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Robot Hardware & Components
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Robot Types & Platforms
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- From Sensors to Intelligence: How Robots See and Feel
- Robot Sensors: Types, Roles, and Integration
- Mobile Robot Sensors and Their Calibration
- Force-Torque Sensors in Robotic Manipulation
- Designing Tactile Sensing for Grippers
- Encoders & Position Sensing for Precision Robotics
- Tactile and Force-Torque Sensing: Getting Reliable Contacts
- Choosing the Right Sensor Suite for Your Robot
- Tactile Sensors: Giving Robots the Sense of Touch
- Sensor Calibration Pipelines for Accurate Perception
- Camera and LiDAR Fusion for Robust Perception
- IMU Integration and Drift Compensation in Robots
- Force and Torque Sensing for Dexterous Manipulation
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AI & Machine Learning
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- Understanding Computer Vision in Robotics
- Computer Vision Sensors in Modern Robotics
- How Computer Vision Powers Modern Robots
- Object Detection Techniques for Robotics
- 3D Vision Applications in Industrial Robots
- 3D Vision: From Depth Cameras to Neural Reconstruction
- Visual Tracking in Dynamic Environments
- Segmentation in Computer Vision for Robots
- Visual Tracking in Dynamic Environments
- Segmentation in Computer Vision for Robots
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- Perception Systems: How Robots See the World
- Perception Systems in Autonomous Robots
- Localization Algorithms: Giving Robots a Sense of Place
- Sensor Fusion in Modern Robotics
- Sensor Fusion: Combining Vision, LIDAR, and IMU
- SLAM: How Robots Build Maps
- Multimodal Perception Stacks
- SLAM Beyond Basics: Loop Closure and Relocalization
- Localization in GNSS-Denied Environments
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Knowledge Representation & Cognition
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- Introduction to Knowledge Graphs for Robots
- Building and Using Knowledge Graphs in Robotics
- Knowledge Representation: Ontologies for Robots
- Using Knowledge Graphs for Industrial Process Control
- Ontology Design for Robot Cognition
- Knowledge Graph Databases: Neo4j for Robotics
- Using Knowledge Graphs for Industrial Process Control
- Ontology Design for Robot Cognition
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Robot Programming & Software
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- Robot Actuators and Motors 101
- Selecting Motors and Gearboxes for Robots
- Actuators: Harmonic Drives, Cycloidal, Direct Drive
- Motor Sizing for Robots: From Requirements to Selection
- BLDC Control in Practice: FOC, Hall vs Encoder, Tuning
- Harmonic vs Cycloidal vs Direct Drive: Choosing Actuators
- Understanding Servo and Stepper Motors in Robotics
- Hydraulic and Pneumatic Actuation in Heavy Robots
- Thermal Modeling and Cooling Strategies for High-Torque Actuators
- Inside Servo Motor Control: Encoders, Drivers, and Feedback Loops
- Stepper Motors: Simplicity and Precision in Motion
- Hydraulic and Electric Actuators: Trade-offs in Robotic Design
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- Power Systems in Mobile Robots
- Robot Power Systems and Energy Management
- Designing Energy-Efficient Robots
- Energy Management: Battery Choices for Mobile Robots
- Battery Technologies for Mobile Robots
- Battery Chemistries for Mobile Robots: LFP, NMC, LCO, Li-ion Alternatives
- BMS for Robotics: Protection, SOX Estimation, Telemetry
- Fast Charging and Swapping for Robot Fleets
- Power Budgeting & Distribution in Robots
- Designing Efficient Power Systems for Mobile Robots
- Energy Recovery and Regenerative Braking in Robotics
- Designing Safe Power Isolation and Emergency Cutoff Systems
- Battery Management and Thermal Safety in Robotics
- Power Distribution Architectures for Multi-Module Robots
- Wireless and Contactless Charging for Autonomous Robots
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- Mechanical Components of Robotic Arms
- Mechanical Design of Robot Joints and Frames
- Soft Robotics: Materials and Actuation
- Robot Joints, Materials, and Longevity
