File: kalman_predictor.h

package info (click to toggle)
chromium 138.0.7204.183-1
  • links: PTS, VCS
  • area: main
  • in suites: trixie
  • size: 6,071,908 kB
  • sloc: cpp: 34,937,088; ansic: 7,176,967; javascript: 4,110,704; python: 1,419,953; asm: 946,768; xml: 739,971; pascal: 187,324; sh: 89,623; perl: 88,663; objc: 79,944; sql: 50,304; cs: 41,786; fortran: 24,137; makefile: 21,806; php: 13,980; tcl: 13,166; yacc: 8,925; ruby: 7,485; awk: 3,720; lisp: 3,096; lex: 1,327; ada: 727; jsp: 228; sed: 36
file content (86 lines) | stat: -rw-r--r-- 2,848 bytes parent folder | download | duplicates (10)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
// Copyright 2018 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.

#ifndef UI_BASE_PREDICTION_KALMAN_PREDICTOR_H_
#define UI_BASE_PREDICTION_KALMAN_PREDICTOR_H_

#include <deque>
#include <vector>

#include "base/component_export.h"
#include "ui/base/prediction/input_predictor.h"
#include "ui/base/prediction/kalman_filter.h"

namespace ui {

// Class to perform kalman filter prediction inherited from InputPredictor.
// This predictor uses kalman filters to predict the current status of the
// motion. Then it predict the future points using <current_position,
// predicted_velocity, predicted_acceleration>. Each kalman_filter will only
// be used to predict one dimension (x, y).
class COMPONENT_EXPORT(UI_BASE_PREDICTION) KalmanPredictor
    : public InputPredictor {
 public:
  // Heuristic option enables changing the influence of acceleration based on
  // change of direction. Direction cut off enables discarding the prediction if
  // the predicted direction is opposite from the current direction.
  enum PredictionOptions {
    kNone = 0x0,
    kHeuristicsEnabled = 0x1,
    kDirectionCutOffEnabled = 0x2
  };

  explicit KalmanPredictor(unsigned int prediction_options);

  KalmanPredictor(const KalmanPredictor&) = delete;
  KalmanPredictor& operator=(const KalmanPredictor&) = delete;

  ~KalmanPredictor() override;

  const char* GetName() const override;

  // Reset the predictor to initial state.
  void Reset() override;

  // Store current input in queue.
  void Update(const InputData& cur_input) override;

  // Return if there is enough data in the queue to generate prediction.
  bool HasPrediction() const override;

  // Generate the prediction based on stored points and given time_stamp.
  // Return false if no prediction available.
  std::unique_ptr<InputData> GeneratePrediction(
      base::TimeTicks predict_time,
      base::TimeDelta frame_interval) override;

  // Return the filtered value of time intervals.
  base::TimeDelta TimeInterval() const override;

 private:
  // The following functions get the predicted values from kalman filters.
  gfx::Vector2dF PredictPosition() const;
  gfx::Vector2dF PredictVelocity() const;
  gfx::Vector2dF PredictAcceleration() const;

  // Predictor for each axis.
  KalmanFilter x_predictor_;
  KalmanFilter y_predictor_;

  // Filter to smooth time intervals.
  KalmanFilter time_filter_;

  // Most recent input data.
  std::deque<InputData> last_points_;

  // Maximum time interval between first and last events in last points queue.
  static constexpr base::TimeDelta kMaxTimeInQueue = base::Milliseconds(40);

  // Flags to determine the enabled prediction options.
  const unsigned int prediction_options_;
};

}  // namespace ui

#endif  // UI_BASE_PREDICTION_KALMAN_PREDICTOR_H_