124 lines
4.5 KiB
Python
124 lines
4.5 KiB
Python
import json
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import math
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# Load robot.json
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with open(r'robot.json') as f:
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robot = json.load(f)
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# Extract markers by link
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markers_by_link = {}
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for link_name, link_data in robot['links'].items():
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markers = link_data.get('markers', [])
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if markers:
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markers_by_link[link_name] = markers
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print("=" * 70)
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print("MARKER DISTRIBUTION BY LINK")
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print("=" * 70)
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for link, markers in markers_by_link.items():
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print(f"\n{link}: {len(markers)} markers")
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for m in markers:
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pos = m['position']
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print(f" ID {m['id']:3d}: pos={pos}")
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# Check rigid body constraints: distances within each link
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print("\n" + "=" * 70)
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print("RIGID BODY CONSTRAINT CHECK (Arm1, Ellbow, Arm2)")
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print("=" * 70)
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for link_name in ['Arm1', 'Ellbow', 'Arm2']:
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if link_name not in markers_by_link:
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continue
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markers = markers_by_link[link_name]
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positions = [(m['position'][0], m['position'][1], m['position'][2]) for m in markers]
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print(f"\n{link_name}:")
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if len(positions) > 1:
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for i in range(len(positions)):
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for j in range(i+1, len(positions)):
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dx = positions[i][0] - positions[j][0]
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dy = positions[i][1] - positions[j][1]
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dz = positions[i][2] - positions[j][2]
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dist = math.sqrt(dx*dx + dy*dy + dz*dz)
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print(f" Marker {markers[i]['id']:3d} <-> {markers[j]['id']:3d}: {dist:7.2f} mm")
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else:
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print(f" Only {len(positions)} marker(s)")
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# Check X-distances between links
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print("\n" + "=" * 70)
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print("X-POSITION CONSTRAINT CHECK (Link relationships)")
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print("=" * 70)
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# Get marker positions per link
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link_x_positions = {}
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for link_name in ['Board', 'Base', 'Arm1', 'Ellbow', 'Arm2']:
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if link_name in markers_by_link:
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x_vals = [m['position'][0] for m in markers_by_link[link_name]]
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link_x_positions[link_name] = {
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'min_x': min(x_vals),
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'max_x': max(x_vals),
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'count': len(x_vals)
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}
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print("\nX-position ranges by link (local coords):")
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for link, data in link_x_positions.items():
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print(f" {link:10s}: x in [{data['min_x']:7.2f}, {data['max_x']:7.2f}] mm ({data['count']} markers)")
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# Check X-distance between Arm1 and Ellbow
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print("\nKey constraint analysis:")
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arm1_x = [m['position'][0] for m in markers_by_link['Arm1']]
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ellbow_x = [m['position'][0] for m in markers_by_link['Ellbow']]
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print(f" Arm1 local X: {arm1_x}")
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print(f" Ellbow local X: {ellbow_x}")
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print(f" => BOTH rotate around X-axis, so X-spread within each link is FIXED")
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print(f" => X-distance between links is FIXED in world (different local X values)")
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# Check Arm2 structure
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print("\n" + "=" * 70)
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print("ARM2 KINEMATIC CHECK (sin(a) dependency)")
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print("=" * 70)
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arm2_markers = markers_by_link['Arm2']
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print(f"\nArm2 has {len(arm2_markers)} markers")
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print("Arm2 marker positions (local coords, before 'a' rotation around Y):")
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for m in arm2_markers:
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pos = m['position']
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print(f" ID {m['id']:3d}: x={pos[0]:8.2f}, y={pos[1]:8.2f}, z={pos[2]:8.2f}")
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print("\nWhen Arm2 rotates around Y-axis (variable 'a'):")
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print(" Rotation matrix Ry(a) acts on [x_local, y_local, z_local]:")
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print(" X_world = 90 + x_local * cos(a) - z_local * sin(a)")
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print(" Y_world = y_local (unchanged)")
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print(" Z_world = x_local * sin(a) + z_local * cos(a)")
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print("\n=> X_world DEPENDS on sin(a) and z_local values!")
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# Verify: X differences between Arm2 markers
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arm2_x_vals = [m['position'][0] for m in arm2_markers]
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arm2_z_vals = [m['position'][2] for m in arm2_markers]
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print(f"\nArm2 local X values: {sorted(set(arm2_x_vals))}")
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print(f"Arm2 local Z values: {sorted(set(arm2_z_vals))}")
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if len(set(arm2_z_vals)) > 1:
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print(f"=> Multiple Z values present: X_world will differ by sin(a) contributions")
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print("\n" + "=" * 70)
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print("SUMMARY: WHICH CONSTRAINTS MAKE SENSE?")
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print("=" * 70)
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print("""
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1. RIGID BODY DISTANCES within Arm1/Ellbow/Arm2:
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✓ VALID - Fixed distances between markers on same rigid link
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✓ HELPS with: Preventing deformation, reducing degrees of freedom
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2. X-DISTANCES between links (Arm1, Ellbow, Base):
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✓ VALID - Both rotate around X-axis, so relative X is fixed
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✓ HELPS with: Preventing sliding along links
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3. X-POSITION of Arm2 dependent on sin(a):
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⚠ PARTIALLY VALID - Different markers have different dependencies
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✓ HELPS with: Constraining the a variable from Z-spread observation
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IMPLEMENTATION RECOMMENDATION:
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- Start with constraints 1 & 2 (rigid body + inter-link X)
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- Use constraint 3 as a sanity check on 'a' estimation
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""")
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