Contact Sensor#
The contact sensor is designed to return the net contact force acting on a given ridgid body. The sensor is written to behave as a physical object, and so the “scope” of the contact sensor is limited to the body (or bodies) that defines it. There are multiple ways to define this scope, depending on your need to filter the forces coming from the contact.
By default, the reported force is the total contact force, but your application may only care about contact forces due to specific objects. Retrieving contact forces from specific objects requires filtering, and this can only be done in a “many-to-one” way. A multi-legged robot that needs filterable contact information for its feet would require one sensor per foot to be defined in the environment, but a robotic hand with contact sensors on the tips of each finger can be defined with a single sensor.
Consider a simple environment with an Anymal Quadruped and a block
from isaaclab_assets.robots.anymal import ANYMAL_C_CFG # isort: skip
@configclass
class ContactSensorSceneCfg(InteractiveSceneCfg):
"""Design the scene with sensors on the robot."""
# ground plane
ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())
# lights
dome_light = AssetBaseCfg(
prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75))
)
# robot
robot = ANYMAL_C_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
# Rigid Object
cube = RigidObjectCfg(
prim_path="{ENV_REGEX_NS}/Cube",
spawn=sim_utils.CuboidCfg(
size=(0.5, 0.5, 0.1),
rigid_props=sim_utils.RigidBodyPropertiesCfg(),
mass_props=sim_utils.MassPropertiesCfg(mass=100.0),
collision_props=sim_utils.CollisionPropertiesCfg(),
physics_material=sim_utils.RigidBodyMaterialCfg(static_friction=1.0),
visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 1.0, 0.0), metallic=0.2),
),
init_state=RigidObjectCfg.InitialStateCfg(pos=(0.5, 0.5, 0.05)),
)
contact_forces_LF = ContactSensorCfg(
prim_path="{ENV_REGEX_NS}/Robot/LF_FOOT",
update_period=0.0,
history_length=6,
debug_vis=True,
filter_prim_paths_expr=["{ENV_REGEX_NS}/Cube"],
)
contact_forces_RF = ContactSensorCfg(
prim_path="{ENV_REGEX_NS}/Robot/RF_FOOT",
update_period=0.0,
history_length=6,
debug_vis=True,
filter_prim_paths_expr=["{ENV_REGEX_NS}/Cube"],
)
contact_forces_H = ContactSensorCfg(
prim_path="{ENV_REGEX_NS}/Robot/.*H_FOOT",
update_period=0.0,
We define the sensors on the feet of the robot in two different ways. The front feet are independent sensors (one sensor body per foot) and the “Cube” is placed under the left foot. The hind feet are defined as a single sensor with multiple bodies.
We can then run the scene and print the data from the sensors
def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
.
.
.
# Simulate physics
while simulation_app.is_running():
.
.
.
# print information from the sensors
print("-------------------------------")
print(scene["contact_forces_LF"])
print("Received force matrix of: ", scene["contact_forces_LF"].data.force_matrix_w)
print("Received contact force of: ", scene["contact_forces_LF"].data.net_forces_w)
print("-------------------------------")
print(scene["contact_forces_RF"])
print("Received force matrix of: ", scene["contact_forces_RF"].data.force_matrix_w)
print("Received contact force of: ", scene["contact_forces_RF"].data.net_forces_w)
print("-------------------------------")
print(scene["contact_forces_H"])
print("Received force matrix of: ", scene["contact_forces_H"].data.force_matrix_w)
print("Received contact force of: ", scene["contact_forces_H"].data.net_forces_w)
Here, we print both the net contact force and the filtered force matrix for each contact sensor defined in the scene. The front left and front right feet report the following
-------------------------------
Contact sensor @ '/World/envs/env_.*/Robot/LF_FOOT':
view type : <class 'omni.physics.tensors.impl.api.RigidBodyView'>
update period (s) : 0.0
number of bodies : 1
body names : ['LF_FOOT']
Received force matrix of: tensor([[[[-1.3923e-05, 1.5727e-04, 1.1032e+02]]]], device='cuda:0')
Received contact force of: tensor([[[-1.3923e-05, 1.5727e-04, 1.1032e+02]]], device='cuda:0')
-------------------------------
Contact sensor @ '/World/envs/env_.*/Robot/RF_FOOT':
view type : <class 'omni.physics.tensors.impl.api.RigidBodyView'>
update period (s) : 0.0
number of bodies : 1
body names : ['RF_FOOT']
Received force matrix of: tensor([[[[0., 0., 0.]]]], device='cuda:0')
Received contact force of: tensor([[[1.3529e-05, 0.0000e+00, 1.0069e+02]]], device='cuda:0')
Notice that even with filtering, both sensors report the net contact force acting on the foot. However, the “force matrix” on the right foot is zero because that foot isn’t in contact with the filtered body, /World/envs/env_.*/Cube. Now, checkout the data coming from the hind feet!
