What are the best ways to increase the durability of a robotic system?

Adding protective coatings to this materials can further strengthen them against wear and tear, especially in harsh enviromnents like extreme heat or cold. What people like to forget: regularly maintain and replace parts as needed (or they avoid the costs), which can greatly extend the life of the robot even when using robust materials.

Building a sturdy robot involves careful material selection. Steel is the standard choice for strength, durability, and cost. Aluminium is robust and lightweight, perfect for complex machinery. Titanium has the best strength-to-weight ratio but is pricey and hard to deal with. Polymers including technical plastics, carbon fibre composites, and bioplastics resist impact and abrasion. Metal-polymer composites combine metal strength with polymer lightness and vibration dampening. Self-healing materials could change harsh-environment robot design. Material selection relies on the robot's role, surroundings, weight, mobility, cost, and complexity.

Using easy-to-replace modules can make it quicker to fix or upgrade parts without stopping the whole robot or using a new/diferent one. Also, designing software that can detect and switch to backup systems automatically helps the robot keep working smoothly even if something goes wrong. This software often requires special training, as (at least in my opinion) is very often not self-explanatory.

Robot redundancy means having more DOF than needed for a task. Flexibility improves robots' adaptability, versatility, and strength. Consider serial, parallel, or mixed kinematics to construct a redundant robot. Operating efficiently and avoiding computational overload requires balancing redundancy and control complexity. Redundancy improves obstacle avoidance, singularity avoidance, multitasking, and fault tolerance. Other factors include sensor fusion, optimisation algorithms, and human-robot interaction. Robots can be reliable, economical, flexible, and able to handle unanticipated real-world obstacles by carefully balancing flexibility and control. This approach lets designers build durable, adaptable robots that live on redundancy.

Robot fault tolerance is essential for safety, productivity, and autonomous system confidence. Robots need hardware redundancy including many sensors and actuators, modular design, robust control algorithms, error detection and recovery, self-diagnosis and reconfiguration, predictive maintenance, human-robot collaboration, and cybersecurity to tolerate faults. These solutions keep robots running after breakdowns, reducing downtime and costs. Space probes, self-driving automobiles, and industrial robots are fault-tolerant. These robots can handle severe conditions, complex traffic, and unanticipated obstructions or system failures.

Robots need frequent maintenance to work well and avoid costly breakdowns. Regular inspections, sensor checks, software updates, proper lubrication and cleaning, data analysis and condition monitoring, predictive maintenance with AI and machine learning, spare parts and training, and operator and maintenance personnel training are key. Effective preventative maintenance can reduce robot downtime, boost productivity, lower maintenance costs, improve safety, and extend its lifespan. Implementing a robust PM programme adapted to your robots and working environment will ensure your robotic workforce runs smoothly, efficiently, and safely for years.

Incorporating sensors that monitor the robot's condition in real-time can alert users to potential issues BEFORE they become major problems. It's like maintaining your bicycle regularly vs. preparing it when it is finally broken. Training users in basic maintenance techniques can also make them independent, so they can repair small issues quickly, reducing the need for extensive repairs later. But from my experience, management often avoids these "extra costs", as it needs long-term planning - something you don't find very often nowadays.

Robots that can repair themselves to stay operational and overcome hurdles in dynamic environments are promising. Modular design, sensor-based damage detection, intrinsic or extrinsic repair, and data processing techniques are possible with these robots. Material limits, complexity, expense, and ethics are issues. Space exploration, catastrophe response, remote operations, and productivity are uses. With advances in materials science, AI and sensor technologies, and ethical regulations, self-healing robots have a bright future. Self-healing technology can revolutionise space exploration and catastrophe response by creating durable and flexible robotic systems.

Para mí manter un mantenimiento regular y actualizaciones periódicas para asegurar la durabilidad de un sistema robótico. Es como cuidar de tu robot para que esté siempre en su mejor forma.

The arrangement and motion planning of a robot significantly influence its lifespan. Strategic design can reduce motor loads during movements, thereby extending their longevity. Various simulation programs are available for modeling robot movements, analyzing loads, and predicting lifespan.