- Soft Robotics: Materials and Actuation
- Mechanical Design: Lightweight vs Stiffness
- Thermal Management for Compact Robots
- Environmental Protection: IP Ratings, Sealing, and EMC/EMI
- Wiring Harnesses & Connectors for Robots
- Lightweight Structural Materials in Robot Design
- Joint and Linkage Design for Precision Motion
- Structural Vibration Damping in Lightweight Robots
- Lightweight Alloys and Composites for Robot Frames
- Joint Design and Bearing Selection for High Precision
- Modular Robot Structures: Designing for Scalability and Repairability
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- End Effectors: The Hands of Robots
- End Effectors: Choosing the Right Tool
- End Effectors: Designing Robot Hands and Tools
- Robot Grippers: Design and Selection
- End Effectors for Logistics and E-commerce
- End Effectors and Tool Changers: Designing for Quick Re-Tooling
- Designing Custom End Effectors for Complex Tasks
- Tool Changers and Quick-Swap Systems for Robotics
- Soft Grippers: Safe Interaction for Fragile Objects
- Vacuum and Magnetic End Effectors: Industrial Applications
- Adaptive Grippers and AI-Controlled Manipulation
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- Robot Computing Hardware
- Cloud Robotics and Edge Computing
- Computing Hardware for Edge AI Robots
- AI Hardware Acceleration for Robotics
- Embedded GPUs for Edge Robotics
- Edge AI Deployment: Quantization and Pruning
- Embedded Computing Boards for Robotics
- Ruggedizing Compute for the Edge: GPUs, IPCs, SBCs
- Time-Sensitive Networking (TSN) and Deterministic Ethernet
- Embedded Computing for Real-Time Robotics
- Edge AI Hardware: GPUs, FPGAs, and NPUs
- FPGA-Based Real-Time Vision Processing for Robots
- Real-Time Computing on Edge Devices for Robotics
- GPU Acceleration in Robotics Vision and Simulation
- FPGA Acceleration for Low-Latency Control Loops
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Control Systems & Algorithms
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- Introduction to Control Systems in Robotics
- Motion Control Explained: How Robots Move Precisely
- Motion Planning in Autonomous Vehicles
- Understanding Model Predictive Control (MPC)
- Adaptive Control Systems in Robotics
- PID Tuning Techniques for Robotics
- Robot Control Using Reinforcement Learning
- PID Tuning Techniques for Robotics
- Robot Control Using Reinforcement Learning
- Model-Based vs Model-Free Control in Practice
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- Real-Time Systems in Robotics
- Real-Time Systems in Robotics
- Real-Time Scheduling for Embedded Robotics
- Time Synchronization Across Multi-Sensor Systems
- Latency Optimization in Robot Communication
- Real-Time Scheduling in Robotic Systems
- Real-Time Scheduling for Embedded Robotics
- Time Synchronization Across Multi-Sensor Systems
- Latency Optimization in Robot Communication
- Safety-Critical Control and Verification
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Simulation & Digital Twins
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- Simulation Tools for Robotics Development
- Simulation Platforms for Robot Training
- Simulation Tools for Learning Robotics
- Hands-On Guide: Simulating a Robot in Isaac Sim
- Simulation in Robot Learning: Practical Examples
- Robot Simulation: Isaac Sim vs Webots vs Gazebo
- Hands-On Guide: Simulating a Robot in Isaac Sim
- Gazebo vs Webots vs Isaac Sim
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Industry Applications & Use Cases
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- Service Robots in Daily Life
- Service Robots: Hospitality and Food Industry
- Hospital Delivery Robots and Workflow Automation
- Robotics in Retail and Hospitality
- Cleaning Robots for Public Spaces
- Robotics in Education: Teaching the Next Generation
- Service Robots for Elderly Care: Benefits and Challenges
- Robotics in Retail and Hospitality
- Robotics in Education: Teaching the Next Generation
- Service Robots in Restaurants and Hotels
- Retail Shelf-Scanning Robots: Tech Stack
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Safety & Standards
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Cybersecurity for Robotics
