US 12,558,787 B2 · Robotic arm obstacle avoiding path planning method

Abstract

A robotic arm obstacle avoiding path planning method is provided. The method includes the following steps: step 1: simplifying the robotic arm model and obstacles, determining robotic arm joint points, and adopting virtual joint interpolation to interpolate connecting rods between adjacent joints; employing spherical bounding boxes at each joint point to envelop and replace the robotic arm model, enabling complete substitution for distance calculation when the robotic arm assumes any posture; step 2: adopting an eye-to-hand configuration to position the depth camera, acquiring in real time the point cloud information of the robotic arm and obstacles in the workspace, and using a robot real-time filtering package to filter out the point cloud information of the robotic arm itself.

A robotic arm obstacle avoiding path planning method, comprising the following steps:

step 1:
based on a robotic arm model and obstacles, determining robotic arm joint points, and adopting virtual joint interpolation to interpolate connecting rods between adjacent joints;
and employing spherical bounding boxes at each joint point to envelop and replace the robotic arm model to facilitate distance calculation when a robotic arm assumes any posture;
step 2:
adopting an eye-to-hand configuration to position a depth camera, acquiring real-time point cloud information of the robotic arm and the obstacles in a workspace, using a robot real-time filtering package to filter out the real-time point cloud information of the robotic arm, and retaining only the real-time point cloud information of the obstacles;
step 3:
before moving the robotic arm, using a rapidly-exploring random tree connect (RRT-Connect) algorithm to perform path planning in a static environment where the robotic arm is located, and leveraging completeness of the RRT-Connect algorithm to obtain a feasible globally planned path;
step 4:
controlling the robotic arm to move along the feasible globally planned path, acquiring the real-time point cloud information of the obstacles in the workspace of the robotic arm, and calculating a distance between a point cloud of an obstacle and the robotic arm joint points in a coordinate system of the robotic arm to obtain a shortest distance;
step 5:
implementing obstacle avoiding through local path planning using an artificial potential field method, determining a distance and a position vector between a robotic arm end and a goal point in real time, and determining a magnitude of an attractive force exerted by the goal point on the robotic arm end based on the distance and the position vector between the robotic arm end and the goal point;
wherein the goal point is a goal position where the robotic arm is controlled to reach;
and a function formula for determining the distance and the position vector between the robotic arm end and the goal point in real time and determining the magnitude of the attractive force based on the distance and the position vector between the robotic arm end and the goal point is:
F
att
=
-
∇
(
U
att
)
=
ξ
′
⁢
ρ
⁢
(
q
,
q
goal
)
,
wherein ρ (q, qgoal) is a Euclidean distance between the robotic arm end and the goal point;
Uatt is an attractive potential field function, and
U
att
=
1
2
⁢
ξ
′
⁢
ρ
2
⁢
(
q
,
q
goal
)
;
and ξ′ is a dynamic gain coefficient of the attractive force, expressed as ξ′=k*(e−ρ(q,qgoal)), wherein the dynamic gain coefficient is inversely proportional to a distance between the robotic arm and the goal point, with a minimum gain coefficient at a starting point, thereby enabling adjustment of the magnitude of the attractive force to prevent an excessive attractive force that cause collisions between the robotic arm and the obstacles, and ensuring that the robotic arm obtains a safe and smooth path;
determining the shortest distance between the robotic arm joint points and the point cloud of the obstacle in real time, wherein when the shortest distance is greater than a set safety distance, a repulsive force of the obstacles on the robotic arm is 0, and when the shortest distance is less than the set safety distance, a magnitude of the repulsive force is determined based on the robotic arm joint points and a nearest obstacle point, and a function formula of the magnitude of the repulsive force is:
F
repi
=
-
∇
(
U
rep
)
=
{
F
rep
⁢
1
⁢
i
+
F
rep
⁢
2
⁢
i
,
ρ
i
⁢
(
q
,
q
obst
)
≤
ρ
0
0
,
ρ
i
⁢
(
q
,
q
obst
)
>
ρ
0
,
wherein Urep is a repulsive potential field generated by the obstacles;
ρ0 is a safety distance radius;
ρi (q, qobst) is a Euclidean distance between the robotic arm end and an i-th obstacle;
Frep1i is a repulsive force component, with direction from the obstacles pointing to the robotic arm end, and magnitude is:
F
rep
⁢
1
⁢
i
=
m
⁢
❘
"\[LeftBracketingBar]"
1
ρ
⁢
(
q
,
q
goal
)
-
1
ρ
0
❘
"\[RightBracketingBar]"
⁢
ρ
n
⁢
(
q
,
q
goal
)
ρ
i
2
⁢
(
q
,
q
obst
)
;
wherein Frep2i is an attractive force component, with direction from the robotic arm end pointing to the goal point, and magnitude is:
F
rep
⁢
2
⁢
i
=
n
2
⁢
m
⁢
❘
"\[LeftBracketingBar]"
1
ρ
i
⁢
(
q
,
q
obst
)
-
1
ρ
0
❘
"\[RightBracketingBar]"
⁢
ρ
n
-
1
⁢
(
q
,
q
goal
)
;
wherein when the robotic arm uses a local planner to plan the safe and smooth path, a combined force generated by the attractive force and the repulsive force guides movements of the robotic arm;
step 6:
introducing a guiding force to the robotic arm end, wherein the guiding force enables the robotic arm to move to a next position for re-planning when the robotic arm is trapped in a local minimum;
a function formula of the guiding force is:
F
a
=
⁢
{
{
1
,
ρ
⁢
(
q
,
q
obst
)
>
ρ
0
/
2
0.5
,
ρ
⁢
(
q
,
q
obst
)
≤
ρ
0
/
2
,
s
=
1
a
*
x
,
s
>
1
,
a function formula of the combined force when falling into the local minimum is:
F
comb
=
F
att
+
∑
i
=
1
s
F
repi
+
F
a
,
wherein s is a number of the obstacles;
a is a guiding force coefficient;
a value range of x is [1, 10];
a value of a varies with the number of the obstacles and a distance between the robotic arm and the obstacles;
when the number of the obstacles is 1, if the distance between the robotic arm and the obstacle is greater than half of a safety distance, then a takes a value of 1, otherwise a takes a value of 0.5;
when the number of the obstacles is greater than 1, a monotonic increasing function is used as a guiding function to assign the value to a until the robotic arm escapes a local minimum point;
and if the next position still falls into the local minimum, the above method is repeated;
step 7:
introducing a pre-planning mechanism performed by the local planner in the local path planning;
and
step 8:
incorporating a following mechanism performed by the local planner in the local path planning.

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Robotic arm obstacle avoiding path planning method

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Robotic arm obstacle avoiding path planning method

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Abstract

Claims5