08 / Robotics / Mechanical design / Computation
Advanced Robotic Arm Systems
A five-axis mechanical design alongside analytical, neural and proposed hybrid motion studies.
01 / Context
The problem
A robotic arm needs compatible mechanical geometry, feasible joint solutions and consistent trajectory behavior before motion can be tested on hardware.
02 / Engineering
The approach
Develop the mechanical assembly, derive interpretable inverse-kinematics models, study learned mappings against analytical references, and define a hybrid evaluation method before hardware integration.
A five-degree-of-freedom SOLIDWORKS arm assembly explores links, joints and gripper integration. Related Python studies cover analytical inverse kinematics for 3-DOF and 4-DOF models and multilayer-perceptron approximations. A hybrid trajectory-tracking approach combining learned predictions, forward-kinematics checks and analytical correction remains a proposed extension; these studies remain separate from physical control integration.
03 / Toolkit
Technologies
- SOLIDWORKS
- Python
- Inverse kinematics
- MLP neural networks
- Trajectory planning
- Mechatronics
04 / Purpose
Intended contribution
Connect mechanical design with robot positioning, model comparison and future motion-control integration.
Development record
What has been established
The CAD design and analytical/neural research work were shared and discussed. Physical construction, model performance metrics, integrated control and publication status are unconfirmed. Hybrid trajectory tracking is methodology planning rather than a completed experiment.
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