10x improvement in pose reaching accuracy

Changes in Default Behavior

• Acceleration and Jerk in Output trajectory from motion_gen is not filtered. Previously, this was
  filtered with a sliding window to remove aliasing artifacts. To get previous behavior, set
  filter_robot_command=True in MotionGenConfig.load_from_robot_config().
• Terminal action for motion planning is now fixed from initial seed. This improves accuracy (10x).
  To get previous behavior, set trajopt_fix_terminal_action=True and also
  trajopt_js_fix_terminal_action=True in MotionGenConfig.load_from_robot_config().
• Introduce higher accuracy weights for IK in gradient_ik_autotune.yml. To use old file,
  pass gradient_ik_file='gradient_ik.yml' in MotionGenConfig.load_from_robot_config(). Similarly
  for IKSolver, pass gradient_file='gradient_ik.yml' in IKSolverConfig.load_from_robot_config().

New Features

• Add fix terminal action in quasi-netwon solvers. This keeps the final action constant (from
  initial seed) and only optimizing for the remaining states. Improved accuracy in
  reaching targets (10x improvement for Cartesian pose targets and exact reaching for joint position
  targets).

BugFixes & Misc.

• Fix bug (opposite sign) in gradient calculation for jerk. Trajectory optimizaiton generates
  shorter motion time trajectories.
• Fix numerical precision issues when calculating linear interpolated seeds by copying terminal
  state to final action of trajectory after interpolation.

Add grasp planning API

Changes in Default Behavior

• Remove explicit global seed setting for numpy and random. To enforce deterministic behavior,
  use np.random.seed(2) and random.seed(2) in your program.
• geom.types.VoxelGrid now uses a different algorithm to calculate number of voxels per dimension
  and also to compute xyz locations in a grid. This new implementation matches implementation in
  nvblox.

New Features

• Add pose cost metric to MPC to allow for partial pose reaching.
• Update obstacle poses in cpu reference with an optional flag.
• Add planning to grasp API in MotionGen.plan_grasp that plans a sequence of motions to grasp
  an object given grasp poses. This API also provides args to disable collisions during the grasping
  phase.
• Constrained planning can now use either goal frame or base frame at runtime.

BugFixes & Misc.

• Fixed optimize_dt not being correctly set when motion gen is called in reactive mode.
• Add documentation for geom module.
• Add descriptive api for computing kinematics.
• Fix cv2 import order in isaac sim realsense examples.
• Fix attach sphere api mismatch in TrajOptSolver.
• Fix bug in get_spline_interpolated_trajectory where
  numpy array was created instead of torch tensor.
• Fix gradient bug when sphere origin is exactly at face of a cuboid.
• Add support for parsing Yaml 1.2 format with an updated regex for scientific notations.
• Move to yaml SafeLoader from Loader.
• Graph search checks if a node exists before attempting to find a path.
• Fix steps_max becoming 0 when optimized dt has NaN values.
• Clone MotionGenPlanConfig instance for every plan api.
• Improve sphere position to voxel location calculation to match nvblox's implementation.
• Add self collision checking support for spheres > 1024 and number of checks > 512 * 1024.
• Fix gradient passthrough in warp batch transform kernels.
• Remove torch.Size() initialization with device kwarg.

Isaac Sim 4.0 support, CUDA Graph improvements, minor bug fixes

New Features

• Interpolated metrics calculation now recreates cuda graph if interpolation steps exceed existing buffer size.
• Add experimental CUDAGraph.reset usage as cuda>=12.0 is not crashing when an existing captured CUDAGraph is freed and recaptured with new memory pointers. Try this experimental feature by
  setting an environment variable export CUROBO_TORCH_CUDA_GRAPH_RESET=1. This feature will allow for changing the problem type in motion_gen and ik_solver without requiring recreation of the class.
• Add partial support for Windows.
• Add Isaac Sim 4.0.0 docker support.
• Examples now work with Isaac Sim 4.0.0.
• Add XRDF support.
• Add curobo.types.file_path.ContentPath to store paths for files representing robot and world. This
  improves development on top of cuRobo with custom robots living external of cuRobo library.
• Add attach external objects to robot link API to CudaRobotModel.
• Add MotionGenStatus.DT_EXCEPTION to report failures due to trajectory exceeding user specified
  maximum trajectory dt.
• Add reading of end-effector mesh if available when rendering trajectory with UsdHelper, also
  supports goalset rendering.
• Kinematics module (curobo.cuda_robot_model) has complete API documentation.

