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
# Pre-defined configs
##
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(
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) 2022-2025, 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# Copyright (c) 2022-2025, The Isaac Lab Project Developers.
7# All rights reserved.
8#
9# SPDX-License-Identifier: BSD-3-Clause
10
11"""Launch Isaac Sim Simulator first."""
12
13import argparse
14
15from isaaclab.app import AppLauncher
16
17# add argparse arguments
18parser = argparse.ArgumentParser(description="Example on using the contact sensor.")
19parser.add_argument("--num_envs", type=int, default=1, help="Number of environments to spawn.")
20# append AppLauncher cli args
21AppLauncher.add_app_launcher_args(parser)
22# parse the arguments
23args_cli = parser.parse_args()
24
25# launch omniverse app
26app_launcher = AppLauncher(args_cli)
27simulation_app = app_launcher.app
28
29"""Rest everything follows."""
30
31import torch
32
33import isaaclab.sim as sim_utils
34from isaaclab.assets import AssetBaseCfg, RigidObjectCfg
35from isaaclab.scene import InteractiveScene, InteractiveSceneCfg
36from isaaclab.sensors import ContactSensorCfg
37from isaaclab.utils import configclass
38
39##
40# Pre-defined configs
41##
42from isaaclab_assets.robots.anymal import ANYMAL_C_CFG # isort: skip
43
44
45@configclass
46class ContactSensorSceneCfg(InteractiveSceneCfg):
47 """Design the scene with sensors on the robot."""
48
49 # ground plane
50 ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())
51
52 # lights
53 dome_light = AssetBaseCfg(
54 prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75))
55 )
56
57 # robot
58 robot = ANYMAL_C_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
59
60 # Rigid Object
61 cube = RigidObjectCfg(
62 prim_path="{ENV_REGEX_NS}/Cube",
63 spawn=sim_utils.CuboidCfg(
64 size=(0.5, 0.5, 0.1),
65 rigid_props=sim_utils.RigidBodyPropertiesCfg(),
66 mass_props=sim_utils.MassPropertiesCfg(mass=100.0),
67 collision_props=sim_utils.CollisionPropertiesCfg(),
68 physics_material=sim_utils.RigidBodyMaterialCfg(static_friction=1.0),
69 visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 1.0, 0.0), metallic=0.2),
70 ),
71 init_state=RigidObjectCfg.InitialStateCfg(pos=(0.5, 0.5, 0.05)),
72 )
73
74 contact_forces_LF = ContactSensorCfg(
75 prim_path="{ENV_REGEX_NS}/Robot/LF_FOOT",
76 update_period=0.0,
77 history_length=6,
78 debug_vis=True,
79 filter_prim_paths_expr=["{ENV_REGEX_NS}/Cube"],
80 )
81
82 contact_forces_RF = ContactSensorCfg(
83 prim_path="{ENV_REGEX_NS}/Robot/RF_FOOT",
84 update_period=0.0,
85 history_length=6,
86 debug_vis=True,
87 filter_prim_paths_expr=["{ENV_REGEX_NS}/Cube"],
88 )
89
90 contact_forces_H = ContactSensorCfg(
91 prim_path="{ENV_REGEX_NS}/Robot/.*H_FOOT",
92 update_period=0.0,
93 history_length=6,
94 debug_vis=True,
95 )
96
97
98def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
99 """Run the simulator."""
100 # Define simulation stepping
101 sim_dt = sim.get_physics_dt()
102 sim_time = 0.0
103 count = 0
104
105 # Simulate physics
106 while simulation_app.is_running():
107
108 if count % 500 == 0:
109 # reset counter
110 count = 0
111 # reset the scene entities
112 # root state
113 # we offset the root state by the origin since the states are written in simulation world frame
114 # if this is not done, then the robots will be spawned at the (0, 0, 0) of the simulation world
115 root_state = scene["robot"].data.default_root_state.clone()
116 root_state[:, :3] += scene.env_origins
117 scene["robot"].write_root_pose_to_sim(root_state[:, :7])
118 scene["robot"].write_root_velocity_to_sim(root_state[:, 7:])
119 # set joint positions with some noise
120 joint_pos, joint_vel = (
121 scene["robot"].data.default_joint_pos.clone(),
122 scene["robot"].data.default_joint_vel.clone(),
123 )
124 joint_pos += torch.rand_like(joint_pos) * 0.1
125 scene["robot"].write_joint_state_to_sim(joint_pos, joint_vel)
126 # clear internal buffers
127 scene.reset()
128 print("[INFO]: Resetting robot state...")
129 # Apply default actions to the robot
130 # -- generate actions/commands
131 targets = scene["robot"].data.default_joint_pos
132 # -- apply action to the robot
133 scene["robot"].set_joint_position_target(targets)
134 # -- write data to sim
135 scene.write_data_to_sim()
136 # perform step
137 sim.step()
138 # update sim-time
139 sim_time += sim_dt
140 count += 1
141 # update buffers
142 scene.update(sim_dt)
143
144 # print information from the sensors
145 print("-------------------------------")
146 print(scene["contact_forces_LF"])
147 print("Received force matrix of: ", scene["contact_forces_LF"].data.force_matrix_w)
148 print("Received contact force of: ", scene["contact_forces_LF"].data.net_forces_w)
149 print("-------------------------------")
150 print(scene["contact_forces_RF"])
151 print("Received force matrix of: ", scene["contact_forces_RF"].data.force_matrix_w)
152 print("Received contact force of: ", scene["contact_forces_RF"].data.net_forces_w)
153 print("-------------------------------")
154 print(scene["contact_forces_H"])
155 print("Received force matrix of: ", scene["contact_forces_H"].data.force_matrix_w)
156 print("Received contact force of: ", scene["contact_forces_H"].data.net_forces_w)
157
158
159def main():
160 """Main function."""
161
162 # Initialize the simulation context
163 sim_cfg = sim_utils.SimulationCfg(dt=0.005, device=args_cli.device)
164 sim = sim_utils.SimulationContext(sim_cfg)
165 # Set main camera
166 sim.set_camera_view(eye=[3.5, 3.5, 3.5], target=[0.0, 0.0, 0.0])
167 # design scene
168 scene_cfg = ContactSensorSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0)
169 scene = InteractiveScene(scene_cfg)
170 # Play the simulator
171 sim.reset()
172 # Now we are ready!
173 print("[INFO]: Setup complete...")
174 # Run the simulator
175 run_simulator(sim, scene)
176
177
178if __name__ == "__main__":
179 # run the main function
180 main()
181 # close sim app
182 simulation_app.close()