概览

简介

RL78/G23-64p 快速原型开发板配备RL78/G23微控制器,是一种专门用于各种应用开发试产的原型开发板。它只需连接USB线即可编写/调试程序,无需任何其他工具即可着手评估。此外,它还可以使用传统E2仿真器和E2 Lite仿真器实现高性能调试(有关方法,请参考用户手册)。标配Arduino Uno和Grove接口,具有高度的可扩展性,譬如能够访问微控制器的所有引脚。本产品还支持使用Arduino IDE写入程序。

特性

  • 配备16位微控制器(64脚、ROM:128KB, RAM:16KB)
  • 使用USB线连接到电脑,即可通过COM端口通信编写/调试程序
  • 可以访问微控制器的所有引脚
  • 标配Arduino Uno和Grove接口
  • 支持Arduino IDE
  • 适用RL78开发环境(软件和工具请参阅此处

应用

文档

设计和开发

软件与工具

软件与工具

Software title
Software type
公司
E2 emulator Lite [RTE0T0002LKCE00000R]
On-chip debugging emulator. Also available as a flash memory programmer. [Support MCU/MPU: RA, RE, RL78, RX, RISC-V MCU]
Emulator 瑞萨电子
E2 emulator [RTE0T00020KCE00000R]
On-chip debugging emulator. Also available as a flash memory programmer. [Support MCU/MPU: RA, RE, RH850, R-Car D1, RL78, RX, RISC-V MCU]
Emulator 瑞萨电子
2 items

软件下载

类型 文档标题 日期
Board Description File ZIP 1 KB
PCB设计文档 ZIP 2.97 MB
PCB设计文档 PDF 168 KB
3 items

样例程序

相关评估板和套件

开发板与套件

使用Chat-GPT为RL78微控制器(Arduino)编写AI代码

这个视频介绍了如何使用ChatGPT和RL78 Arduino兼容板进行AI编程,包括点亮7段LED、旋转电机和使用温湿度传感器进行感应等实际例子。即使是初学者也能轻松体验AI编程!

 

详细的步骤介绍:

使用Chat-GPT为RL78微控制器(Arduino)编写AI代码 | Renesas

 

相关产品: RL78/G23-64p FPB

相关资源: Quick Start Guide page (GitHub)

 

Disclaimer:

1. Informational Purposes Only: This video serves as a general guide to using ChatGPT/GPT-4 to write code for an Arduino RL78 evaluation board. Renesas does not guarantee the accuracy or completeness of the content provided.

2. Third-Party Rights Infringement: Note that code generated using ChatGPT/GPT-4 might potentially infringe third-party intellectual property rights. Renesas makes no representations or warranties that the use of ChatGPT/GPT-4 will not violate any third-party rights. Users are urged to exercise due diligence to ensure compliance with applicable laws and third-party rights.

3. No Liability: In no event shall Renesas be liable for any damages, data loss, or other adverse consequences that may occur as a result of using the information, code, techniques, or tools demonstrated in this video. You may want to apply industry standard static and dynamic code assessments as AI code has been recognized to possibly contain malware fragments as well as deriving other unwanted outcomes.