Transitioning from CNC/3D printing to robotics, the AR4MK2 was redesigned to overcome EU sourcing challenges and improve structural integrity. This build replaces imperial bearings with metric components, reduces part count through 3D-printed consolidations, and reinforces critical joints – all while maintaining full AR4 software compatibility.

This AR4-based “HandyBot” understands voice commands to autonomously pick/place tabletop objects using cutting-edge AI vision (Grounding DINO, Segment Anything) and OpenAI Whisper speech recognition. The $2300 system combines an AR4 arm, RealSense D435 camera, and custom ROS 2 pipeline for real-world object interaction.

🔗 Build it yourself: GitHub Repo
💬 Discuss the ROS driver: Community Thread

The AR4 robotic arm system received significant motion control upgrades. The core innovation involves a split-axis homing sequence that prevents potential self-collision during initialization by separating the homing process into two distinct phases.

Motion control improvements center around advanced acceleration algorithms implementing S-curve profiles, replacing the previous linear motion approach. This upgrade enables smooth transitions between waypoints while maintaining positioning accuracy. The Raspberry Pi-based control system executes these motion profiles while managing real-time position feedback.

Operational Workflow

1. System initialization with split homing sequence

2. Automatic centering procedure completion

3. Waypoint execution with dynamic speed adjustment

4. Continuous collision monitoring during operation

5. Graceful error recovery protocols

Performance Outcomes

• 72% reduction in motion-induced vibration

• 100% prevention of homing collisions

• Sub-millimeter positioning repeatability

The complete motion control solution demonstrates how firmware and control logic enhancements can significantly upgrade robotic system capabilities without mechanical modifications. Video documentation showcases the dramatic improvement in motion quality and operational safety.

Goal: Replace manual part handling with automated systems for efficiency/consistency.

Challenges: Retrofitting old drilling machine with Arduino-controlled pneumatics.

Results:

CNC machine: Reliable 15-minute cycles over 3 months.

Drilling machine: 40-second cycles with zero downtime in first week.

Long-Term Testing: Monitoring performance under 8-hour daily operation.

Curiosity, I wanted to learn the technology underlying Arm Robots. How they built, operated, and controlled. I purchased it in November and had some difficulties at customs while attempting to explain all of the components and their purposes. It took about 6 hours of official paperwork and processing. The building process was hectic, and there was no room for error because spare components are not available in Jordan. Overall, it worth the time and the effort.