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Ethics & Responsible AI
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Careers & Professional Development
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- How to Build a Strong Robotics Portfolio
- Hiring and Recruitment Best Practices in Robotics
- Portfolio Building for Robotics Engineers
- Building a Robotics Career Portfolio: Real Projects that Stand Out
- How to Prepare for a Robotics Job Interview
- Building a Robotics Resume that Gets Noticed
- Hiring for New Robotics Roles: Best Practices
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Research & Innovation
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Companies & Ecosystem
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- Funding Your Robotics Startup
- Funding & Investment in Robotics Startups
- How to Apply for EU Robotics Grants
- Robotics Accelerators and Incubators in Europe
- Funding Your Robotics Project: Grant Strategies
- Venture Capital for Robotic Startups: What to Expect
- Robotics Accelerators and Incubators in Europe
- VC Investment Landscape in Humanoid Robotics
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Technical Documentation & Resources
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- Sim-to-Real Transfer Challenges
- Sim-to-Real Transfer: Closing the Reality Gap
- Simulation to Reality: Overcoming the Reality Gap
- Simulated Environments for RL Training
- Hybrid Learning: Combining Simulation and Real-World Data
- Sim-to-Real Transfer: Closing the Gap
- Simulated Environments for RL Training
- Hybrid Learning: Combining Simulation and Real-World Data
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- Simulation & Digital Twin: Scenario Testing for Robots
- Digital Twin Validation and Performance Metrics
- Testing Autonomous Robots in Virtual Scenarios
- How to Benchmark Robotics Algorithms
- Testing Robot Safety Features in Simulation
- Testing Autonomous Robots in Virtual Scenarios
- How to Benchmark Robotics Algorithms
- Testing Robot Safety Features in Simulation
- Digital Twin KPIs and Dashboards
Designing Efficient Power Systems for Mobile Robots
Designing an efficient power system is the hidden art that brings mobile robots to life. Whether you’re building a delivery rover, an industrial AGV, or an agile research bot, the heartbeat of your creation is the power system. As a robotics engineer, I see this challenge as more than just picking a battery — it’s about orchestrating energy flow, reliability, and intelligence into every movement. Let’s dive into the essentials of power system design for mobile robots and uncover how a well-engineered backbone transforms robotic potential into real-world functionality.
Battery Selection: The Core of Robotic Mobility
The choice of battery shapes almost every aspect of your robot’s performance — range, payload, safety, and even business viability. Today, lithium-ion (Li-ion) and lithium-polymer (LiPo) batteries dominate the field, thanks to their high energy density and rechargeability. But there are nuances to consider:
- Energy Density: For lightweight drones or autonomous vehicles, maximizing watt-hours per kilogram is crucial. High energy density means longer missions or smaller, lighter robots.
- Current Delivery: Motors often demand bursts of high current. LiPo batteries excel here, but require careful handling and charging protocols.
- Cycle Life: If your robot operates continuously (think warehouse logistics), opt for chemistries with higher cycle life, like LiFePO4 or advanced Li-ion cells.
- Safety and Form Factor: In medical or educational robots, the physical shape, built-in protection, and non-toxicity may be critical.
Real-world example: Boston Dynamics’ Spot robot uses high-capacity, hot-swappable batteries, enabling extended missions and minimal downtime—a vital edge in field robotics.
Battery Sizing: The Practical Formula
Start with a clear profile of your robot’s power consumption: Sum up the peak and average current for all subsystems — motors, controllers, sensors, and compute units. Then, apply a safety margin (often 20–30%) to account for unforeseen loads or battery aging.
“The best battery is one you never have to think about—until it’s time to swap or recharge.”
