates several subsystems,including speech recognition,prompt engineering,LLM and ROS,enabling seamless control of robots through human voice or text commands.The LLM component is optimized,with its performance refined from the open-source Llama2 model through fine-tuning and quantization procedures.Through extensive experiments conducted in both real-world and virtual environments,ROSGPT demonstrates its efficacy in meeting user requirements and delivering user-friendly interactive experiences.The system demonstrates versatility and adaptability through its ability to comprehend diverse user commands and execute corresponding tasks with precision and reliability,thereby showcasing its potential for various practical applications in robotics and AI.The demonstration video can be viewed at https://iklxo6z9yv.feishu.cn/docx/Lux3dmTDxoZ5YnxWJTZcxUCWnTh.
