QUIZ 4: Sensor Fusion, Triangulation¶
Due date: 2026-02-07 23:59.
Recommended Resources:
- SF: Sensing and Filtering, Steven M. LaValle, PDF
- Recorded Lectures and Slides
Question 1¶
Suppose 𝑋 = ℝ³, corresponding to the position of a point, 𝑝, in a 3D environment. Consider a sensor that is a pinhole camera with known position and orientation, as defined in lecture 5.
Suppose the point 𝑝 is observed in the image (i.e., it lies in the field of view of the camera). Which statements are TRUE?
Vihjeet
Viestit
Question 2¶
Using the same setup as in the previous question, suppose the point 𝑝 is not observed (i.e., it lies outside the field of view of the camera).
Which statements are TRUE?
Vihjeet
Viestit
Question 3¶
Consider the state-time space 𝑍 defined as:
Z = X \times T, \qquad
X = [-1,1], \qquad
T = [0,10].
\\\
Define the sensor:
h(x,t)=t.
\\\
Which statements are TRUE if the observation is ℎ(𝑧)=5?
Vihjeet
Viestit
Question 4¶
Consider the preimages of a sensor ℎ : ℝ² → ℝ, defined as:
h(x)=\lVert x-(1,1)\rVert.
\\\
Which statements are TRUE?
Vihjeet
Viestit
Question 5¶
Consider a point robot with the state space 𝑋 = ℝ². Define a region 𝑉 ⊂ 𝑋 and a sensor:
h(x)=
\begin{cases}
1, & x\in V\\
0, & x\notin V.
\end{cases}
\\\
Which statements are TRUE?
Vihjeet
Viestit
Question 6¶
Let 𝑋 = ℝ² be a state space. There are two sensors. One sensor, ℎ₁, measures the distance to a landmark located at coordinates (0, 0). The other sensor, ℎ₂, measures the distance to a landmark located at coordinates (0, 4). Consider a spatial triangulation approach that uses these sensors to solve the problem of estimating the state 𝑥 ∈ 𝑋.
Define the intersection of two preimages, 𝑦₁ and 𝑦₂, as Δ(𝑦₁, 𝑦₂) = ℎ₁⁻¹(𝑦₁) ∩ ℎ₂⁻¹(𝑦₂). Which statements are TRUE?
Note: Symbol ⟺ denotes "if and only if".
Vihjeet
Viestit
Question 7¶
Consider the state–time space:
Z = X \times T, \quad
X = \mathbb{R}^2, \quad
T = [0,10].
\\\
Define three sensors on 𝑍:
- Time sensor: ℎ₁(𝑥, 𝑡) = 𝑡.
- Distance-to-landmark sensor: ℎ₂(𝑥, 𝑡) = ∥𝑥 − (0, 0)∥.
- Detection sensor for a region 𝑉 ⊂ 𝑋:
h_3(x,t) =
\begin{cases}
1, & x \in V, \\
0, & x \notin V.
\end{cases}
\\\
For three observations, 𝑦₁, 𝑦₂, and 𝑦₃, define the 3-way triangulation as the intersection of three preimages:
\Delta(y_1, y_2, y_3)
= h_1^{-1}(y_1) \cap h_2^{-1}(y_2) \cap h_3^{-1}(y_3).
\\\
Which statements are TRUE?
Vihjeet
Viestit
Question 8¶
Consider the state space 𝑋 = ℝ².
- The distance-to-landmark at (1, 1) sensor is defined as:
ℎ_1(𝑥) = ∥𝑥 − (1, 1)∥.
\\\
- Now suppose the sensor is affected by a nondeterministic disturbance with known bound 𝜀 > 0, with the resulting nondeterministic sensor:
h_2(x,d)= ∥x − (1,1)∥ + d, \,\,\,\, d \in [-\varepsilon, \varepsilon].
\\\
Let 𝐻₂⁻¹ denote the nondeterministic preimage of ℎ₂(𝑥, 𝑑). Which statements are TRUE?
Vihjeet
Viestit
Question 9¶
Consider the state-time space
Z = X \times T, \qquad
X = \mathbb{R}^2, \qquad
T = [0,10].
\\\
Now consider the time, distance, and detection sensors, as in Question 7, but assume that the time and distance sensors are affected by nondeterministic disturbances with known bounds. Let 𝜀₁ > 0 and 𝜀₂ > 0 denote the disturbance bounds for the time and distance sensors, respectively.
Define the following sensors on 𝑍:
- Nondeterministic time sensor: ℎ₁(𝑥, 𝑡, 𝑑) = 𝑡 + 𝑑, 𝑑 ∈ [−𝜀₁, 𝜀₁].
- Nondeterministic distance-to-landmark at (0,0) sensor: ℎ₂(𝑥, 𝑡, 𝑑) = ‖𝑥‖+ 𝑑, 𝑑 ∈ [−𝜀₂, 𝜀₂].
- Detection sensor for a region 𝑉 ⊂ 𝑋 (no disturbance):
h_3(x,t) = \begin{cases}
1, & x \in V, \\
0, & x \notin V.
\end{cases}
\\\
For observations 𝑦₁, 𝑦₂, 𝑦₃, define the 3-way triangulation as the intersection of the corresponding preimages:
\Delta(y_1, y_2, y_3) =
H_{1}^{-1}(y_1)
\cap
H_{2}^{-1}(y_2)
\cap
h_3^{-1}(y_3).
\\\
Which statements are TRUE?
Vihjeet
Viestit
Question 10¶
Consider a point robot with the state space 𝑋 = ℝ². Let 𝑉 ⊂ 𝑋 be a detection region.
The robot is equipped with a probabilistic detection sensor that outputs 𝑦 = ℎ(𝑥) ∈ {0, 1}, where 𝑦 = 1 indicates 𝑥 ∈ 𝑉 and 𝑦 = 0 indicates 𝑥 ∉ 𝑉.
The sensor model is:
P(y=1 \mid x\in V)=\tfrac{9}{10}, \qquad P(y=0 \mid x\in V)=\tfrac{1}{10},
\\\
\\\
P(y=1 \mid x\notin V)=\tfrac{1}{10}, \qquad P(y=0 \mid x\notin V)=\tfrac{9}{10}.
\\\
Assume the prior:
P(x\in V)=\tfrac{1}{2}.
\\\
Suppose the observation is 𝑦 = 1. Which statements are TRUE?
Vihjeet
Viestit
Authors¶
Anna LaValle, Steven M. LaValle.
Anna palautetta
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