-------------------------------
Contact sensor @ '/World/envs/env_.*/Robot/.*H_FOOT':
view type : <class 'omni.physics.tensors.impl.api.RigidBodyView'>
update period (s) : 0.0
number of bodies : 2
body names : ['LH_FOOT', 'RH_FOOT']
Received force matrix of: None
Received contact force of: tensor([[[9.7227e-06, 0.0000e+00, 7.2364e+01],
[2.4322e-05, 0.0000e+00, 1.8102e+02]]], device='cuda:0')
In this case, the contact sensor has two bodies: the left and right hind feet. When the force matrix is queried, the result is None because this is a many body sensor, and presently Isaac Lab only supports “many to one” contact force filtering. Unlike the single body contact sensor, the reported force tensor has multiple entries, with each “row” corresponding to the contact force on a single body of the sensor (matching the ordering at construction).
Code for contact_sensor.py
1# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
2# All rights reserved.
3#
4# SPDX-License-Identifier: BSD-3-Clause
5
6"""Launch Isaac Sim Simulator first."""
7
8import argparse
9
10from isaaclab.app import AppLauncher
11
12# add argparse arguments
13parser = argparse.ArgumentParser(description="Example on using the contact sensor.")
14parser.add_argument("--num_envs", type=int, default=1, help="Number of environments to spawn.")
15# append AppLauncher cli args
16AppLauncher.add_app_launcher_args(parser)
17# demos should open Kit visualizer by default
18parser.set_defaults(visualizer=["kit"])
19# parse the arguments
20args_cli = parser.parse_args()
21
22# launch omniverse app
23app_launcher = AppLauncher(args_cli)
24simulation_app = app_launcher.app
25
26"""Rest everything follows."""
27
28import torch
29import warp as wp
30
31import isaaclab.sim as sim_utils
32from isaaclab.assets import AssetBaseCfg, RigidObjectCfg
33from isaaclab.scene import InteractiveScene, InteractiveSceneCfg
34from isaaclab.sensors import ContactSensorCfg
35from isaaclab.utils import configclass
36
37##
38# Pre-defined configs
39##
40from isaaclab_assets.robots.anymal import ANYMAL_C_CFG # isort: skip
41
42
43@configclass
44class ContactSensorSceneCfg(InteractiveSceneCfg):
45 """Design the scene with sensors on the robot."""
46
47 # ground plane
48 ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())
49
50 # lights
51 dome_light = AssetBaseCfg(
52 prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75))
53 )
54
55 # robot
56 robot = ANYMAL_C_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
57
58 # Rigid Object
59 cube = RigidObjectCfg(
60 prim_path="{ENV_REGEX_NS}/Cube",
61 spawn=sim_utils.CuboidCfg(
62 size=(0.5, 0.5, 0.1),
63 rigid_props=sim_utils.RigidBodyPropertiesCfg(),
64 mass_props=sim_utils.MassPropertiesCfg(mass=100.0),
65 collision_props=sim_utils.CollisionPropertiesCfg(),
66 physics_material=sim_utils.RigidBodyMaterialCfg(static_friction=1.0),
67 visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 1.0, 0.0), metallic=0.2),
68 ),
69 init_state=RigidObjectCfg.InitialStateCfg(pos=(0.5, 0.5, 0.05)),
70 )
71
72 contact_forces_LF = ContactSensorCfg(
73 prim_path="{ENV_REGEX_NS}/Robot/LF_FOOT",
74 update_period=0.0,
75 history_length=6,
76 debug_vis=True,
77 filter_prim_paths_expr=["{ENV_REGEX_NS}/Cube"],
78 )
79
80 contact_forces_RF = ContactSensorCfg(
81 prim_path="{ENV_REGEX_NS}/Robot/RF_FOOT",
82 update_period=0.0,
83 history_length=6,
84 debug_vis=True,
85 filter_prim_paths_expr=["{ENV_REGEX_NS}/Cube"],
86 )
87
88 contact_forces_H = ContactSensorCfg(
89 prim_path="{ENV_REGEX_NS}/Robot/.*H_FOOT",
90 update_period=0.0,
91 history_length=6,
92 debug_vis=True,
93 )
94
95
96def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
97 """Run the simulator."""
