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Policy logic from an internal Kamino RL drlegs example should be moved into the main DR Legs example with a CLI switch for policy vs standalone. The request prefers moving to ONNX to avoid a torch dependency and to align the benchmark with the example.

Newton nut_bolt_sdf example fails QA because nuts move jitterily instead of slow and controlled under both xpbd and mujoco solvers. No stderr or crash occurs, but expected physical behavior is not met.

Newton cloth_poker_cards example fails QA: the card stack remains bouncy and never settles after impact. Performance is ~2.5 FPS on an RTX 3080 Laptop GPU.

Newton replay_viewer example fails QA because replayed humanoid bodies penetrate/fall through the ground. The recording run emitted repeated broadphase overflow/contact-capacity warnings, suggesting insufficient buffers as a possible cause.

Newton basic_shapes passes under xpbd but fails under vbd because ground friction appears effectively absent for non-round objects, causing ice-like sliding. This contradicts expected behavior in the sample.

The request is to validate Isaac Sim’s force-based conveyor formulation (Warp kernels applying friction-limited tangential forces from contact impulses) using Newton solvers. Newton’s current conveyor example uses a rotating belt mesh and ordinary friction and lacks behavior verification beyond stability.

Users request a design document covering API Capture, serialized .wrp graphs, and CPU capture/replay. The feature set has expanded enough that code and user guide usage examples are not sufficient to understand behavior and constraints.

In the mujoco_xpbd_coupled_solver example, the chain falls through the cube without interacting, indicating broken collision/constraint coupling. The provided repro uses newton[examples]==1.4.0.rc1 and Warp 1.15.0 on Windows.

In the mujoco_mpm_coupled_solver example, some particles appear stuck in mid-air and do not move. The repro is with newton[examples]==1.4.0.rc1 and Warp 1.15.0 on Windows.

The kamino_mujoco_admm_solver example consistently warns about truncated contacts. The log indicates this happens in a typical setup (Warp 1.15.0 on A40), suggesting defaults or limits are easy to exceed.

The `admm_contact_solver` example sometimes crashes when clicking the UI "Reset" button, with Warp CUDA error 700 illegal memory access. The crash is intermittent and can occur after several resets.

The cable_bundle_hysteresis example renders all cables as a uniform color with no variation, and some CLI options appear to have no effect. This makes the example confusing and possibly indicates a rendering/material or parameter wiring issue.

Examples that adjust ViewerGL camera speed fail because _cam_speed moved from ViewerGL to ViewerGUI in Newton v1.3.0. The example uses hasattr checks that no longer find the attribute, making small-scale scenes hard to view.

In the proxy_joint_gripper example, a deformable object drifts out of the gripper over time. The object should remain stably held after grasping rather than sliding away unexpectedly.

In xpbd_vbd_coupled_solver running with `--solver vbd`, particles pass through unexpectedly. The baseline is expected to keep cloth/particles bounded and above ground.

In mujoco_vbd_coupled_solver with `--solver vbd`, there is excessive floor penetration. Rigid bodies and particles should not significantly penetrate the ground in a baseline configuration.

Switching examples after enabling certain visualization options (Show Joints/Contacts/Inertia Boxes) can crash with Warp CUDA error 700, leading to PTX module load failures. This occurs when moving from robot_g1 to admm_contact_solver.

In mujoco_franka_vbd_cable_admm_solver, the Franka robot penetrates the floor. The example likely needs a placement adjustment and corresponding keypoint updates.

kamino_mujoco_admm_solver logs warnings that Newton rigid_contact_max exceeds Kamino model_max_contacts_host, causing contact truncation. Defaults should be aligned to prevent unexpected truncation in the example.

robot_policy go2 run with PhysX prints repeated narrowphase overflow warnings recommending higher nconmax/naconmax values. The example should be configured to avoid these warnings by default.

Running robot_ur10 with 32 worlds shows some robot instances visually colliding with their base. This suggests an issue with initial placement, joint configuration, or collision setup when scaling world count.

robot_policy go2 repeatedly logs narrowphase overflow warnings suggesting higher nconmax/naconmax. The example is expected to run without these warnings in its default configuration.

The vbd_soft_rigid_contact example runs at around 7 fps on Windows 11 with an A6000. Performance is too low for comfortable use.

A user reports the vbd_rigid_rigid_contact example is hard to understand and questions its value, noting it looks like simple wireframe shapes with unclear purpose. They ask for clarification on what is being shown and why.

The rigid_soft_contact example runs at around 20 Hz on Windows 11 with an A6000. The reporter notes the framerate does not look good at this speed.

Aerial robots are increasingly moving from remote observation toward physical interaction with objects, surfaces, structures, loads, and surrounding flows. This review argues that aerial manipulation cannot be understood as classical manipulation simply mounted on a flying base. Because flying agents remain aloft through continuous momentum and energy exchange with the surrounding medium, support, locomotion, stabilization, and task-directed interaction are intrinsically coupled. Building on broad views of manipulation as intentional environmental regulation through physical interaction, we propose a medium-aware interpretation of aerial manipulation in which interaction may be mediated by contact, by the surrounding fluid, or by both. The review organizes biological and robotic examples into a repertoire of interaction modes and a capability ladder, then develops an actuation-geometric viewpoint in which redundancy induces task-equivalent fibers. Internal motion along these fibers can trade energy for active readiness, aerodynamic promptness, and passive medium coupling. This perspective clarifies why aerial manipulation is difficult, why biological flyers remain broader than robotic systems, and how future platforms may command forces while also shaping how the medium acts back on them.

Safe landing-site assessment in unstructured environments remains a key challenge for autonomous UAV deployment, as vision-only learning approaches often degrade under terrain variability and provide limited transparency in safety decisions. We present NEUROSYMLAND, a neuro-symbolic landing-site assessment system that integrates lightweight perception with explicit safety reasoning. The framework constructs a probabilistic semantic scene graph from onboard visual input and evaluates candidate landing regions using symbolic constraints capturing terrain flatness, obstacle clearance, and spatial consistency, enabling structured reasoning under perceptual uncertainty while maintaining edge-feasible execution. Across 72 simulated landing scenarios spanning diverse terrains, NEUROSYMLAND achieves 61 successful assessments, outperforming four competitive baselines (37-57 successes). To evaluate deployability, we further conduct 100 hardware-in-the-loop trials with randomized initial poses, profiling end-to-end latency, stage-wise execution time, and system-level metrics including CPU/GPU utilization, memory footprint, and power consumption. Results demonstrate improved robustness and interpretability with bounded edge-resource usage. Profiling shows that symbolic reasoning contributes only a small fraction of end-to-end latency, while the main computational cost arises from perception and PSSG construction. These results demonstrate the feasibility of deploying the landing-site assessment stack on edge-constrained UAV hardware, and all source code, datasets, prompts, and symbolic rule refinement examples are released in an open-source repository

This paper presents a novel non-linear mathematical model of an articulated tractor-trailer system that can be used, in combination with receding horizon techniques, to improve the performance of path tracking tasks of articulated systems. Due to its dual steering mechanisms, this type of vehicle can be very useful in precision agriculture, particularly for seeding, spraying and harvesting in small fields. The articulated tractor-trailer system model was embedded within a non-linear model predictive controller and the trailer position was monitored. When the kinematic of the trailer was considered, the deviation of trailer's position was reduced substantially alongside not only straight paths but also in headland turns. Using the proposed mathematical model, we were able to control the trailer's position itself rather than the tractor's position. The Robot Operating System (ROS) framework and Gazebo simulator were used to perform realistic simulations examples.