Changes in Default Behavior

• Cuda graph capture of optimization iterations resets solver before recording.
• join_path(a, b) now requires a to not have a trailing slash to make the file compatible with Windows.
• Drop examples support for Isaac Sim < 4.0.0.
• asset_root_path can be either empty string or None.
• Order of variables in SelfCollisionKinematicsConfig has changed. Unused variables
  moved to bottom.
• Remove requirement of warmup for using offset_waypoint in PoseCost.

BugFixes & Misc.

• Minor documentation fixes to install instructions.
• Add support for older warp versions (<1.0.0) as it's not possible to run older isaac sim with newer warp versions.
• Add override option to mpc dataclass.
• Fix bug in PoseCost.forward_pose() which caused torch_layers_example.py to fail.
• Add warp constants to make module hash depend on robot dof, for modules that generate runtime
  warp kernels. This fixes issues using cuRobo in isaac sim.
• Add plan_config.timeout check to plan_single_js().
• Recreation of interpolation buffer now copies the joint names from raw trajectory.
• Fix bug in running captured cuda graph on deleted memory pointers
  when getting metrics on interpolated trajectory
• Change order of operations in cuda graph capture of particle opt to get correct results
  during graph capture phase.
• Franka Panda now works in Isaac Sim 4.0.0. The fix was to add inertial parameters to all links in
  the urdf.
• Create new instances of rollouts in wrap classes to ensure cuda graph rollouts are not
  accidentally used in other pipelines.
• Add cuda graph check for get_metrics.
• Remove aligned address assumption for float arrays inside kernel (local memory).
• Add check for existing warp kernel in a module before creating a new one to avoid corruption of
  existing cuda graphs.

Improved joint space planning and planning start validity check

New Features

• Add start state checks for world collision, self-collision, and joint limits.
• Add finetune with dt scaling for motion_gen.plan_single_js to get more time optimal
  trajectories in joint space planning.
• Improve joint space planning convergence, now succeeds in more planning problems with higher
  accuracy.

Changes in default behavior

• Some warp kernels are now compiled based on runtime parameters (dof), causing a slowdown in load
  time for motion_gen. To avoid this slowdown, add an environment variable CUROBO_USE_LRU_CACHE=1
  which will cache the runtime generated kernels.

BugFixes & Misc.

• Fix bug in evaluator to account for dof maximum acceleration and jerk.
• Add unit test for different acceleration and jerk limits.
• Add a check in self-collision kernels to avoid computing over inactive threads.
• Add link_poses as an additional property to kinematics to be more descriptive.
• Add g_dim check for int in batched planning.
• Add link_poses for motion_gen.warmup() in batch planning mode.
• Add link_poses as input to batch_goalset.
• Add finetune js trajopt solver.
• Pass raw velocity, acceleration, and jerk values to dt computation function to prevent
  interpolation errors from causing out of joint limit failures
• Add finetune_js_dt_scale with a default value > 1.0 as joint space trajectories are
  time optimal in sparse obstacle environments.
• Add note on deterministic behavior to website. Use lbfgs history < 12 for deterministic
  optimization results.
• Add warning when adding a mesh with the same name as in existing cache.
• Remove warmup for batch motion gen reacher isaac sim example.
• Fix python examples in getting started webpage.
• Refactor warp mesh query kernels to use a wp.func for signed distance queries.

Re-timing post-processing improves motion generation quality at slow speeds, API documentation

New Features

• Significant improvements for generating slow trajectories. Added re-timing post processing to
  slow down optimized trajectories. Use MotionGenPlanConfig.time_dilation_factor<1.0 to slow down a
  planned trajectory. This is more robust than setting velocity_scale<1.0 and also allows for
  changing the speed of trajectories between planning calls
• curobo.util.logger adds logger_name as an input, enabling use of logging api with other
  packages.

Changes in default behavior

• Move CudaRobotModelState from curobo.cuda_robot_model.types to
  curobo.cuda_robot_model.cuda_robot_model
• Activation distance for bound cost in now a ratio instead of absolute value to account for very
  small range of joint limits when velocity_scale<0.1.
• TrajResult is renamed to TrajOptResult to be consistent with other solvers.
• Order of inputs to get_batch_interpolated_trajectory has changed.
• MpcSolverConfig.load_from_robot_config uses world_model instead of world_cfg to be
  consistent with other wrappers.

