OTP R14A今天发布了

本次更新主要集中在修复大量BUG,并未进行大幅度的性能改进。亮点包括实现了二进制模块,允许用户通过自定义回调模块处理配置数据,引入了新的NIF特性等。

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以下是这次发布的亮点,没有太大的性能改进, 主要是修理了很多BUG!

--- HIGHLIGHTS ----------------------------------------------------------

OTP-8217 == erts stdlib compiler ==

The module binary from EEP31 (and EEP9) is implemented.

OTP-8485 == common_test ==

It is now possible for the user to provide specific callback
modules that handle test configuration data, so that data on
arbitray form can be accessed (e.g. by reading files or by
communicating with a configuration server process). Two
default callback modules have been introduced in Common Test:
ct_config_plain and ct_config_xml. The former is used to
handle the traditional Common Test configuration files (with
terms on key-value tuple form) and the latter to handle
configuration data on XML representation.

OTP-8555 == erts ==

New NIF features:

Send messages from a NIF, or from thread created by NIF, to
any local process (enif_send)

Store terms between NIF calls (enif_alloc_env,
enif_make_copy)

Create binary terms with user defined memory management
(enif_make_resource_binary)

And some incompatible changes made to the API. For more
information see the warning text in erl_nif(3).

OTP-8623 == compiler erts hipe stdlib ==

Receive statements that can only read out a newly created
reference are now specially optimized so that it will execute
in constant time regardless of the number of messages in the
receive queue for the process. That optimization will benefit
calls to gen_server:call(). (See gen:do_call/4 for an example
of a receive statement that will be optimized.)

OTP-8650 == common_test ==

The run_test script has been replaced by a program (with the
same name) which can be executed without explicit
installation. The start flags are the same as for the legacy
start script.

OTP-8706 == erts hipe tools ==

eprof has been reimplemented with support in the Erlang
virtual machine and is now both faster (i.e. slows down the
code being measured less) and scales much better. In
measurements we saw speed-ups compared to the old eprof
ranging from 6 times (for sequential code that only uses one
scheduler/core) up to 84 times (for parallel code that uses 8
cores).

Note: The API for the eprof has been cleaned up and extended.
See the documentation.

期待R14B有大的动作!
内容概要:本文档详细介绍了基于MATLAB实现的无人机三维路径规划项目,核心算法采用蒙特卡罗树搜索(MCTS)。项目旨在解决无人机在复杂三维环境中自主路径规划的问题,通过MCTS的随机模拟与渐进式搜索机制,实现高效、智能化的路径规划。项目不仅考虑静态环境建模,还集成了障碍物检测与避障机制,确保无人机飞行的安全性和效率。文档涵盖了从环境准备、数据处理、算法设计与实现、模型训练与预测、性能评估到GUI界面设计的完整流程,并提供了详细的代码示例。此外,项目采用模块化设计,支持多无人机协同路径规划、动态环境实时路径重规划等未来改进方向。 适合人群:具备一定编程基础,特别是熟悉MATLAB和无人机技术的研发人员;从事无人机路径规划、智能导航系统开发的工程师;对MCTS算法感兴趣的算法研究人员。 使用场景及目标:①理解MCTS算法在三维路径规划中的应用;②掌握基于MATLAB的无人机路径规划项目开发全流程;③学习如何通过MCTS算法优化无人机在复杂环境中的飞行路径,提高飞行安全性和效率;④为后续多无人机协同规划、动态环境实时调整等高级应用打下基础。 其他说明:项目不仅提供了详细的理论解释和技术实现,还特别关注了实际应用中的挑战和解决方案。例如,通过多阶段优化与迭代增强机制提升路径质量,结合环境建模与障碍物感知保障路径安全,利用GPU加速推理提升计算效率等。此外,项目还强调了代码模块化与调试便利性,便于后续功能扩展和性能优化。项目未来改进方向包括引入深度强化学习辅助路径规划、扩展至多无人机协同路径规划、增强动态环境实时路径重规划能力等,展示了广阔的应用前景和发展潜力。
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