98 # Define simulation stepping
99 sim_dt = sim.get_physics_dt()
100 sim_time = 0.0
101 count = 0
102
103 # Simulate physics
104 while simulation_app.is_running():
105 if count % 500 == 0:
106 # reset counter
107 count = 0
108 # reset the scene entities
109 # root state
110 # we offset the root state by the origin since the states are written in simulation world frame
111 # if this is not done, then the robots will be spawned at the (0, 0, 0) of the simulation world
112 root_pose = wp.to_torch(scene["robot"].data.default_root_pose).clone()
113 root_pose[:, :3] += scene.env_origins
114 scene["robot"].write_root_pose_to_sim_index(root_pose=root_pose)
115 root_vel = wp.to_torch(scene["robot"].data.default_root_vel).clone()
116 scene["robot"].write_root_velocity_to_sim_index(root_velocity=root_vel)
117 # set joint positions with some noise
118 joint_pos, joint_vel = (
119 wp.to_torch(scene["robot"].data.default_joint_pos).clone(),
120 wp.to_torch(scene["robot"].data.default_joint_vel).clone(),
121 )
122 joint_pos += torch.rand_like(joint_pos) * 0.1
123 scene["robot"].write_joint_position_to_sim_index(position=joint_pos)
124 scene["robot"].write_joint_velocity_to_sim_index(velocity=joint_vel)
125 # clear internal buffers
126 scene.reset()
127 print("[INFO]: Resetting robot state...")
128 # Apply default actions to the robot
129 # -- generate actions/commands
130 targets = wp.to_torch(scene["robot"].data.default_joint_pos)
131 # -- apply action to the robot
132 scene["robot"].set_joint_position_target_index(target=targets)
133 # -- write data to sim
134 scene.write_data_to_sim()
135 # perform step
136 sim.step()
137 # update sim-time
138 sim_time += sim_dt
139 count += 1
140 # update buffers
141 scene.update(sim_dt)
142
143 # print information from the sensors
144 print("-------------------------------")
145 print(scene["contact_forces_LF"])
146 print("Received force matrix of: ", scene["contact_forces_LF"].data.force_matrix_w)
147 print("Received contact force of: ", scene["contact_forces_LF"].data.net_forces_w)
148 print("-------------------------------")
149 print(scene["contact_forces_RF"])
150 print("Received force matrix of: ", scene["contact_forces_RF"].data.force_matrix_w)
151 print("Received contact force of: ", scene["contact_forces_RF"].data.net_forces_w)
152 print("-------------------------------")
153 print(scene["contact_forces_H"])
154 print("Received force matrix of: ", scene["contact_forces_H"].data.force_matrix_w)
155 print("Received contact force of: ", scene["contact_forces_H"].data.net_forces_w)
156
157
158def main():
159 """Main function."""
160
161 # Initialize the simulation context
162 sim_cfg = sim_utils.SimulationCfg(dt=0.005, device=args_cli.device)
163 sim = sim_utils.SimulationContext(sim_cfg)
164 # Set main camera
165 sim.set_camera_view(eye=[3.5, 3.5, 3.5], target=[0.0, 0.0, 0.0])
166 # design scene
167 scene_cfg = ContactSensorSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0)
168 scene = InteractiveScene(scene_cfg)
169 # Play the simulator
170 sim.reset()
171 # Now we are ready!
172 print("[INFO]: Setup complete...")
173 # Run the simulator
174 run_simulator(sim, scene)
175
176
177if __name__ == "__main__":
178 # run the main function
179 main()
180 # close sim app
181 simulation_app.close()