BugFixes & Misc.

• Fix bug in MotionGen.plan_batch_env where graph planner was being set to True. This also fixes
  isaac sim example batch_motion_gen_reacher.py.
• Add min_dt as a parameter to MotionGenConfig and TrajOptSolverConfig to improve readability
  and allow for having smaller interpolation_dt.
• Add epsilon to min_dt to make sure after time scaling, joint temporal values are not exactly
  at their limits.
• Remove 0.02 offset for max_joint_vel and max_joint_acc in TrajOptSolver
• Bound cost now scales the cost by 1/limit_range**2 when limit_range<1.0 to be robust to small
  joint limits.
• Added documentation for curobo.util.logger, curobo.wrap.reacher.motion_gen,
  curobo.wrap.reacher.mpc, and curobo.wrap.reacher.trajopt.
• When interpolation buffer is smaller than required, a new buffer is created with a warning
  instead of raising an exception.
• torch.cuda.synchronize() now only synchronizes specified cuda device with
  torch.cuda.synchronize(device=self.tensor_args.device)
• Added python example for MPC.

Improved motion quality, precision, and better joint space planning.

New Features

• Add mimic joint parsing and optimization support. Check ur5e_robotiq_2f_140.yml.
• Add finetune_dt_scale as a parameter to MotionGenPlanConfig to dynamically change the
  time-optimal scaling on a per problem instance.
• MotionGen.plan_single() will now try finetuning in a for-loop, with larger and larger dt
  until convergence. This also warm starts from previous failure.
• Add high_precision mode to MotionGenConfig to support <1mm convergence.

Changes in default behavior

• collision_sphere_buffer now supports having offset per link. Also, collision_sphere_buffer only
  applies to world collision while self_collision_buffer applies for self collision. Previously,
  self_collision_buffer was added on top of collision_sphere_buffer.
• TrajEvaluatorConfig cannot be initialized without dof as now per-joint jerk and acceleration
  limits are used. Use TrajEvaluatorConfig.from_basic() to initialize similar to previous behavior.
• finetune_dt_scale default value is 0.9 from 0.95.

BugFixes & Misc.

• Fix bug in WorldVoxelCollision where env_query_idx was being overwritten.
• Fix bug in WorldVoxelCollision where parent collision types were not getting called in some cases.
• Change voxelization dimensions to include 1 extra voxel per dim.
• Added seed parameter to IKSolverConfig.
• Added sampler_seed parameter RolloutConfig.
• Fixed bug in links_goal_pose where tensor could be non contiguous.
• Improved ik_solver success by removing gaussian projection of seed samples.
• Added flag to sample from ik seeder instead of rollout_fn sampler.
• Added ik startup profiler to benchmark/curobo_python_profile.py.
• Reduced branching in Kinematics kernels and added mimic joint computations.
• Add init_cache to WorldVoxelCollision to create cache for Mesh and Cuboid obstacles.
• TrajEvaluator now uses per-joint acceleration and jerk limits.
• Fixed regression in batch_motion_gen_reacher.py example where robot's position was not being
  set correctly.
• Switched from smooth l2 to l2 for BoundCost as that gives better convergence.
• requires_grad is explicitly stored in a varaible before tensor.detach() in warp kernel calls
  as this can get set to False in some instances.
• Fix dt update in MotionGen.plan_single_js() where dt was not reset after finetunestep, causing
  joint space planner to fail often.
• Improve joint space planner success by changing smooth l2 distance cost to l2 distance. Also,
  added fallback to graph planner when linear path is not possible.
• Retuned weigths for IKSolver, now 98th percentile accuracy is 10 micrometers wtih 16 seeds
  (vs 24 seeds previously).
• Switch float8 precision check from const to macro to avoid compile errors in older nvcc, this
  fixes docker build issues for isaac sim 2023.1.0.

v0.7.0 with improved collision gradients, ESDF Voxel grid, Constrained Planning, Isaac sim 2023.1.1 support

