Pros of Bullet3

• Widely adopted in game development and robotics simulations
• Extensive documentation and community support
• Highly optimized for performance, especially in real-time applications

Cons of Bullet3

• Less focus on accuracy compared to DART
• More complex API, steeper learning curve for beginners
• Limited built-in support for articulated rigid body dynamics

Code Comparison

DART example (inverse kinematics):

InverseKinematics* ik = new InverseKinematics(bodyNode);
ik->addTargetTranslationalConstraint(bodyNode, desiredPosition);
ik->solve();

Bullet3 example (rigid body creation):

btCollisionShape* shape = new btSphereShape(1.0);
btDefaultMotionState* motionState = new btDefaultMotionState();
btRigidBody::btRigidBodyConstructionInfo rbInfo(mass, motionState, shape);
btRigidBody* body = new btRigidBody(rbInfo);

Both DART and Bullet3 are powerful physics engines, but they cater to different needs. DART excels in accuracy and articulated body simulations, while Bullet3 shines in performance-critical applications and game development. The choice between them depends on the specific requirements of your project.

Pros of FCL

• Specialized in collision detection and distance computation
• Supports a wide range of geometric primitives and collision algorithms
• Lightweight and can be easily integrated into other projects

Cons of FCL

• Limited to collision detection and distance computation
• Lacks built-in dynamics simulation capabilities
• May require additional libraries for complete robotics simulations

Code Comparison

FCL (collision detection):

fcl::CollisionObject<double> obj1(shape1);
fcl::CollisionObject<double> obj2(shape2);
fcl::CollisionRequest<double> request;
fcl::CollisionResult<double> result;
fcl::collide(&obj1, &obj2, request, result);

DART (physics simulation):

dart::dynamics::SkeletonPtr robot = dart::dynamics::Skeleton::create("robot");
dart::simulation::WorldPtr world = dart::simulation::World::create();
world->addSkeleton(robot);
world->step();

Summary

FCL is a specialized library for collision detection and distance computation, while DART is a more comprehensive dynamics and simulation toolkit. FCL excels in its focused functionality and can be easily integrated into other projects. DART, on the other hand, provides a full-featured environment for robotics simulation, including physics, kinematics, and collision detection. The choice between the two depends on the specific requirements of your project and whether you need a complete simulation framework or just collision detection capabilities.

Pros of Drake

• More comprehensive toolset for robotics simulation and control
• Stronger integration with optimization and planning algorithms
• Better support for multi-body dynamics and contact mechanics

Cons of Drake

• Steeper learning curve due to its complexity
• Heavier computational requirements for some simulations
• Less flexible for real-time applications compared to DART

Code Comparison

Drake example (Python):

import pydrake.all as drake

builder = drake.systems.DiagramBuilder()
plant, scene_graph = drake.multibody.plant.AddMultibodyPlantSceneGraph(builder, time_step=0.0)
parser = drake.multibody.parsing.Parser(plant)
parser.AddModelFromFile("model.urdf")
plant.Finalize()

DART example (C++):

#include <dart/dart.hpp>

auto world = std::make_shared<dart::simulation::World>();
auto skeleton = dart::dynamics::Skeleton::create("robot");
dart::utils::DartLoader loader;
skeleton = loader.parseSkeleton("model.urdf");
world->addSkeleton(skeleton);

Both libraries provide powerful tools for robotics simulation, but Drake offers a more comprehensive ecosystem for advanced robotics applications, while DART focuses on real-time performance and flexibility. Drake's integration with optimization tools makes it suitable for complex planning tasks, whereas DART's lightweight design allows for faster simulations in certain scenarios.