{"product_id":"simulating-robots-with-pybullet-elenaor-sloane-9798189509674","title":"Simulating Robots with PyBullet: Test your drone flight code and robot physics safely on your computer screen using Python","description":"\u003cb\u003eBuild, Control, and Test Virtual Robots Before Risking Real Hardware\u003c\/b\u003e\u003cp\u003eA robot may look stable on a computer screen while quietly exceeding a joint limit, applying unrealistic forces, drifting away from its target, touching an obstacle, or landing too quickly.\u003c\/p\u003e\u003cp\u003eUseful simulation requires more than attractive animation. You must define what the experiment is supposed to prove, use appropriate physical parameters, measure the robot's state, record the results, and compare its behaviour with clear pass-and-failure criteria.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eSimulating Robots with PyBullet\u003c\/b\u003e provides a practical introduction to testing robot movement, drone-control logic, collisions, sensors, cameras, feedback controllers, and complete missions with Python.\u003c\/p\u003e\u003cp\u003eWritten for beginners with basic Python knowledge and intermediate programmers entering robotics simulation, the book uses PyBullet to create controlled virtual environments for wheeled robots, articulated arms, and a simplified quadrotor. Every core exercise runs on a computer, so no physical robot, electronics construction, advanced calculus, or ROS installation is required.\u003c\/p\u003e\u003cp\u003eInside this project-based guide, you will learn how to: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUnderstand what physics simulation can and cannot prove\u003c\/li\u003e\n\u003cli\u003eDistinguish simulation from animation and data visualisation\u003c\/li\u003e\n\u003cli\u003eDefine a clear experimental question before building a virtual world\u003c\/li\u003e\n\u003cli\u003eRecord assumptions, variables, measurements, and acceptance limits\u003c\/li\u003e\n\u003cli\u003eCreate repeatable experiments with controlled starting conditions\u003c\/li\u003e\n\u003cli\u003eInstall Python, PyBullet, NumPy, Matplotlib, and testing tools\u003c\/li\u003e\n\u003cli\u003eUse isolated virtual environments and reproducible dependency files\u003c\/li\u003e\n\u003cli\u003eWork in graphical and headless execution modes\u003c\/li\u003e\n\u003cli\u003eConnect to and disconnect from the PyBullet physics server safely\u003c\/li\u003e\n\u003cli\u003eConfigure gravity, time steps, asset paths, and simulation state\u003c\/li\u003e\n\u003cli\u003eLoad static and dynamic rigid bodies\u003c\/li\u003e\n\u003cli\u003eRead position, orientation, linear velocity, and angular velocity\u003c\/li\u003e\n\u003cli\u003eDetect ground contact and record numerical results\u003c\/li\u003e\n\u003cli\u003eUse consistent SI units throughout a simulation\u003c\/li\u003e\n\u003cli\u003eConfigure mass, inertia, centre of mass, friction, restitution, and damping\u003c\/li\u003e\n\u003cli\u003eSelect stable physics and controller update rates\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThe book maintains a clear boundary between virtual evidence and real-world safety. It explains that simulation cannot guarantee exact motor performance, sensor behaviour, battery condition, manufacturing quality, or aerodynamic accuracy. Any transfer to physical hardware must repeat checks for motor direction, sensor axes, controller gains, stopping distance, timeouts, emergency shutdown, hover thrust, and landing behaviour.\u003c\/p\u003e\u003cp\u003eSupporting resources include an installation and compatibility checklist, version-verification record, coordinate-frame reference, SI-unit table, quaternion conventions, wheel-speed and differential-drive formulas, hover-thrust calculations, PID equations, time-step relationships, and a robotics glossary.\u003c\/p\u003e\u003cp\u003eWhether you are a Python learner, robotics student, educator, drone developer, hobbyist, control-systems beginner, or programmer preparing algorithms for later hardware testing, this guide will help you turn a moving virtual model into a measurable engineering experiment.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDefine the question. Build only the model required. Measure every result. Automate the acceptance test. Treat a passing simulation as evidence-not proof of hardware safety.\u003c\/b\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Elenaor Sloane\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9798189509674\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 07\/28\/2026\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 220\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.60lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.00h x 6.00w x 0.55d","brand":"Elenaor Sloane","offers":[{"title":"Paperback","offer_id":50666020372735,"sku":"9798189509674","price":18.99,"currency_code":"USD","in_stock":true}],"url":"https:\/\/www.whiterainbookhouse.com\/products\/simulating-robots-with-pybullet-elenaor-sloane-9798189509674","provider":"WR Book House","version":"1.0","type":"link"}