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
@configclass
class ContactSensorsSceneCfg(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,
history_length=6,
debug_vis=True,
)
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 only the left foot has a non zero “force matrix”, because the right foot isn’t standing on 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.
2# All rights reserved.
3#
4# SPDX-License-Identifier: BSD-3-Clause
5
6"""Launch Isaac Sim Simulator first."""
7
8import argparse
9
10from omni.isaac.lab.app import AppLauncher
11
12# add argparse arguments
13parser = argparse.ArgumentParser(description="Tutorial on adding sensors on a robot.")
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# parse the arguments
18args_cli = parser.parse_args()
19
20# launch omniverse app
21app_launcher = AppLauncher(args_cli)
22simulation_app = app_launcher.app
23
24"""Rest everything follows."""
25
26import torch
27
28import omni.isaac.lab.sim as sim_utils
29from omni.isaac.lab.assets import AssetBaseCfg, RigidObjectCfg
30from omni.isaac.lab.scene import InteractiveScene, InteractiveSceneCfg
31from omni.isaac.lab.sensors import ContactSensorCfg
32from omni.isaac.lab.utils import configclass
33
34##
35# Pre-defined configs
36##
37from omni.isaac.lab_assets.anymal import ANYMAL_C_CFG # isort: skip
38
39
40@configclass
41class ContactSensorSceneCfg(InteractiveSceneCfg):
42 """Design the scene with sensors on the robot."""
43
44 # ground plane
45 ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg())
46
47 # lights
48 dome_light = AssetBaseCfg(
49 prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75))
50 )
51
52 # robot
53 robot = ANYMAL_C_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot")
54
55 # Rigid Object
56 cube = RigidObjectCfg(
57 prim_path="{ENV_REGEX_NS}/Cube",
58 spawn=sim_utils.CuboidCfg(
59 size=(0.5, 0.5, 0.1),
60 rigid_props=sim_utils.RigidBodyPropertiesCfg(),
61 mass_props=sim_utils.MassPropertiesCfg(mass=100.0),
62 collision_props=sim_utils.CollisionPropertiesCfg(),
63 physics_material=sim_utils.RigidBodyMaterialCfg(static_friction=1.0),
64 visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 1.0, 0.0), metallic=0.2),
65 ),
66 init_state=RigidObjectCfg.InitialStateCfg(pos=(0.5, 0.5, 0.05)),
67 )
68
69 contact_forces_LF = ContactSensorCfg(
70 prim_path="{ENV_REGEX_NS}/Robot/LF_FOOT",
71 update_period=0.0,
72 history_length=6,
73 debug_vis=True,
74 filter_prim_paths_expr=["{ENV_REGEX_NS}/Cube"],
75 )
76
77 contact_forces_RF = ContactSensorCfg(
78 prim_path="{ENV_REGEX_NS}/Robot/RF_FOOT",
79 update_period=0.0,
80 history_length=6,
81 debug_vis=True,
82 filter_prim_paths_expr=["{ENV_REGEX_NS}/Cube"],
83 )
84
85 contact_forces_H = ContactSensorCfg(
86 prim_path="{ENV_REGEX_NS}/Robot/.*H_FOOT",
87 update_period=0.0,
88 history_length=6,
89 debug_vis=True,
90 )
91
92
93def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene):
94 """Run the simulator."""
95 # Define simulation stepping
96 sim_dt = sim.get_physics_dt()
97 sim_time = 0.0
98 count = 0
99
100 # Simulate physics
101 while simulation_app.is_running():
102
103 if count % 500 == 0:
104 # reset counter
105 count = 0
106 # reset the scene entities
107 # root state
108 # we offset the root state by the origin since the states are written in simulation world frame
109 # if this is not done, then the robots will be spawned at the (0, 0, 0) of the simulation world
110 root_state = scene["robot"].data.default_root_state.clone()
111 root_state[:, :3] += scene.env_origins
112 scene["robot"].write_root_link_pose_to_sim(root_state[:, :7])
113 scene["robot"].write_root_com_velocity_to_sim(root_state[:, 7:])
114 # set joint positions with some noise
115 joint_pos, joint_vel = (
116 scene["robot"].data.default_joint_pos.clone(),
117 scene["robot"].data.default_joint_vel.clone(),
118 )
119 joint_pos += torch.rand_like(joint_pos) * 0.1
120 scene["robot"].write_joint_state_to_sim(joint_pos, joint_vel)
121 # clear internal buffers
122 scene.reset()
123 print("[INFO]: Resetting robot state...")
124 # Apply default actions to the robot
125 # -- generate actions/commands
126 targets = scene["robot"].data.default_joint_pos
127 # -- apply action to the robot
128 scene["robot"].set_joint_position_target(targets)
129 # -- write data to sim
130 scene.write_data_to_sim()
131 # perform step
132 sim.step()
133 # update sim-time
134 sim_time += sim_dt
135 count += 1
136 # update buffers
137 scene.update(sim_dt)
138
139 # print information from the sensors
140 print("-------------------------------")
141 print(scene["contact_forces_LF"])
142 print("Received force matrix of: ", scene["contact_forces_LF"].data.force_matrix_w)
143 print("Received contact force of: ", scene["contact_forces_LF"].data.net_forces_w)
144 print("-------------------------------")
145 print(scene["contact_forces_RF"])
146 print("Received force matrix of: ", scene["contact_forces_RF"].data.force_matrix_w)
147 print("Received contact force of: ", scene["contact_forces_RF"].data.net_forces_w)
148 print("-------------------------------")
149 print(scene["contact_forces_H"])
150 print("Received force matrix of: ", scene["contact_forces_H"].data.force_matrix_w)
151 print("Received contact force of: ", scene["contact_forces_H"].data.net_forces_w)
152
153
154def main():
155 """Main function."""
156
157 # Initialize the simulation context
158 sim_cfg = sim_utils.SimulationCfg(dt=0.005, device=args_cli.device)
159 sim = sim_utils.SimulationContext(sim_cfg)
160 # Set main camera
161 sim.set_camera_view(eye=[3.5, 3.5, 3.5], target=[0.0, 0.0, 0.0])
162 # design scene
163 scene_cfg = ContactSensorSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0)
164 scene = InteractiveScene(scene_cfg)
165 # Play the simulator
166 sim.reset()
167 # Now we are ready!
168 print("[INFO]: Setup complete...")
169 # Run the simulator
170 run_simulator(sim, scene)
171
172
173if __name__ == "__main__":
174 # run the main function
175 main()
176 # close sim app
177 simulation_app.close()