New Features

• Add function to disable and enable collision for specific links in KinematicsTensorConfig.
• Add goal index to reacher results to return index of goal reached when goalset planning.
• Add locked joint state update api in MotionGen class.
• Add goalset warmup padding to handle varied number of goals during goalset planning and also when
  calling plan_single after warmup of goalset.
• Add new trajopt config to allow for smooth solutions at slow speeds (velocity_scale<=0.25). Also
  add error when velocity_scale<0.1.
• Add experimental robot image segmentation module to enable robot removal in depth images.
• Add constrained planning mode to motion_gen.
• Use torch.compile to leverage better kernel fusion in place of torch.jit.script.
• Significantly improved collision computation for cuboids and meshes. Mesh collision checker is
  now only 2x slower than cuboid (from 5x slower). Optimization convergence is also improved.
• LBFGS kernels now support history <= 31 from history <= 15.
• 2x faster LBFGS kernel that allocates upto 68kb of shared memory, preventing use in CUDA devices
  with compute capability <7.0.
• On benchmarking Dataset, Planning time is now 42ms on average from 50ms. Higher quality solutions
  are also obtained. See benchmarks for more details.
• Add WorldCollisionVoxel, a new collision checking implementation that uses a voxel grid
  of signed distances (SDF) to compute collision avoidance metrics. Documentation coming soon, see
  benchmark/curobo_voxel_benchmark.py for an example.
• Add API for ESDF computation from world representations, see
  WorldCollision.get_esdf_in_bounding_box().
• Add partial support for isaac sim 2023.1.1. Most examples run for UR robots. Franka Panda is
  unstable.

Changes in default behavior

• Increased default collision cache to 50 in RobotWorld.
• Changed CSpaceConfig.position_limit_clip default to 0 as previous default of 0.01 can make
  default start state in examples be out of bounds.
• MotionGen uses parallel_finetune by default. To get previous motion gen behavior, pass
  warmup(parallel_finetune=False) and MotionGenPlanConfig(parallel_finetune=False).
• MotionGen loads Mesh Collision checker instead of Primitive by default.
• UR10e and UR5e now don't have a collision sphere at tool frame for world collision checking. This
  sphere is only active for self collision avoidance.
• With torch>=2.0, cuRobo will use torch.compile instead of torch.jit.script to generate fused
  kernels. This can take several seconds during the first run. To enable this feature, set
  environment variable export CUROBO_TORCH_COMPILE_DISABLE=0.

Breaking Changes

• Renamed copy_if_not_none to clone_if_not_none to be more descriptive. Now copy_if_not_none
  will try to copy data into reference.
• Renamed n_envs in curobo.opt module to avoid confusion between parallel environments and
  parallel problems in optimization.
• Added more inputs to pose distance kernels. Check curobolib/geom.py.
• Pose cost run_vec_weight should now be [0,0,0,0,0,0] instead of [1,1,1,1,1,1]
• max_distance is now tensor from float and is an input to collision kernels.
• Order of inputs to SweptSdfMeshWarpPy has changed.

BugFixes & Misc.

• refactored wp.index() instances to [] to avoid errors in future releases of warp.
• Fix bug in gaussian transformation to ensure values are not -1 or +1.
• Fix bug in ik_solver loading ee_link_name from argument.
• Fix bug in batch_goalset planning, where pose cost was selected as GOALSET instead of
  BATCH_GOALSET.
• Added package data to also export .so files.
• Fixed bug in transforming link visual mesh offset when reading from urdf.
• Fixed bug in MotionGenPlanConfig.clone() that didn't clone the state of parallel_finetune.
• Increased weighting from 1.0 to 10.0 for optimized_dt in TrajEvaluator to select shorter
  trajectories.
• Improved determinism by setting global seed for random in graph_nx.py.
• Added option to clear obstacles in WorldPrimitiveCollision.
• Raise error when reference of tensors change in MotionGen, IKSolver, and TrajOpt when cuda graph
  is enabled.
• plan_single will get converted to plan_goalset when a plan_goalset was used to initialize cuda
  graph.
• plan_goalset will pad for extra goals when called with less number of goal than initial creation.
• Improved API documentation for Optimizer class.
• Set use_cuda_graph to True as default from None in MotionGenConfig.load_from_robot_config
• Add batched mode to robot image segmentation, supports single robot multiple camera and batch
  robot batch camera.
• Add log_warn import to arm_reacher.py
• Remove negative radius check in self collision kernel to allow for self collision checking with
  spheres of negative radius.
• Added conftest.py to disable torch.compile for tests.
• Added UR5e robot with robotiq gripper (2f-140) with improved sphere model.
• Fix bug in aarch64.dockerfile where curobo was cloned to wrong path.
• Fix bug in aarch64.dockerfile where python was used instead of python3.
• Remove unused variables in kernels.
• Added pybind11 as a dependency as some pytorch dockers for Jetson do not have this installed.
• Fix incorrect dimensions in MotionGenResult.success in MotionGen.plan_batch() when
  trajectory optimization fails.
• Added unit tests for collision checking functions.
• Fix bug in linear interpolation which was not reading the new optimized_dt to interpolate
  velocity, acceleration, and jerk.
• Remove torch.jit.script wrapper for lbfgs as it causes TorchScript error if history is different
  between trajopt and finetune_trajopt.