Power Distribution: The Nervous System
Efficient power distribution is about delivering the right voltage and current to every component, minimizing losses, and ensuring robust operation. Modern robots employ a mix of power buses (e.g., 24V, 12V, 5V) and localized regulators. Key principles include:
- Segmentation: Isolate high-power circuits (motors, actuators) from sensitive electronics (sensors, compute) to prevent interference.
- Wiring and Connectors: Use appropriately rated cables and secure connectors; poor connections are a leading cause of intermittent faults.
- Redundancy: For mission-critical robots, dual power paths or backup batteries can be lifesavers.
Consider a typical AGV: Separate fuses for motor drivers and logic boards, plus power rails with different voltage levels, ensure both safety and modularity.
Converters and Regulators: Delivering the Right Energy
Most robotic platforms need to convert battery voltage (often 12V–24V) down to 5V or 3.3V for electronics — or up for specific actuators. The choice between linear regulators and switching regulators (DC-DC converters) is crucial:
| Feature | Linear Regulator | Switching Regulator (DC-DC) |
|---|---|---|
| Efficiency | Low (dissipates heat) | High (90%+ possible) |
| Size/Weight | Simple, compact | May need external components |
| Noise | Very low | Can introduce ripple |
| Use-case | Low-power, sensitive circuits | Main power rails |
Expert tip: Critical sensors and microcontrollers often need ultra-clean power — use linear regulators or low-noise DC-DC converters, and always decouple supply lines with capacitors.
Protection Circuits: Guarding Against the Unexpected
No robot should venture out without robust protection. Short circuits, overcurrent, reverse polarity, and voltage spikes can spell disaster for hardware — and budgets. Modern protection strategies include:
- Fuses and PTCs: Simple, inexpensive, and effective for preventing catastrophic failures.
- TVS Diodes and Transient Protection: Absorb voltage spikes from motors or hostile environments.
- Battery Management Systems (BMS): For lithium batteries, a quality BMS is non-negotiable — it prevents overcharging, deep discharge, and cell imbalance.
- Reverse Polarity Protection: Simple diode or MOSFET circuits can save you from costly mistakes during maintenance or upgrades.
“Every hour spent on protection saves ten on repairs.”
Monitoring Tools: Intelligence for Maintenance and Performance
Gone are the days of flying blind. Today’s mobile robots integrate advanced power monitoring — live current, voltage, and state-of-charge feedback, often with cloud reporting. This data enables predictive maintenance, smart charging, and even dynamic mission planning.
- Smart BMS and Telemetry: Surface actionable battery data to your control system or operator dashboard.
- Remote Diagnostics: Analyze power anomalies before they become field failures.
- Logging and Analytics: Use historical data to optimize routes, charging cycles, and hardware upgrades.
Case in point: Warehouse robots at Amazon constantly report battery health, allowing the fleet controller to schedule recharging and avoid downtime.
Modern Approaches and Templates: Accelerating Reliable Development
Why reinvent the wheel? Leveraging proven power system templates and modular architectures accelerates development, reduces risk, and ensures compliance. Open-source hardware designs, reference schematics, and simulation tools (like LTspice or MATLAB Simulink) are invaluable for both prototyping and scaling up.
For startups and research teams, structured design patterns — such as modular battery packs, plug-and-play power rails, and integrated monitoring boards — enable rapid iteration without sacrificing reliability.
Common Pitfalls and How to Avoid Them
- Underestimating Peak Loads: Always measure real-world current spikes during mission-critical maneuvers.
- Neglecting Thermal Management: Power electronics generate heat; ensure adequate cooling or derating.
- Poor Documentation: Thorough wiring diagrams and labeling are essential for debugging and upgrades.
“A great robot not only moves itself — it tells you how it’s feeling, what it needs, and when it needs a recharge.”
Designing an efficient power system is both art and science. With modern knowledge, robust components, and structured development patterns, your robots can achieve new levels of performance, reliability, and intelligence. And if you’re looking to accelerate your own journey in AI and robotics, partenit.io offers ready-to-use templates and expert insights to get your projects up and running, fast.
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