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Peter Johnson
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// Copyright (c) FIRST and other WPILib contributors.
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// Open Source Software; you can modify and/or share it under the terms of
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// the WPILib BSD license file in the root directory of this project.
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#pragma once
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#include <algorithm>
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#include <functional>
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#include <optional>
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#include <utility>
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#include <vector>
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#include <wpi/MathExtras.h>
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#include <wpi/SymbolExports.h>
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#include "frc/geometry/Pose2d.h"
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#include "units/time.h"
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namespace frc {
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/**
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* The TimeInterpolatableBuffer provides an easy way to estimate past
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* measurements. One application might be in conjunction with the
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* DifferentialDrivePoseEstimator, where knowledge of the robot pose at the time
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* when vision or other global measurement were recorded is necessary, or for
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* recording the past angles of mechanisms as measured by encoders.
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*
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* When sampling this buffer, a user-provided function or wpi::Lerp can be
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* used. For Pose2ds, we use Twists.
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*
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* @tparam T The type stored in this buffer.
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*/
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template <typename T>
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class TimeInterpolatableBuffer {
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public:
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/**
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* Create a new TimeInterpolatableBuffer.
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*
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* @param historySize The history size of the buffer.
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* @param func The function used to interpolate between values.
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*/
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TimeInterpolatableBuffer(units::second_t historySize,
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std::function<T(const T&, const T&, double)> func)
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: m_historySize(historySize), m_interpolatingFunc(func) {}
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/**
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* Create a new TimeInterpolatableBuffer. By default, the interpolation
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* function is wpi::Lerp except for Pose2d, which uses the pose exponential.
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*
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* @param historySize The history size of the buffer.
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*/
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explicit TimeInterpolatableBuffer(units::second_t historySize)
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: m_historySize(historySize),
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m_interpolatingFunc([](const T& start, const T& end, double t) {
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return wpi::Lerp(start, end, t);
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}) {}
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/**
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* Add a sample to the buffer.
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*
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* @param time The timestamp of the sample.
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* @param sample The sample object.
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*/
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void AddSample(units::second_t time, T sample) {
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// Add the new state into the vector
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if (m_pastSnapshots.size() == 0 || time > m_pastSnapshots.back().first) {
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m_pastSnapshots.emplace_back(time, sample);
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} else {
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auto first_after = std::upper_bound(
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m_pastSnapshots.begin(), m_pastSnapshots.end(), time,
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[](auto t, const auto& pair) { return t < pair.first; });
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if (first_after == m_pastSnapshots.begin()) {
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// All entries come after the sample
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m_pastSnapshots.insert(first_after, std::pair{time, sample});
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} else if (auto last_not_greater_than = first_after - 1;
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last_not_greater_than == m_pastSnapshots.begin() ||
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last_not_greater_than->first < time) {
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// Some entries come before the sample, but none are recorded with the
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// same time
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m_pastSnapshots.insert(first_after, std::pair{time, sample});
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} else {
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// An entry exists with the same recorded time
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last_not_greater_than->second = sample;
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}
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}
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while (time - m_pastSnapshots[0].first > m_historySize) {
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m_pastSnapshots.erase(m_pastSnapshots.begin());
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}
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}
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/** Clear all old samples. */
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void Clear() { m_pastSnapshots.clear(); }
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/**
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* Sample the buffer at the given time. If the buffer is empty, an empty
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* optional is returned.
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*
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* @param time The time at which to sample the buffer.
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*/
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std::optional<T> Sample(units::second_t time) const {
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if (m_pastSnapshots.empty()) {
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return {};
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}
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// We will perform a binary search to find the index of the element in the
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// vector that has a timestamp that is equal to or greater than the vision
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// measurement timestamp.
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if (time <= m_pastSnapshots.front().first) {
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return m_pastSnapshots.front().second;
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}
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if (time > m_pastSnapshots.back().first) {
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return m_pastSnapshots.back().second;
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}
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if (m_pastSnapshots.size() < 2) {
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return m_pastSnapshots[0].second;
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}
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// Get the iterator which has a key no less than the requested key.
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auto upper_bound = std::lower_bound(
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m_pastSnapshots.begin(), m_pastSnapshots.end(), time,
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[](const auto& pair, auto t) { return t > pair.first; });
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if (upper_bound == m_pastSnapshots.begin()) {
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return upper_bound->second;
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}
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auto lower_bound = upper_bound - 1;
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double t = ((time - lower_bound->first) /
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(upper_bound->first - lower_bound->first));
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return m_interpolatingFunc(lower_bound->second, upper_bound->second, t);
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}
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/**
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* Grant access to the internal sample buffer. Used in Pose Estimation to
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* replay odometry inputs stored within this buffer.
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*/
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std::vector<std::pair<units::second_t, T>>& GetInternalBuffer() {
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return m_pastSnapshots;
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}
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/**
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* Grant access to the internal sample buffer.
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*/
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const std::vector<std::pair<units::second_t, T>>& GetInternalBuffer() const {
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return m_pastSnapshots;
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}
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private:
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units::second_t m_historySize;
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std::vector<std::pair<units::second_t, T>> m_pastSnapshots;
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std::function<T(const T&, const T&, double)> m_interpolatingFunc;
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};
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// Template specialization to ensure that Pose2d uses pose exponential
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template <>
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inline TimeInterpolatableBuffer<Pose2d>::TimeInterpolatableBuffer(
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units::second_t historySize)
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: m_historySize(historySize),
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m_interpolatingFunc([](const Pose2d& start, const Pose2d& end, double t) {
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if (t < 0) {
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return start;
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} else if (t >= 1) {
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return end;
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} else {
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Twist2d twist = (end - start).Log();
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Twist2d scaledTwist = twist * t;
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return start + scaledTwist.Exp();
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}
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}) {}
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} // namespace frc
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