Known Bugs (WIP)

• Franka Panda robot loading from urdf in isaac sim 2023.1.1 is unstable.

New release with bug fixes, features, & higher quality solutions

New Features

• Added support for actuated axis to be negative (i.e., urdf joints with <axis xyz="0 -1 0"/> are
  now natively supported).
• Improved gradient calculation to account for terminal state. Trajectory optimization can reach
  within 1mm of accuracy (median across 2600 problems at 0.017mm).
• Improved estimation of previous positions based on start velocity and acceleration. This enables
  Trajectory optimization to optimize from non-zero start velocity and accelerations.
• Added graph planner and finetuning step to joint space planning (motion_gen.plan_single_js). This
  improves success and motion quality when planning to reach joint space targets.
• Added finetuning across many seeds in motion_gen, improving success rate and motion quality.
• Add urdf support to usd helper to export optimization steps as animated usd files for debugging
  motion generation. Check examples/usd_examples.py for an example.
• Retuned weights for IK and Trajectory optimization. This (+ other fixes) significantly improves
  pose reaching accuracy, IK accuracy improves by 100x (98th percentile < 10 micrometers) and motion
  generation median at 0.017mm (with). IK now solves most problems with 24 seeds (vs 30 seeds prev.).
  Run benchmark/ik_benchmark.py to get the latest results.
• Added external_asset_path to robot configuration to help in loading urdf and meshes from an
  external directory.

BugFixes & Misc.

• Update nvblox wrappers to work with v0.0.5 without segfaults. Significantly improves stability.
• Remove mimic joints in franka panda to maintain compatibility with Isaac Sim 2023.1.0 and 2022.2.1
• Cleanup docker scripts. Use build_docker.sh instead of build_dev_docker.sh. Added isaac sim
  development docker.
• Fixed bug in backward kinematics kernel, helped improve IK and TO pose reaching accuracy..
• Changed panda_finger_joint2 from <axis xyz="0 1 0"/>
  to <axis xyz="0 -1 0"/> in franka_panda.urdf to match real robot urdf as cuRobo now supports
  negative axis.
• Changed benchmarking scripts to use lock joint state of [0.025,0.025] for mpinets dataset.
• Added scaling of mesh to Mesh.get_trimesh_mesh() to help in debugging mesh world.
• Improved stability and accuracy of MPPI for MPC.
• Added NaN checking in STOMP covariance computation to account for cases when cholesky decomp
  fails.
• Added ground truth collision check validation in benchmarks/curobo_nvblox_benchmark.py.

Performance Regressions

• cuRobo now generates significantly shorter paths then previous version. E.g., cuRobo obtains
  2.2 seconds 98th percentile motion time on the 2600 problems (benchmark/curobo_benchmark.py), where
  previously it was at 3 seconds (1.36x quicker motions). This was obtained by retuning the weights and
  slight reformulations of trajectory optimization. These changes have led to a slight degrade in
  planning time, 20ms slower on 4090 and 40ms on ORIN MAXN. We will address this slow down in a later
  release. One way to avoid this regression is to set finetune_dt_scale=1.05 in
  MotionGenConfig.load_from_robot_config().

Isaac Sim 2023.1.0 and dockerfiles

• Added support for Isaac Sim 2023.1.0 in examples
• Added dockerfiles for python and isaac sim installation

Initial Public Release

v0.6.0

Update issue templates